The Practice Areas

Abstract

The remainder of this book describes the practice areasand their usage experiences in industry. The practice areas provide software companies with structure to use to organize innovation. The practice areas are not written from an engineering perspective. They are orthogonal to the typical software engineering disciplines such as requirements management, architecture, testing …

The remainder of this book describes the practice areasand their usage experiences in industry. The practice areas provide software companies with structure to use to organize innovation. The practice areas are not written from an engineering perspective. They are orthogonal to the typical software engineering disciplines such as requirements management, architecture, testing …

The practice areas were distilled by observing how software companies innovate. Practice areas fulfil the following criteria:

• Relevance: They represent a common pattern that occurs in several software companies.

• Innovation-related: They represent a challenge or opportunities related to innovation, not just engineering.

• Transferable: They allow the identification of a set of key activities that can be mastered by companies and be communicated.

Based on the above criteria, eight practice areas have been identified. An overview is provided in Fig. 2.1.

Fig. 2.1

Eight practice areas for software innovation

In the remaining section, the practice areas are introduced briefly and motivated. At the end of this chapter, the structure of the practice areas is introduced.

2.1 The Practice Areas at a Glance

2.1.1 The Art of Focusing

The problem of your software company may not be a low volume of ideas. It is probable that many team members and customers produce plenty of ideas in your organization. Generating, collecting and processing these ideas can consume a large amount of energy.

The perceived malleability of software (Sect. 1.6.1) and the large innovation potential put many software companies in a situation in which there are too many ideas to pursue.

Your company may have specific innovation targets it wants to achieve. These targets are most probably not explicit and are difficult to communicate. Suppose you could steer your available creative resource in such a way that it produced ideas within the scope of these targets.

Software companies that are able to funnel the ideation process in a specified, well-defined direction have a competitive advantage over more reactive companies that shoot in all directions. Knowing what to pursue – but most of all what not pursue – is a necessary skill that software companies need to master.

This practice area is about defining (measurable) innovation targets and goals, thereby allowing funnelling of ideas in well-defined and intended directions.

2.1.2 The Art of Idea Harvesting

How do you collect ideas for your next software release? Where do your ideas originate? Who identifies and follows up ideas? Where do you store ideas and input for your product?

Several software companies were a little embarrassed when we asked them these questions. Answers included: ‘We don’t really do now, there is no time’, ‘We are not managing this explicitly’, ‘It’s Alain you should talk to, he does all of it’.

Our field studies revealed that, if present at all, most software companies have a rather ad-hoc idea harvesting process, hence the motivation for this practice area. Software companies need to consider carefully how they will harvest ideas. Ideas can originate from various sources inside and outside the company. An infrastructure will need to be put in place to store ideas systematically so they are not lost.

This practice area is about installing the mechanisms for achieving efficient and effective idea harvesting in software companies.

2.1.3 The Art of Idea Valuation

If you are a product manager in a software company, you will like this practice area and recognize the dilemma. Imagine that you are faced with a number of requests and you have to select the most valuable one. Which one do you choose? The technical refactoring proposed by two developers who can speed up future developments or the new feature proposed by a sales representative for the German market?

Once captured, the software company needs to understand the value of ideas. Attributing value to ideas is a challenging endeavour. Value can be expressed in many different ways, and value frames tend to vary greatly between different companies. Even internally in the company, different stakeholders will have different interpretations of value. We observed that this can lead to great confusion in software companies, hence the motivation for this practice area.

This practice area is about installing uniform and consistent value frame models for: (1) reasoning on the value of ideas between stakeholders, (2) making ideas ‘comparable’ and (3) finding the best ideas.

2.1.4 The Art of Openness

On several occasions, we confronted CEOs of software companies with the question: ‘Are you doing anything with open source software’? The answer was often no. Later, during interviews with the development team, it became apparent that they actually were doing much with open source communities (even contributing), but that the management was not aware of this.

In software companies, doing everything yourself is becoming an illusion. On the other hand, companies need to acknowledge about how much they actually do and do not share. Being open can take many forms. Companies can create open products (e.g., by using open source), have open development processes (e.g., open innovation) or have an open business model (e.g., business models based on open innovation). An organization should be aware of its degree of openness (or closeness) with respect to these different dimensions.

This practice area is about defining an openness strategy for the companies. It is about finding the optimal level of openness at each level, i.e., product, process, organization and business models.

2.1.5 The Art of Optimizing the Impact of Critical Experts

Some people can have a huge impact on software innovation within your company. Somehow, their productivity seems higher and their insights are invaluable when it comes to steering your innovations. Having access to these experts at the right time, even if it is only for a short time, can change the way you innovate.

Unfortunately, most of these people have busy schedules. When you come to think of it, some of them, e.g., lead users, are not even on your pay list.

This practice area is about how you can create an environment in which the Impact of critical experts for your innovation can be increased and optimized. This practice area deals with understanding your innovation bottlenecks, installing means to deal with these bottlenecks and ultimately installing communities around your innovation bottlenecks.

2.1.6 The Art of Crafting Smart Products

If you feel threatened by the abundance of software technologies out there or if other players are invading your home markets with innovative solutions, this practice area will interest you.

It will show how to exploit the ICT jungle and how to turn this threat into innovation opportunities: Making your product more user conscious, environment conscious and ecosystem conscious.

This practice area is about being smart with software. It is all about creating products that use information about themselves, the environment in which they operates, or other products in their environment, with the goal to offer new differentiating functionalities.

2.1.7 The Art of Innovation Stimulation

As software is increasing in the value chain, you may want to give higher priority to innovation, but how do you stimulate innovation in a software company when every release is a rat race to meet the next deadline?

In software engineering innovation, it often boils down to problem solving and fire fighting. There is no real innovation culture in many software organizations. Rather there is an attitude of high productivity and working towards deadlines.

Giving time and resources to innovation is a necessity, and this practice area explains how you can get the most out of that investment, and why these activities are needed. Stimulating innovation is so much more than brainstorming.

This practice area is about fostering the right culture to enable innovation. It is all about encouraging internal and external people to participate in the innovation process.

2.1.8 The Art of Innovation Incubation

You have identified a nice and promising new opportunity to explore, but it involves entering a completely new market and mastering new technologies. How will you manage the risks and how will you turn these ideas into real products or radical innovations?

As more software companies are leaving the comfort zone of incremental innovation, the need for dedicated incubation support is increasing. Incubation is the process of transforming more disruptive ideas into market solutions. Software companies may be very good at producing ideas but weak in their realization. Innovation incubation can take many forms; it can range from incremental innovations in the form of new product innovations to launching spin-out companies.

This practice area is about creating an incubation infrastructure for transforming disruptive ideas into market solutions so that the software company can move out of its innovation comfort zone in a safer way.

2.2 Structure of the Practice Areas

The eight practice areas are written by different authors and can be read independently. Each of the practice areas is structured in five main sections. A short description of each of these sections is given below.

• Description and scope

• Main activities

• Links to other practice areas

• Questions

• References

2.2.1 Description and Scope

This section describes the overall purpose and scope of the given practice area. It describes why this practice area is important to software companies and explains the typical challenges to tackle. Where applicable, it presents the way different types of companies interpret the given practice area. Examples are provided to illustrate the importance of the practice area.

2.2.2 Main Activities

This section highlights a set of core activities a company should perform in order to master the given practice area. The way a particular company interprets these activities depends greatly on the specific context in which the company operates. These activities provide a strong basis on which to start implementing the practice area.

For each practice area, a drawing similar to the one in Fig. 2.2 is provided. It is taken from the Art of Focusing (Sect. 2.3) as an example.

Fig. 2.2

Main activities of the art of focusing

As shown in the figure, the activities are clustered around three categories:

• Activities that allow a company to understand the given art

• Activities that allow a company to address the art

• Activities that allow a company to sustain the art

Activities in the Understanding the Art category are required to start or bootstrap the practice area (‘Where do you start’?). Activities in this cluster often have to do with gaining an insight into what the practice area means in the context of the organization. They explore the practice area. In the Art of Focusing practice area, for instance, the activity of Preparing the Innovation Canvas involves preparation work for activities in the other categories.

Activities in the Addressing the Art category describe activities that allow the company to implement practical measures and processes for a given practice area. In the case of the Art of Focusing, the activity of Discovering Innovation Targets describes an activity a company should perform in that practice area.

Activities in the Sustaining the Art category of activities need to sustain the practice area (‘How do you keep it alive in your company’?). In the above example of the Art of Focusing, the activity of Innovation Target Portfolio Management suggests that the company is actively managing its innovation goals on a continuous basis.

In some cases, the interpretation of the practice area is different depending on the software development strategy (see Sect. 1.8) that a company uses. If this is the case, the differences are included in the description of the practice area. In the case that an activity is only relevant to a particular development strategy, it is indicated in the scheme. In Fig. 2.2, for example, the activity Point Solution Thinking is only relevant to out-of-the-box development (label OB) and custom development (label CD). It is not relevant to project-based development because the label (PB) is not mentioned. If no labels are assigned to an activity, it is applicable to all development strategies.

2.2.3 Links to Other Practice Areas

Each practice area describes the links to the other practice areas. These links are also drawn in the scheme (see Fig. 2.2 for an example).

In the example, a link is depicted between the Art of Focusing and two other practice areas: the Art of Idea Harvesting and the Art of Innovation Stimulation. The link is shown at the level of the activities.

2.2.4 Questions

Each practice area is concluded with a series of challenging questions. They help you to reflect on the practice area in your context.

2.3 The Art of Focusing

Nick Boucart, Wim Codenie, Nicolás González-Deleito, and Peter Verhasselt

2.3.1 Description and Scope

For software product builders, a lack of ideas is usually not the problem. On the contrary: it is the abundance of ideas ‘floating around’ in the company that causes most headaches. Many software builders, especially the out-of-the-box and customized product builders, have bug databases or issue trackers filled with ideas for improving the product. The items in such issue tracking systems range from simple bug reports and feature requests to ideas for new products or processes. The real challenge for a company in this situation is to create a concrete focus for its innovations, thereby limiting the number of ideas that can really make a difference to the company. In other words: they need to define their innovation targets and decide how to reach them. This is what the Art of Focusing is all about.

2.3.1.1 Trying to Focus Today

Good ideas are valuable and a terrible thing to waste. That is why many companies we studied try to collect all the ideas that are available in the company. Most companies realize that randomly launching ideas, hoping that somebody will pick them up, is not the way to go and try to implement a comprehensive process to focus on innovation. The use of a suggestion box, whatever its form, is the most obvious approach.

In software companies, the suggestion box usually takes the form of a centrally-accessible idea database, which is the springboard for the company’s innovation efforts. Any database should facilitate the search and submission of ideas. These ‘virtual suggestion boxes’ come in all kinds of formats and shapes, including Excel files, issue tracking systems (Serrano and Ciordia 2005) and dedicated idea management tools (Diener and Piller 2010), to name a few. Some companies even open these systems up to their customers.

2.3.1.2 Idea Databases – The Cons Outweigh the Pros

The suggestion box may well be a universal concept, yet it is seldom used successfully in software companies. In most cases, employees are so enthusiastic to share their ideas that the database fills up much too quickly, even more so if, for example, the management encourages its use by offering incentives to employees who come up with ideas that are later implemented.

The abundance of ideas quickly poses challenges, however, as the database will contain suggestions in different areas, and at varying levels of maturity and detail. It is very hard and time-consuming to compare and assess this eclectic collection of ideas, making it very difficult to manage the idea database. As a consequence, the processing of suggestions takes a very long time, which disappoints and demotivates employees. Ultimately, the idea box initiatives fail because of their initial success.

2.3.1.3 Innovation Targets: An Instrument for Focusing

In order to avoid this abundance of ideas, software-intensive companies must find a way to channel the creativity of the stakeholders in a direction that is beneficial to their business and in line with the strategy of the company. They need to define clear innovation targets, thus setting tangible and measurable goals for the company with respect to innovation. These targets define the boundaries within which stakeholders can be creative and for which ideas are solicited.

Surprising as it may seem, this stricter approach actually encourages creativity, as well-defined innovation targets force stakeholders to focus on clear goals. Consequently, their suggestions will be more concrete and of a higher quality. As the ideas put forward are much better aligned with the company goals, their impact is likely to be bigger. In turn, this will result in more effective results. This is illustrated by both (Fellowforce 2011) and (Innocentive 2011) that use the concept of “challenge” to funnel ideation.

Innovation targets can be very diverse and will depend to a great extent on the type of company. Companies can define innovation targets at product level, process level or business level, and for the short or long term.

Defining the right targets for innovation solves the problem inherent to idea databases: consequently, the suggestions will be focused, more concrete and applicable within the company’s longer term strategy. This will result in an easier and less time-consuming idea harvesting and valuation process, and significantly improve the company’s efficiency.

Why is focusing so difficult for software builders ?

To best illustrate why focusing is so hard for many software builders, let us consider two examples.

Example 1

Out of the Box Inc. the organization of Out of the Box Inc. consists of many stakeholders, all potentially busy generating and processing ideas and innovations:

• Vision and Strategy : Managers who develop the corporate vision and make the strategic decisions that drive the business.

• Product Management: Focus mostly on managing the product portfolio. Here the corporate vision is translated into tangible products and services.

• Sales: The link to the ‘outside’. The sales and marketing teams take the software products to customers, negotiate deals and often capture requests for new product features.

• Development: Deals with all software engineering activities, including requirements engineering, implementation and testing, as well as support.

Why does Out of the Box Inc needs to define innovation targets?

• Scattered Ideation : Stakeholders often generate ideas stemming from their own context and perspective. Therefore, many ideas differ in nature in accordance with the stakeholder that initiated them. Ideas are therefore difficult to compare. Is an idea for a technical refactoring better than a suggestion made by a customer and reported by a sales person? This differentiation of ideas makes it difficult to create a consistent and coherent overall focus.

• Assumption-Driven Ideation: Activities and people in part of the organization are not always as aligned as they should be. This gives rise to ‘assumption-driven ideation’. Sales people assume that a certain idea is trivial to implement, while developers assume that their new product idea will eventually be a killer feature, without really knowing what customers actually want. Focusing proves challenging because only very few people, if any, get to see the big picture.

• Highly Dynamic Context: The domain of software engineering is inherently a very dynamic environment where changes in markets and technologies often require a company to shift its focus.

• Vision not Properly Translated into Usable Guidelines: Even though the company’s main value drivers are often well understood by management, in reality they do not provide a developer or product manager with sufficient guidance. Sometimes, employees spend more time arguing about how and why given features are in line with the overall company value drivers than coming up with new product features.

• Overwhelming Feature Streams: Most software products contain a large number of features, and, as illustrated above, plenty of ideas for even more features float around in the organization. Out of the Box Inc. is often tempted to just do it all, thereby creating a very feature-rich product frequently watering down the clear focus on the purpose of the software the company once had.

Example 2

The Project Company. In the Project Company, the dominant activities are fundamentally different from those of Out of the Box Inc. The prevailing activities can be divided into two categories:

• Project-Related Activities : As most, if not all, software at the Project Company is developed within the scope of well-defined customer projects, each of the projects forms a stream of activities in itself. In addition, each project is already highly targeted at the customer’s individual requirements and at ensuring an optimum software delivery process to the customer. In many of the projects run by the Project Company, methodologies like Scrum ensure that the teams are focused on delivering.

• Cross-Project Activities : These are initiatives deployed by the company across projects. They can include the development of frameworks to speed up the project work, initiatives to stimulate knowledge sharing and transfer between projects, etc.

Why is it so difficult for the Project Company to focus?

• Unavailability of Resources: The great majority of the company’s resources are allocated to individual projects. Yet, company-wide innovation – like speeding up the execution of projects, developing different kinds of services, creating a shared infrastructure – cannot be achieved within the scope of a single project. Furthermore, as staff are often assessed on the results of their projects, activities that contribute to common, non-project-specific goals are not prioritized and therefore performed in-between project tasks.

• Timing: Simply bringing people together to work on cross-project initiatives proves difficult: what is the incentive for them? If the Project Company is unable to answer this question properly and clearly, and cannot demonstrate the objective of the exercise, it will have a hard time convincing its people to go the extra mile.

• Framework Development: Many organizations, like the Project Company, focus on developing frameworks and infrastructures that can become common building blocks to be used in all projects, and as such they aim to create leverage between projects. Even though these structures may help channel the focus initially, they are often a source of distraction. The innovation needs of the individual projects will typically conflict with them, and much time and energy will be lost arguing about the correct approach.

2.3.1.4 Examples of Innovation Targets

To conclude this section, a number of example innovation targets are presented as an illustration. It is clear that innovation targets are company-specific, yet some commonalities can be observed across companies, especially between companies operating within similar product development models.

Example 1: Innovation targets for out-of-the-box product software builders.

It should not come as a big surprise that many out-of-the-box product builders define product-related innovation targets, although some process-related targets are also seen:

• Collect ten ideas to adapt our offering so we can enter this new market and have a reach a market share of 10%.

• Collect five ways to solicit early feedback from users for our new upcoming product release.

• Find five ideas to develop new revenue streams with our products and services that earn us at least ten thousand euro per month.

• Identify four data resources we could exploit.

• Make three proposals to break down our complex legacy product and derive a suite of point solutions out of it.

Example 2: Innovation targets for project-based software builders

One of the big challenges project-based companies face with respect to achieving growth is that their way of operating is very resource hungry. In fact, if they want to do twice as many customer projects, they need to hire twice as many people. Many project-based companies define innovation targets around this challenge, although project companies also often tend to define process-related innovation targets:

• Identify four ‘things’ we can share across projects, such that the execution of the projects is speeded up by 20%, allowing us to do 20% more with the same resources.

• Identify two areas of expertise that we could ‘productize’ as new solutions, rather than just deploy the expertise in our projects.

• Collect ideas to improve the accuracy of our estimates by 15%.

Note that innovation targets are not phrased as questions. They follow a grammatical structure that starts with a verb and is followed by a quantifiable goal or result.

2.3.2 The Art of Focusing – Main Activities

Although the basic principles of innovation focus are universal, the recipe for success is different from one software company to the next (Dehoff and Neely 2004). Describing a number of template innovation targets is therefore impossible. In this chapter, we elaborate on the main activities companies must deploy in order to identify the targets that best suit them and master the Art of Focusing (Fig. 2.3).

Fig. 2.3

Main activities of the art of focusing

2.3.2.1 Preparing the Innovation Target Canvas

In order to identify effective innovation targets, a company needs to understand the environment in which it is operating (i.e. the innovation target canvas). It needs to understand its own position in the value chain, its value propositions, the activities it deploys for delivering this value proposition, etc. (Kim 2005; Osterwalder and Pigneur 2010). Other types of information, ranging from market demand and trends, technological trends, own products and technologies, etc. can be part of this ‘innovation target canvas’. If a company fails to compose such a canvas, it will fail to spot effective innovation targets.

Some useful questions when building an innovation target canvas:

What products and services is the company actually selling?

What kind of assets does the company hold?

What does the company’s business model look like?

What are the main elements?

These questions are especially important for bigger, more mature companies with many legacy products and services:

How can we leverage resources in new ways?

Trends analysis: which trends in our industry can we harness?

What are the anticipated customer needs?

2.3.2.2 Point Solution Thinking

Many companies try to make their products as generic as possible in order to appeal to a larger audience. Examples are CRM and ERP systems, collaboration platforms, database software, etc. This makes it very difficult to define and state their exact value proposition. The scope of the company is then so broad that it becomes almost impossible to define a reasonable number of innovation targets that fully grasp the company’s innovation ambitions.

In order to counter this problem, many software companies are converging their offering towards point solutions, i.e., solutions that solve one particular problem without considering related issues. In doing so, they try to make their value proposition much more tangible and specific and focus on how the company differentiates itself from the competition.

Companies that apply point solution thinking will find that they become better at deriving concrete value propositions from their ideas. This will help them put constraints on ideas, and as such even stimulate creativity.

Defining innovation targets will indeed be easier for companies that have these point solutions, but of course building point solutions is not an option for every companies. For example, this activity applies less for project companies.

2.3.2.3 Innovation Target Discovery

Innovation target discovery can be described as translating potential value propositions into concrete and measurable goals, respecting the company’s specifics. The company will use its innovation target canvas as input to do this. Innovation targets thus create a context in which stakeholders can be creative. The challenges the company is facing constitute another source for innovation target discovery. These challenges may relate to engineering, but they may well be organizational or linked to marketing. The discovery of innovation targets is a creative process in itself and should therefore be treated as such.

2.3.2.4 Innovation Target Pitching

Once an innovation target is defined, it needs to be communicated to the stakeholders. As it is crucial to convince stakeholders of the importance of these targets, the innovation targets really have to be pitched and sold to them.

Arguing clearly and passionately in favour of an innovation target and making a case as to why you should start thinking in this or that direction is a prerequisite for stimulating the creativity of your stakeholders, given the fact that many stakeholders will interpret an innovation target from their perspective, it is necessary to adapt the pitch for the innovation target to the different audiences. Failing to pitch a given innovation target will almost always result in a misunderstanding of the target, thereby leaving too much room for interpretation by different stakeholders, resulting in a loss of focus.

2.3.2.5 Innovation Target Campaign Design

Once a company has identified a certain target, it should start thinking about the best way to address the given target. The way it is addressed depends greatly on the individual targets: some innovation targets can be addressed during short intensive brainstorms behind whiteboards, while other innovation targets may require big sustained campaigns supported by online platforms reaching hundreds of people.

An example from industry can be found in (Fraser 2005).

2.3.2.6 Innovation Target Portfolio Management

Innovation target discovery is not an exact science with only one possible result. Just as a software builder’s environment may contain a wide variety of ideas, so that company can set a broad range of potential innovation targets. That is why, depending on their size and structure, and the number of on-going initiatives, companies usually have a number of innovation targets running in parallel. Note that this is true for many companies, although these targets are often not made explicit. This gives all employees the opportunity to participate in a campaign, as otherwise, many people would be left out when the innovation target is purely technical.

Managing the portfolio of innovation targets is an art form in its own right. The company needs to determine when to launch which innovation target and decide which innovation targets are no longer valid. At the same time, an understanding of how well stakeholders respond to innovation targets should be developed. Can they handle more targets without losing focus? Determining and understanding the level of engagement of your stakeholders is crucial, as launching many innovation targets at once may overwhelm them and cause distortion in the focus, resulting in scattered contributions and too little progress. On the other hand, if too few innovation targets are launched, companies risk not using all the available innovation potential.

2.3.3 Relations with Other Practice Areas

The Art of Focusing provides input to the Art of Idea Harvesting through innovation targets.

Innovation targets can be used to stimulate innovation within the company. Through well-defined challenges you can promote the creativity of your people.

Innovation targets put forward measures for success, depending on the individual targets, and as such deal with the Art of Idea Valuation.

For each innovation target that is put forward, it is necessary to assess how open to be in addressing the target. Which stakeholders do we invite? External, internal or both? As such, the practice area of focusing interacts with the Art of Openness practice area.

2.3.4 Questions

In order to start thinking about the Art of Focusing, you could ask yourself the following questions:

• What is your focus with respect to innovation? Are your initiatives well aligned or quite scattered?

• How do you identify your innovation targets?

• What are your innovation targets? Do you explicitly define on what you should innovate?

• How do you measure your innovation targets? Do you define metrics and KPI’s for your innovation targets?

• Who defines your innovation targets?

• How do you follow up trends in your domain? How do you keep up with evolutions in technology? How do you communicate all this within your organization?

• How and when do you evaluate your innovation targets?

• How does time affect your innovation targets?

• How do you ensure that everyone who should know about the targets actually does?

• How do you motivate people to engage with your targets?

2.4 The Art of Idea Harvesting

Wim Soens

2.4.1 Description and Scope

Idea harvesting is quite straightforward as a concept. It is about capturing and storing ideas as they emerge from different sources across and beyond the organization (i.e., ideation) and subsequently shaping them into high-value concepts (i.e., concept definition) ready for further exploration.

As simple as it may seem, the practice of idea harvesting is not trivial. Yet, when it comes down to end-user involvement in idea harvesting – also known as crowdsourcing – software companies have an enormous advantage over other industries. Today’s online technology offers software builders the unique opportunity to continuously monitor and observe the way end-users use their software, in addition to conventional techniques of online polling and questioning end-users, which have already been adopted by other industries. The tracking, logging and interpretation of real-time behavioural data provide a huge source of inspiration for new software features and even entirely new business models. The main advantage of this approach is that it is a non-intrusive technique that remains hidden to the end-user compared with other techniques, which require active user participation.

In order to exploit this possibility fully to their advantage, software companies need to set up an efficient process to capture, organize, shape and execute diverse ideas flowing in from different sources. Today, many software companies use their bug or issue tracking system for this, with ideas taking the form of feature requests. This approach is suboptimal for a number of reasons. First, the real purpose of issue tracking systems is to support engineering activities. Hence, they are located in the New Product Development (NPD) phase of the innovation process, which comes after the Front End phase in which the real ideation should be happening. Second, issue-tracking systems are by default closed and process-centric applications that do not correspond to the (semi-) open and people-centric nature of collaborative idea management tools.

In this practice area, we do not put much focus on idea generation and creativity techniques, as this topic is addressed in the Art of Innovation Stimulation practice area. The real issue here is how to trigger the idea generation process and then – after the ideas have been generated – how to capture and further process the ideas. Later in this chapter, we cover the different activities related to idea harvesting (the hows) in detail, but first we start by explaining the challenges at hand (the whys).

The Art of Idea Harvesting focuses on addressing three specific problem domains:

• Balancing the quantity and quality of ideas

• Eliminating screening bottlenecks

• Minimizing assessment risks (Fig. 2.4)

  Fig. 2.4

  

  Common problems related to the art of idea harvesting

2.4.1.1 Balancing the Quantity and Quality of Ideas

In order to increase the value, number and success probability of ideas and concepts entering the development process, software companies have to evolve from a closed innovation process controlled by a centralized and collocated research team towards a more open, collaborative way of innovating (see Sect. 2.6).

The opening up of the ideation stage of the innovation process to larger groups has proven to have a strong positive effect on the number of harvested ideas (Valacich et al. 1992). The downside of open ideation or crowdsourcing, however, is that the quality of the idea portfolio – expressed as the ratio of radical ideas (i.e., ideas touching a solution or problem areas that are new to the company and still have to be explored) versus incremental ideas (i.e., ideas that stay well within a company’s trusted solution and market domains) – does actually deteriorate. Of course, it could be argued that the quality ratio does not really matter because the probability of ending up with more radical ideas does increase with quantity – albeit not proportionately (Reinig and Briggs 2008). The consequence, however, is that the huge number of ideas that has to be harvested for that purpose may cause a screening bottleneck downstream, which should be avoided in order to drive a constant flow of ideas towards implementation in the software development process. Hence, in order to maintain a good balance between quantity and quality, it is crucial to give strategic guidance and focus to an innovation community. The harvesting of ideas should therefore not be restricted to capturing unsolicited ideas. It is also good practice to solicit ideas actively through targeted innovation campaigns (see Sect. 2.3).

2.4.1.2 Eliminating Screening Bottlenecks

Crowdsourced ideation often introduces a strong first-screening problem because of the large number of unstructured ideas that is injected into the innovation funnel. The scarcity of review resources (see Sect. 2.7), the sequential nature of the screening process and the high uncertainty of determining the success probability of ideas and concepts causes a bottleneck at the front end, which in turn threatens to stall the complete innovation process. Once people start to feel that their ideas remain ‘undealt with’, they will eventually stop sharing them. We will come back to the motivational aspects of idea generation in more detail later, but it must be clear that a good process backbone is needed to build and sustain a strong innovation culture.

There are several approaches to improving screening efficiency, but most companies tackle this problem by implementing a professional idea management software tool (an option that is generally preferred over the more expensive alternative of increasing screening resources and frequency). The market of idea and innovation management tools is growing exponentially, and many solutions are available today, from very simple and low cost solutions to very advanced and expensive ones. They all offer some kind of Web 2.0 aggregation technology to identify, track, filter, rank and analyse ideas in order to improve screening efficiency. Most tools use a simple collaborative filtering algorithm based on explicit voting. More advanced tools use aggregators that predict the future success of ideas with complex algorithms that combine explicit peer-review data (voting and scoring) with implicit community behavioural data such as page views, ratings, social bookmarks and tags.

2.4.1.3 Minimizing Assessment Risks

Opening up the front end of innovation and successfully addressing the above-mentioned challenges eventually results in rich and valuable ideas or concepts being produced. The final challenge is then to choose which ideas or concepts to invest in for further development (see Sect. 2.5). This is a difficult decision due to the high uncertainty in the early development stage. On the other hand, there is little room for error, as the cost of failure increases exponentially from this point onward.

The basic approach to minimizing assessment risks is to evaluate the idea or concept from as many different and diverse angles as possible. Here too, software technology can bring an answer. Collaborative innovation management systems tackle this assessment challenge by tapping into the collective intelligence of large innovation networks using group decision support systems (GDSS). The clear benefits of using a GDSS (over more traditional assessment techniques) are more precise communication and cross-pollination (members are empowered to build on the ideas of others), leading to a more objective evaluation of ideas.

2.4.2 The Art of Idea Harvesting – Main Activities

There are several ways to organize and structure idea harvesting, depending on the specific innovation strategy (e.g., incremental vs radical, tech push vs market pull …) and the goals that need to be achieved, but any process will usually consists of five major activities (Fig. 2.5):

Fig. 2.5

Main activities of the art of idea harvesting

• Triggering Ideas

• Capturing Ideas

• Organizing Ideas

• Shaping Ideas

• Idea Portfolio Management

2.4.2.1 Triggering Ideas

There are two basic approaches to triggering ideas. The first is to call for ideas through targeted innovation challenges or idea campaigns (i.e., solicited ideation). This practice is covered extensively in another chapter (see Sect. 2.3).

The second approach is to create an innovative culture that stimulates people to share their ideas spontaneously (i.e., unsolicited ideation). Stimulating creativity by fostering the right innovation culture is a practice area in itself (see Sect. 2.9) dedicated to creating an inspiring environment to encourage internal and external people to generate and share ideas. In order to turn ideation into a continuous and self-sustaining process, however, the stimulation of spontaneous ideation should also be strongly embedded into the idea harvesting process, mainly by providing effective inspiration and feedback channels.

Triggering ideas for out-of-the-box software companies

The activity of triggering ideas is of special concern to software companies offering out-of-the-box solutions to the market because their relationship with the end-user is more distant and indirect than that of custom software developers. The latter have a very close and direct relationship with their customers, which in most cases are also the end-users. Close interaction with the customer/end-user is a natural part of a custom development project, creating many opportunities for both parties to share knowledge and ideas in a very spontaneous way.

For most out-of-the-box software companies, the direct customers are retail partners, not end-users. More importantly, neither retail partners nor end-users initiate (let alone finance) the software development project, which is solely the responsibility of the software developer. In order to trigger ideas from end-users, out-of-the-box software companies have to invest in dedicated communication channels to inform the end-user community about the project and provide a transparent platform on which to share and discuss ideas.

2.4.2.1.1 Inspiration

Inspiration can come from many different sources but probably first from other people’s ideas. The provision of a transparent repository in which to browse and search for all ideas will trigger many new ideas. Repositories as such tend to fill up with a huge number of very diverse ideas over time, and it is necessary to provide additional tools such as recommender systems or social bookmarking to help users find ideas that may inspire them. Most idea management systems let users vote and tag other ideas and then use these votes and tags to suggest other links they may find interesting. High-end tools use advanced recommendation algorithms or correlation engines to achieve cross-fertilization of ideas.

As well as ideas, other types of content such as papers, blog posts, news articles, etc. can inspire users and trigger new ideas. When setting up an environment for capturing and sharing ideas, it is therefore good practice to allow users to also publish and share experience and knowledge in all possible formats

2.4.2.1.2 Feedback

It is very important that idea owners are able to follow up the status and progress of the ideas that they (and others) have submitted. Efficient and transparent feedback channels are therefore a key requirement of any idea harvesting system. Feedback can be partially automated and communicated through e-mail notifications or dashboard messages that are generated based on user activity data. Peers or superiors should also give feedback about ideas or other contributions in a personal way during informal and even formal conversations.

2.4.2.2 Capturing Ideas

The main concern here is to capture all ideas. In order to master the activity of capturing ideas, there are four important aspects to look into: openness, accessibility, ubiquity and diversity.

2.4.2.2.1 Openness

Idea management software tools have become widely accepted in most industries because of their effectiveness at harvesting ideas. The level of openness of such systems varies greatly from one company to another (see Sect. 2.6).

When companies start to adopt idea management tools they usually opt for a closed system in which access is only granted to internal employees, i.e., closed ideation.

More experienced companies will gradually open up their ideation system to selected external partners such as university labs, knowledge centres or key suppliers, i.e., semi-open ideation.

The use of true Ideagoras – places on the Internet where large numbers of people and/or businesses gather to share ideas – is growing in importance, and an increasing number of companies have already successfully adopted this strategy, i.e., open ideation.

Ideagoras fall into three broad categories:

• True-Market Ideagoras

  Intermediary brokers organizing ideation campaigns for their clients set up this type of Ideagora. Contributors (or problem solvers) are usually attracted and incentivized with cash rewards or prizes. Well-known market Ideagoras are innocentive.com, yet2.com and ninesigma.com.

• Competition-Based Ideagoras

  A competition-based Ideagora generally works on one specific problem or challenge launched by one promoting company. The competition is usually open to anyone, offering a chance to win prize money for solving a problem. A well-known example in the software industry is the US video rental company Netflix’s competition to improve its recommendation algorithm, offering a $1 million prize to the winner.

• B2C Ideagoras

  This type of corporate Ideagora engages customers to bring in ideas on ways to improve a company’s product or service. They are typically hosted by big companies with strong brands. B2C Ideagoras tend to generate incremental ideas that are generally not rewarded financially. Two very popular examples are mystarbucksidea.com and Dell’s IdeaStorm.

2.4.2.2.2 Accessibility

It should be extremely simple and straightforward to submit and share ideas. It should not take more than a few seconds for anybody to submit an idea; otherwise people will not bother. Idea forms should be very basic: an idea title and a short description should be all that is needed to capture and register an idea. Remember that this is the only and most important thing at this stage. It is not a problem that the idea will not be fully fleshed out. Many companies make the mistake of forcing users to fill in complex idea forms with many mandatory fields. This will discourage idea submitters and many ideas will never make it to the submit button. There will be enough time later to complete the ideas (see Sect. 2.4.2.4).

2.4.2.2.3 Ubiquity

Ideas can emerge during many activities and in different places: discussions with people in meeting rooms, producing reports behind a desk, interacting with others at the coffee machine, handling requests from customers on the phone, reading reports on the train …

Capturing ideas where and when they occur is key to successful idea harvesting. Idea management systems should therefore be ubiquitous, i.e., accessible anywhere, at any time and through any media, e.g., smartphones, LANs, the Internet, messaging software and e-mail clients. In the specific case of software or software-intensive products, ubiquity can also be achieved by integrating online idea publishing functionality into the software itself. As already mentioned in the introduction to this practice area, this is a unique opportunity for software companies and it is currently not being exploited fully.

2.4.2.2.4 Diversity

On a personal level, diversity triggers alternative ways of thinking and behaving. Hence, people who live in intersections of social worlds (i.e., people on the ‘edge’ of organizations) tend to have better ideas than people with a higher network constraint (Burt 2003).

The identification and management of idea sources for maximum diversity is therefore crucial to harvesting quality ideas. Diversity means involvement of people from multiple disciplines in the ideation process, internal sources (marketing, sales and software engineers) as well as external sources (research partners, suppliers, customers and end-users).

With applications such as Facebook and Twitter, software technology has become deeply social. As such, it has become a key enabler to exploit effectively the diversity of large user communities. Through social software, end-users can become an integral part of the innovation and development ecosystem. As a consequence, products – especially software products – are becoming dynamic in the sense that they are not merely consumed or used as they are but are customized, redesigned or even re-engineered to fit the specific requirements of individual users or user groups (von Hippel 2005). Social media are an important source for innovation. Observing and listening to these channels in order to capture new ideas must become a best practice in every company (Fig. 2.6).

Fig. 2.6

Networked innovation

2.4.2.3 Organizing Ideas

This activity consists of filtering, merging, ranking and/or clustering all captured ideas in order to prepare them for further processing. Depending on the innovation strategy and the expected outcomes, however, the organization (and processing) of ideas has to be managed in different ways.

There are four types of innovation, which are visualised in the graphics below (core growth, market pull, technology push and basic research), though in fact only Classes I, II and III are relevant domains for applying idea-harvesting techniques. Basic research (Class IV) innovation falls outside the scope of this practice area because it is a highly knowledge-centric domain. As such, ideas cannot really exist in this space of unknown unknowns because in order to be explicit they must be linked to at least one known problem or solution domain. Hence, there is less need for a true idea harvesting system here. A collaborative knowledge management system is a much better option (Fig. 2.7).

Fig. 2.7

Four types of innovation

2.4.2.3.1 Organizing Class I Ideas

For core growth ideas (incremental or Class I innovation), a sequential process-driven approach is most common. The basic concept is to separate the good ideas from the bad ones based on simple quantitative criteria such as cost/benefit ratio, technical feasibility and development cost. Less than 20% of all ideas usually survive this initial screening, with other ideas being ‘killed’ or archived.

Here, the main challenge is to design a process that can screen large numbers of ideas. This problem is usually tackled by tapping into the collective intelligence of an innovation network through community voting, based on the popular theory from Surowiecki (2004a) (Wisdom of Crowds) that the aggregation of information within a community can lead to better decisions – better than could have been made by any single member of the group. In practice, screening algorithms based on explicit voting prove to be effective in solving screening bottlenecks, but the quality of the filtering may still be questioned. (Are we sure we did not ‘kill’ good ideas?)

In order to improve screening quality, more advanced innovation platforms try to predict the future success of ideas with collaborative ranking algorithms that combine explicit voting with implicit community behaviour data such as page views, ratings, bookmarks and tags. Provided these algorithms have used the correct association rules, i.e., the relation between the value of an idea and a certain activity (e.g., bookmarking), this approach has proven effective. The key issue, however, is that association rules differ from one community to another due to the variation in behavioural patterns, and they are influenced by cultural, social and other differences. Community behaviour also tends to change over time within the same community. As a consequence, the fine-tuning of these algorithms (usually by trial and error) is a complex, time-consuming and never-ending effort.

In order to solve the problem described above, a new generation of algorithms is emerging. These adaptive (or self-tuning) collaborative ranking algorithms use data mining to extract association rules from activity facts in relation to the success rate of ideas. In other words, the algorithms seek relations between the collaborative behaviour of an online innovation community and the value of the ideas and concepts it generates in order to predict the value of new ideas based on these behavioural patterns.

2.4.2.3.2 Organizing Class II & III Ideas

For radical innovation (or Class II and III innovation), a sequential process will not do because ideas need to develop organically before being subjected to a quantitative assessment. Pushing ideas through a quantitative assessment would simply kill most of the so-called ‘out-of-the-box’ ideas, which are exactly the type of ideas that are needed for this kind of innovation. Instead, the organization of ideas should focus on finding and clustering those ideas that carry a germ of a strong innovative concept and need to be developed further during incubation. Hence, instead of a process-centric approach, a people- (or network-) centric approach is more appropriate. In Class II and III innovation, an emergent and people-centric collaborative model is therefore better than the Class I sequential and process-focused stage gate model.

The core architecture of such ‘collaborative systems’ is built around creation spaces in which communities can address innovation opportunities and challenges, generate and share ideas and insights and shape them into strong concepts with strategic value for the company.

In order to facilitate the process of filtering and clustering ideas, these systems apply the concept of ‘Collaborative filtering’. Collaborative filtering is part of a bigger concept called ‘harnessing collective intelligence’ (coined by), which refers to using advanced social science algorithms to identify, track, filter, rank and analyse social media content. It also includes applying semantic technology to track discussions on specific topics and analysing the share of voice and tonal sentiment.

Collaborative Filtering

The term collaborative filtering was first used by David Goldberg at Xerox PARC in 1992 in a paper called ‘Using collaborative filtering to weave an information tapestry’. He designed a system called Tapestry that allowed people to annotate documents as either interesting or uninteresting and he used this information to filter documents for other people.

There are now hundreds of web sites that employ some kind of collaborative filtering algorithm for movies, music, books, dating, shopping, other web sites, podcasts, articles and even jokes.

Examples of ‘Harnessing Collective Intelligence’:

• PageRank algorithm (Google)

• ‘Interestingness’ algorithm (Flickr)

• ‘People who bought this also bought…’ feature (Amazon)

• ‘Similar artist radio’ algorithm (Last.fm)

• Reputation system (eBay)

• AdSense (Google)

2.4.2.4 Shaping Ideas

As idea submission has to be made extremely easy (see Sect. 2.4.2.2), it is very likely that the initial idea description will not be much more than a captive title and a short abstract. To allow for a detailed review and reduce the assessment risk, however, a full idea description that addresses all review criteria is needed. This is why an additional shaping activity is needed.

2.4.2.4.1 Shaping Class I Ideas

With regard to organizing ideas, the activity of shaping ideas is handled differently for incremental (Class I) ideas vs radical (Class II and III) ideas. The shaping of incremental ideas usually takes one or two iterations with the idea generator itself in order to ‘fill in the gaps’ and prepare the idea for review, for which the assessment criteria are quantitative and very well defined. Shaping consists of documenting the idea (e.g., with drawings) or building up a good case against the evaluation criteria (e.g., what the costs and the benefits are, whether it is technically feasible, etc.).

2.4.2.4.2 Shaping Class II & III Ideas

Shaping radical ideas – in order to turn them into concepts – takes more time, is more complex and needs the engagement of several people besides the idea generator. In most cases, radical concepts are the result of combining and building on several other ideas over time. These kinds of emergent processes are quite ‘fuzzy’ and organic, and not yet fully understood by social scientists, let alone applied by process designers. The current state-of-the art in this domain is still at an experimental stage, and no real standards or best practices have been defined yet. Innovative, collaborative software companies are already implementing socio-cognitive features in collaborative innovation software, however, in order to leverage the social dynamics of communities, for instance, by integrating social science technology to connect people and knowledge in order to trigger ‘serendipitous’ events.

2.4.2.5 Idea Portfolio Management

Idea Portfolio Management is about creating and maintaining a well-balanced portfolio of ideas based on a number of different criteria such as the strategic innovation domain, innovation class, development time, investment, risk, etc. The main goal of idea portfolio management is to secure continuous output of ideas addressing short-term business improvements (doing things better) as well as long-term business opportunities (doing things differently).

2.4.2.5.1 Strategic Innovation Domains

The top-level ‘strategic’ differentiators of ideas are their innovation domains, which can be categorised into four main domains and ten sub-domains according to the model by Doblin (see Table 2.1).

Table 2.1 Ten types of innovation

Innovation is not just about improving product performance, although it is still the domain in which most companies ‘fight their battles’. Too few companies realise that there are many innovation opportunities besides the product performance domain. There are huge opportunities for innovations in the business model domain, especially for software companies. Dell, for instance, became very successful in the finance category domain by making the customers pay for their PCs before assembly and shipment. Another well-known example in this domain is software companies that changed their payment model from charging flat licence fees to offering free basic functionality with paid special services. Yet another example, this time in the product system domain, is bundling several software applications into a single ‘suite’.

2.4.2.5.2 Innovation Portfolio

Inside each of the ten strategic innovation domains, all four classes of innovation that were described earlier apply. This results in a 3D space that can be used to map all ideas, research projects, development projects and products or services in the innovation pipeline (Fig. 2.8).

Fig. 2.8

Innovation portfolio

In order to obtain a well-balanced innovation portfolio, ideas should be harvested in all four main innovation categories (i.e., finance, process, offerings and delivery) and innovation classes I, II and III (i.e., core growth, market pull and technology push). A good balance does not mean that there has to be an equal distribution of ideas across all innovation categories and classes. This should not be an objective as it is practically unachievable. There will always be more Class I ideas than Class II and Class III ideas (which are harder to obtain), and most of them will be situated in the product performance domain (because this domain is directly related to your offering). It is important, however, not to neglect the other domains and to take the appropriate steps to harvest a substantial proportion of non-Class I product performance ideas. Targeting specific ideation campaigns in the other domains can do the trick (see Sect. 2.3).

2.4.3 Relations with Other Practice Areas

• Art of Openness

  • Balancing the quantity and quality of ideas:opening up ideation to larger groups in order to increase the value, amount and success probability of ideas and concepts entering the development process

  • Capturing Ideas:the three levels of openness: closed ideation, semi-open ideation (selected partnerships) and open ideation (true Ideagoras)

• Art of Focusing

  • Balancing the quantity and quality of ideas:it is crucial to give strategic guidance and focus to an innovation community through innovation targets.

  • Triggering ideas:one of the basic approaches to triggering ideas is to call for ideas through innovation challenges or idea campaigns (i.e., solicited ideation)

  • Idea Portfolio Management:focused ideation campaigns to push an innovation community outside its comfort zone in order to harvest radical ideas (Classes II and III)

• Art of Optimizing the Impact of Critical Resources

  • Eliminating screening bottlenecks:the scarcity of review resources – among other problems – can cause a bottleneck in the front-end ideation process.

• Art of Idea Valuation

  • Minimizing assessment risks:dealing with the high uncertainty at the front end to choose the right ideas or concepts for further development

• Art of Innovation Stimulation

  • Triggering Ideas:another approach to triggering ideas is to create an innovative culture that stimulates people to share their ideas spontaneously (i.e., unsolicited ideation)

• Art of Innovation Stimulation

  • Triggering Ideas:Another approach to trigger ideas is to create an innovative culture that stimulates people to spontaneously share their ideas (i.e. unsolicited ideation).

2.4.4 Questions/Checklist

• How can you find a good balance between the quantity and quality of ideas?

• How can you avoid or eliminate screening bottlenecks?

• How can you minimize the risks of idea assessment?

• How should you provide effective inspiration and feedback channels in order to stimulate spontaneous ideation?

• How can you create open, accessible, ubiquitous and diverse harvesting systems in order to capture ideas efficiently?

• How can you filter, merge, rank and/or cluster all captured ideas in order to prepare them for further processing?

• How can you organize and process ideas based on your specific innovation strategy and the expected outcomes?

• How can you shape different types of ideas?

• What are the top-level ‘strategic’ differentiators of ideas?

• How can you distribute the ideas in the innovation portfolio across the different innovation categories and innovation classes?

2.5 The Art of Idea Valuation

Wim Codenie, Nick Boucart, and Tom Tourwé

2.5.1 Description and Scope

Consider the following scenario. You are a product manager in an out-of-the-box software company and have to decide which features to include in the upcoming release of your flagship product. You have carefully assessed all the requests in your issue tracking system and considered all the estimates provided by the developers.

There is only room for one more request. It is up to you to choose. Two options are available: request number 89 and request number 543. Request 89 is a feature that is highly attractive to the Brazilian market. Request 543 is technical refactoring in the data access layer, resulting in a moderate performance gain, better overall reliability and easier maintenance.

Which one will you choose? Which of these two requests is most valuable?

The scenario above demonstrates that for out-of-the-box software companies, the Art of Idea Valuation is all about mastering release definition, the process of determining the content of the next product release by selecting the most valuable requirements from a large pool of ideas (Tourwe et al. 2009a).

Now consider a second scenario in which you are the CEO of a project-based software company.

One morning, two of your lead architects enthusiastically pay you a visit and pitch an exciting new idea to you to introduce a framework that could be leveraged in most, if not all, the company’s customer projects.

The architects argue that such a framework would dramatically speed up development, increase the productivity of the developers, create a standardized way of working and reduce the chances of reinventing the wheel. Looks nice doesn’t it!

You lean back in your chair; sigh silently and think: once again two guys struck by framework fever. This proposal is at least the sixth ‘framework proposal’ you received this year. You received one for a user interface framework and three for data persistency frameworks. Only a week ago, two people suggested a security framework that would bring us nothing but benefits.

All these proposals are attempts to share and reuse knowledge between projects, and although all these proposals were made with the best intentions, calculating the return on investment of such initiatives seems very hard.

The scenario above demonstrates that for many software companies that use a project-based development strategy, the Art of Idea Valuation has much to do with understanding the return on investment of cross-project initiatives. In individual customer projects, the value of what is delivered is usually clear; for project companies, it is the customer that dictates which innovations are most valuable. The release definition problem is less relevant to these companies.

An overview of the way software companies value ideas can be found in Tourwe et al. (2009b). We briefly describe three common strategies on the way companies handle this.

2.5.1.1 Idea Valuation by an Enlightened Product Manager

Many organizations, especially software companies producing out-of-the-box software, appoint a gatekeeper, in the form of the product manager, to resolve the valuation challenge. The product manager guards and structures the potential requirements and selects the best ones. In order to do so, the product manager studies the market and competitors and listens to customers, users and prospects in the hope of spotting the most interesting opportunities. All this information should give the product manager enough insight to choose the most valuable requirements, leaving less valuable ones for later.

Managing all this quickly becomes a complex task for the product manager. In fact, the product manager needs to combine different pieces of information to determine the value of a potential requirement (e.g., business value, technical risk, cost, etc.). In many cases, this information is scattered across different people within the organization, incomplete and even tainted by personal opinion. In practice, the task of valuing ideas is simply too complex and overwhelming for any single person.

2.5.1.2 Idea Valuation by Voting

Another technique for valuation used by software companies is voting. Participants are presented with a list of requirements and ideas and are asked to cast a vote on those requirements they like most. This can be in the form of simple yes/no voting, or voting with a number of a particular scale (e.g., one to five). The requirements that receive most votes are considered most valuable.

Due to their simplicity and ease of use, voting systems seem attractive. Unfortunately, they are not without problems: in order for a stakeholder to cast an informed vote, he/she needs to understand all the aspects not only of the given requirement but also of all others. In fact, it is only then that a person can truly understand when to vote yes and when to vote no.

Understanding the advantages and disadvantages of each and every request is time-consuming for stakeholders and requires them to be very knowledgeable about all the value aspects. Hence, for many software companies, voting does not completely meet their needs when it comes to valuation.

2.5.1.3 Idea Valuation by a Requirements Prioritization Algorithm

As voting is clearly simple and simplistic at the same time, people have looked for ways to overcome its disadvantages while retaining its advantages. This has given rise to research into automated requirements prioritization through algorithms (Lehtola 2006). These algorithms capture the value of a requirement in a single number, computed by means of a formula that combines the values of relevant criteria in a clever way. Based on this number, the list of requirements is sorted.

Although the concept itself is quite clear and promising, it is hard to apply in practice. You may wonder whether it is possible to identify one generally applicable formula to be used by different organizations in different domains:

• What criteria should such a formula take into account? Most probably a combination of predefined criteria, such a cost, effort and risk, and user-defined criteria such as product stability or attractiveness to a given market. Some criteria may be more important than others, and a formula should also take this into account.

• Which scales would such a formula use to express a value for each given criteria? Criteria such as cost and effort can be expressed in absolute terms (money or estimated time) while others, such as attractiveness to a given market, are much more difficult to express as numbers.

• How should the uncertainty of estimates for the given values be dealt with? As the different values can only be estimated, and estimates depend heavily on the experience and knowledge of the stakeholders providing them, the outcome of the requirements prioritization algorithm may differ depending on the stakeholder using it.

Although requirement prioritization algorithms can have their merits, solely relying on them to address the Art of Idea Valuation is not enough.

2.5.2 The Art of Idea Valuation – Main Activities

The picture below describes the different activities a software company should implement in order to master the Art of Idea Valuation (Fig. 2.9).

Fig. 2.9

Main activities of the art of idea valuation

2.5.2.1 Defining Value Models

When asked, different stakeholders in a software company will give different definitions of value.

Developers will look at ‘value’ from a technical angle such as increasing maintainability of the product, increasing performance or decreasing complexity.

Sales and marketing departments will often interpret ‘value’ in terms of market share or simply revenue. For the management ‘value’ will be elements that help to realize the company mission (e.g., achieving product excellence).

Somehow the software company needs to bring together these different interpretations of ‘value’ into a value model, a terminology that stakeholders can use to reason and communicate about value. The ultimate goal of such a value model is to make it possible to compare different ideas and requests in the context of this value model.

A value model describes a set of value elements (called factors in Kim 2005). These are characteristics that are important in some way to a company and are usually linked to a particular way of realizing a competitive advantage.

Some examples are given below. Value elements can be driven by different objectives of the company:

• Quality-driven value elements (e.g., inspired by the ISO 9126 Software Quality Standard)

  • Performance of the product

  • Usability of the product

  • Maintainability

  • …

• Delivery-driven value elements

  • Trainability on the product (ease of training new users to use the product)

  • Ease of deploying new versions

  • …

• Market-driven value elements

  • Attractiveness to the German market

  • Compliance with safety regulations in a market

  • …

After having a clear value model, there is a need to establish an appropriate measure for that value. For quantitative definitions of value, these measurements can be quite easy to determine, e.g., if value is defined in terms of net present value, financial measures should be used. If the definition of value includes qualitative factors, a plethora of different measurements is available:

• Interval scoring (e.g., measuring the improvement in user experience on a scale of 1–10)

• The Kano model of customer satisfaction (Kano et al. 1984) introduces three possible values: basic, linear and exciter.

• The MoSCoW Method (Clegg and Barker 2004) proposes four values: must, should, could and won’t have.

• Strategy Canvasses (Kim 2005) visually present the value elements of the model and score them from ‘low’ to ‘high’, compared with the rest of the industry.

Many out-of-the-box software product builders have quite a complex value model, taking into account the many interpretations of value that are used in the company by different stakeholders.

As mentioned before, developers will look at value from a technical perspective while the sales and marketing department typically assesses value from a more financial and new business perspective. The biggest challenge with respect to defining the value models is solving the tension between these various interpretations of value. How do you make them comparable and how do you translate value from one interpretation to another?

Ideally, there is one value model for the whole company, but this is not always realistic.

A company we met during a survey struggled with its release definition process. It had a strong development team that pushed technical features and a strong sales team that pushed market features. It never managed to make it all comparable and had many disputes trying to sort out what was most valuable. The company solved this problem in a pragmatic way. Instead of defining one overall value model to be used by all stakeholders, different models for different stakeholders were introduced. It allocated a ‘budget’ to each release for each group of stakeholders. The company typically allocated 20% of the total release effort to requests nominated by developers, 60% to sales and marketing and 20% to the support team. Within each release slot, each stakeholder group defined its own value model and filled up its slot according to that value model.

Note that for project-based software companies, the situation is different. Within a given project, it is the customer of the project that dictates what is most valuable. The software company has to follow the value frame imposed by the customer. For cross-project initiatives, on the other hand, the value model often boils down to determining the return on investment of a certain shared activity.

2.5.2.2 Defining Constraint Models

Understanding the value of an idea is important but not enough. Software companies also need to understand the implications of realizing a certain idea. For many companies, this means that they like to understand the risks and costs associated with the idea as well as possible implications when the innovation may fail. Other properties often seen in constraint models are timing (can the innovation be delivered on time) and resources needed to implement the idea.

Fortunately, in the field of software engineering, many techniques are available for effort estimation. A good overview can be found in McConnell (2006).

2.5.2.3 Value and Constraint Association

Value and constraint association is the activity of estimating value and cost with concrete ideas. It consists of applying the value and constraint models to the individual ideas and rating them with possible values.

• Example: This idea for new functionality contributes to our goal to enter the German market (= value element). It will provide us with two new customers in Germany next year (= the value).

• Example: This refactoring of our code contributes to the look and feel of the product (=value element). It will ensure that all future new screens we develop will have the same format (= the value).

Software companies need to define who to involve in associating value with a given request, when this value association needs to be made, how it is going to be made and what method is going to be used.

Associating value is not a straightforward activity:

• As the real value of a request is only known after it has been realized, value attribution relies on estimates and guesses. As a consequence, the software company has to deal with the uncertainty associated with these values and constraints.

• Typically, a large number of requests need to be valued, which means that whatever approach is used, it needs to be scalable and efficient.

• Many different stakeholders may need to be involved in the value association activity. The value and constraint models will indicate what information is needed and hence which stakeholders to involve. Software companies may involve customers in the valuation activities to obtain valuation information directly from the market (Blank 2005a).

Several different techniques are used by software companies, ranging from relying on the wisdom of crowds by aggregating the opinions of many individual stakeholders (Surowiecki 2004b) using stakeholder weighting (Tsiporkova et al. 2006) to give domain experts’ opinions more weight, to applying lean principles such as deciding as late as possible (Poppendieck and Poppendieck 2004) so that decisions are taken when more information is available and uncertainty is reduced.

Value association strategies based on the wisdom of crowds are promising (Tourwe et al. 2009a). They try to involve all stakeholders by allowing them to express their opinions on the value of an idea. Stakeholders can use their own vocabulary when expressing the value of a requirement by using free-form ‘tags’ (e.g. ‘innovative’, ‘sellable’, ‘quality-improving’ …). Inspired by the work on folksonomies, this can allow a company-specific definition of a value model to grow in a bottom-up way.

Example: The art of Idea Valuation at Nokia Siemens Networkd (NSN), by Tuomo Kinnunen.

NSN has a business case practice for idea valuation. Business cases combine three aspects of idea valuation: market assessment, technical study and financial analysis. The market assessment checks whether an idea matches with a real need, identifies the size of the potential market, and analyses payback and pricing possibilities. The technical study investigates technical feasibility of an idea and assesses work efforts of different technical alternatives. The financial analysis utilizes a market assessment to predict added revenues by an idea. In addition, the technical study is used to estimate costs caused by bringing an idea to market. The financial analysis is culminated into an estimation of payback level and cash flow.

Business cases are used to support decision-making. For this purpose all the business case aspects are compared to strategy and risks. Technical and market risks are viewed against expected reward and strategic objectives. The aim of the business case practice is that only potentially valuable ideas for the company will go into further development.

2.5.2.4 Release Composition

Release compositions are all about taking decisions.

It is within this activity that a software company decides which requests to include and which ones not to include in the upcoming release. In order to make decisions effectively about releases, it is important to state the goals explicitly that the company wants to achieve with the upcoming release, preferably indicating the goals in a measurable way.

Examples of such goals could be: increase the performance of the product by 20%, make the product compliant with regulations in a new target market or increase the market share by 5% in the Latin-American region. Goals can be defined top-down or bottom-up. In a top-down approach, release goals are defined based on a product roadmap or strategic analysis. In a bottom-up approach, the release goal is derived from the request database itself: requests that are repeatedly asked for by customers or requests that originated from big customers may be taken as release goals in such a scenario.

Once the goal of a release is put forward, it is necessary to start populating the release, i.e., decide which requests fit best with this goal, while at the same time fulfilling the constraints, such as timing and budget. Different guidelines for populating a release exist and a full overview is provided in (Tourwe et al. 2009a, b; Karlsson 2006; Lehtola 2006). Some techniques include:

• Clustering in importance groups : These approaches divide the requirements into a small number of different importance groups. Methods include Kano (Kano et al. 1984), the MoSCoW Method (Clegg and Barker 2004) and the Planning Game (Beck and Fowler 2001). Cohn (2005) suggests selecting low-cost, high-value requests first, then high-cost, high-value, then low-value, low-cost, etc.

• Consensus-based approaches : These are specifically geared towards reaching consensus among a group of stakeholders. An example is the Delphi method (Rowe and Wright 1999).

• Multi-criteria ranking : Automatic ranking of the requirements based on the value of multiple relevant criteria and a specific formula that combines these values into a single value (Release Planner 2011).

• Pair-wise comparison : Approaches that rely on mutually comparing all requirements and identifying the most valuable one for each comparison. An example is the ‘20/20 vision’ innovation game (Hohmann 2006).

• Voting systems: Approaches that involve different stakeholders and ask each one to express his/her preference in some way or another. Examples include the ‘Buy a Feature’ innovation game (Hohmann 2006).

• Financial approaches : Approaches based on financial measures, such as the Internal Rate of Return, Net Present Value or business cases.

The number of requirements available for the next product increment influences the trade-off between a lightweight, coarse-grained approach and a fine-grained, more heavyweight approach. The latter approach can be used when few requirements are available and an in-depth analysis of each and every requirement is feasible. This makes the choice for a particular set of requirements to be included in the next release very well motivated and rational. These approaches do not scale well when the number of potential requirements is high, however, as specifying the value of thousands of requirements in detail is too time-consuming. In such cases, coarse-grained approaches can be applied.

2.5.2.5 Mastering Consensus Models

Inevitably, conflicts will arise when different stakeholders are involved in request valuation. To have a sustainable valuation process, it is important to identify the reasons for such disagreement and take the appropriate measures to reach consensus.

The reasons for disagreement on the value of a particular idea can be manifold: the idea may not be sufficiently clear to all stakeholders. The idea may have a high degree of uncertainty.

Different methods exist to identify such disagreements (e.g., planning poker, various information radiations such as internal stakeholder disagreements and stakeholder satisfaction) (Regnell et al. 2001; etc.).

Planning poker for instance offers a way of reaching consensus. It offers a workshop-based approach in which stakeholders move towards a consensus by stating their opinions and learning from one another. Other ways of reaching consensus include stakeholder weighting, which takes into account the importance of stakeholders, and the multi-step ranking algorithm presented in Tsiporkova et al. (2006).

Some companies use the enlightened product manager approach and reach consensus by definition, as only one stakeholder decides. Other companies are looking for ways to remove the bottleneck of this approach and realize that a model for reaching consensus is a necessity.

Key ingredients for mastering consensus building among stakeholders:

• Motivating value models and constraint models: Stakeholders need to understand why the company focuses on certain value elements and not on others. For example, a company desiring to enter a new market may value speed to market above feature richness, because the company wants to enjoy the first mover’s advantage. Without this rationale clearly communicated, it may be hard for certain stakeholders to understand why features that are essential in their opinion are not valued highly.

• Motivating value and constraint estimates: Claiming that an idea has a certain value is one thing. Capturing the rationale behind this claim is more difficult, especially when no obvious consensus is reached. Stakeholders should be able to communicate clearly and motivate their reasoning behind their value estimates. In line with the example above, stakeholders will have to motivate why a certain feature is essential despite the fact that it costs a considerable amount of time to implement.

• Motivating release compositions: Clear reasoning should be given why a certain release contains the given set of features and why another (maybe equally valued feature) is left out. This motivation starts by clearly motivating the goal of the release. Again, in the spirit of the above example, the release goal could be to have a minimal product available for the new target market ready to ship in 4 months from now.

• Allow the controversial requirements to emerge : There is usually consensus on the value of most ideas. For some ideas, however, the valuation by different stakeholders can be polarized. It is important that these ideas emerge, as they may be interesting to explore.

2.5.3 Relationships with Other Practice Areas

The Art of Focusing is related to other practice areas in the following way:

• Art of Focusing :Within the Art of Focusing, the company sets forward the concrete innovation goals, thereby (partially) indicating what kind of values the company is looking for. This gives guidance to the value and constraint models as well as the release composition activity.

• Art of Openness:A company will have to decide which stakeholders to include in the value association activity. It may opt to include stakeholders that are not part of its own organization (e.g., customers, suppliers, etc.).

• Art of Idea Harvesting:The link to idea harvesting is obvious; without ideas and requests, there is no real need for valuation.

• Art of Innovation Incubation:Ideas that are considered worth pursuing are candidates for incubation.

2.5.4 Questions

• How do you evaluate and rate (feature) requests? Do you follow any specific process (workflow)?

• Which criteria do you consider important for evaluating features?

• How do you compare different ideas?

• Who evaluates (feature) ideas?

• What do you do when people do not agree on idea valuations?

• How do you define the focus for a release?

• How do you select features to include in a release?

• Do you trace decisions to motivate why a feature is (not) selected?

• What are the typical disagreements with valuation?

• What happens when stakeholders do not understand certain features?

2.6 The Art of Openness

• Timo Koivumäki,
• Kaisa Koskela &
• Pirjo Näkki 

1. VTT Technical Research Centre of Finland, Vuorimiehentie 3, 1000, FI-02044 VTT, Espoo, Finland

   Timo Koivumäki (Research Professor), Kaisa Koskela (Research Scientist) & Pirjo Näkki (Research Scientist)

2.6.1 Description and Scope of the Art of Openness

The Art of Openness practice area deals with finding the best ways for different types of software companies to use the opportunities of external resources – enhancing the company’s competitiveness by using external knowledge in the innovation process and creating new revenue streams through exploitation of external channels.

Increasing dynamics in the business environment, such as the rapid pace of technological development, intensified competition through market globalization, evolution of customer needs and new technology-enabled value creation possibilities, have challenged software-intensive organizations to work more openly also in terms of innovation. The nature of the software industry, and the ICT industry as a whole, has confronted radical chances, and the scarce resources inside companies are therefore not enough to maintain their competitiveness in the dynamic market. In order to be successful, software companies need to discover ways to use the innovative potential in the ICT environment by opening the boundaries of their value creation processes. In fact, a company’s ability to absorb external knowledge has become one of the main drivers of competitiveness (Spithovena et al. 2009). Equally important is learning to maximize the value of in-house ideas that are not suitable for the company by taking them to the market through external channels (Chesbrough 2004).

The Art of Openness is closely related to the concept of open innovation introduced by Henry Chesbrough (2004). Although the concept has become widely used, the software viewpoint is largely neglected in the general open innovation discussion (Pikkarainen et al. 2009). Open source communities have been used as a source of innovation in software development, but there are also many other possibilities for practising openness that emerge due to the special nature of software. Openness becomes easier as software products and services can be shared at virtually no cost once they have been produced. Different versions of the software can thus be distributed to customers and other stakeholders for testing and obtaining improvement ideas already before the product launch – if a fixed launch is needed at all. More and more software products are used online, where continuous updating and improving of the software is possible. Many software companies also provide public feedback and idea channels to involve users in the continuous innovation process. User innovations occur, especially when the software is used, when users find new practices and purposes for it. Online collaboration tools can also be used for customer and/or user involvement during the software development phase. New ideas can come up when increments of the product can be available to the stakeholders all the time.

The Art of Openness can take many forms and should in itself not be the purpose. Very few companies can be described purely as open or closed. Instead, openness should be seen as a continuum that ranges from more closed approaches to more open ones (Paasi et al. 2010). A company needs to find the strategy most suited to its situation – the type of software product and the characteristics of the markets. Openness is a strategic decision in the company and is supported by high-level management, though the actual practices can vary from case to case.

2.6.1.1 Outside-in and Inside-Out Approaches in the Art of Openness

Basically, the Art of Openness can be practised in companies using two different approaches, namely the outside-in and the inside-out approach, or by combining the two (Gassmann and Enkel 2004). The outside-in approach refers to the internal use of external knowledge through which companies can integrate, for example, external stakeholders into the process of exploring and co-creating new innovations. Dell IdeaStorm¹ is a good example of using innovative ideas that reside within users. Dell IdeaStorm is a web site launched in 2007 on which users can post development ideas related to Dell products. Another successful example of using the outside-in openness approach is the SAPiens community established by SAP in 2007. SAPiens is a community platform for students and academics within the scope of the SAP University Alliances Programme.² Using or licensing external software components in a company’s products is another example of the outside-in approach.

The inside-out approach deals with the external exploitation of internal knowledge. The key benefit is that through activities such as licensing and commercializing ideas in different industries, companies can gain faster access to the market than through internal development. This way, companies can also increase their revenues through a wider customer base. Companies relying on open source software in their commercial products are good examples of successful inside-out openness strategies. For example, Sugar CRM³ offers its basic customer relationship management solution as free and open source software, but the more advanced professional version is sold at an annual fee. MySQL⁴ is another example of a company that provides the open source code free, but additionally sells training, certification, consulting and support services. These companies use the external developer community in the development of their offerings and receive revenue from the supplementary services.

A combined approach, in which outside-in and inside-out approaches are incorporated in order to benefit from external knowledge and new opportunities of idea commercialization, can be carried out in, for example, strategic cooperation partnerships or networks/alliances. In a strategic partnership, the focus is not on bringing resources over the company borders (inside or outside) but on innovating together. Co-creation challenges the whole business model of the company, as the owner of the ideas and products can no longer be strictly defined, and a win-win situation is more difficult to achieve, although it would be highly beneficial to all parties (Prahalad and Ramaswamy 2004).

2.6.1.2 Approaching the Art of Openness at Three Different Levels

The Art of Openness can be considered at three different levels: product, process and business/strategic level.

Openness at product level revolves around the topic of opening up the product in different ways. For project-based and out-of-the-box software companies, this could mean, for example, using open source software as part of the product or contributing to open source communities and that way gaining recognition that can lead to profit-making orders in the future. Online services can be opened to third parties at the application programming interface (API) level so that other services can interact with them or even create new services combining your product with those of others (so-called mash-ups). A speciality of the software domain is that, when working on customized software product development, you do not need to create the customizations from scratch but can use pieces of other parties’ software (via Open APIs or open source) freely as part of your own offering, which saves your resources. The customization can even be left to the customer itself, if your software is made to be modifiable.

Openness at the process level deals with opening up company processes to external influences/resources. Process-wise, a software company can apply the Art of Openness in different phases of the process and by using different external resources. The resources can include new technology, ideas or other input from different stakeholders. An out-of-the-box software company, for example, can use its large end-user base and co-create with the users in several phases of its innovation process, e.g., idea generation and testing prototypes or including the users as active participants throughout the new product development. For software companies involved in project-based development, a close relationship with the customer is natural. Customized product development companies can cooperate with third parties to create standards for new APIs or create other technical enablers for software customization.

The business/strategic level recipe for software business has been to constantly create new innovative out-of-the-box products that can be sold to the masses at a virtually non-existent marginal cost. Due to the increasing pace of new emerging technologies and the speed of change in the business environment in the software domain, this has become a challenging path to follow. To tackle the challenges of finding a new competitive edge, companies are turning to more and more customized offerings, preferably mass-customized in the sense that users can customize their products themselves. Openness is one of the key enablers of this shift because close producer-client interaction is one of the key sources of value co-creation.

2.6.2 The Art of Openness – Main Activities

2.6.2.1 Specifying an Openness Strategy

The openness strategy specification deals with evaluating the company’s existing business model, vision and strategy and then deciding on the appropriate openness strategy. The strategic decision on the degree of openness includes analysing the value of the Art of Openness, i.e., the way openness affects the company’s value creation, the timing of openness (when/how long in the product cycle to be open) and the type of openness suitable for the company (Fig. 2.10).

Fig. 2.10

The art of openness, relation to other practice areas

The value of the Art of Openness to the company depends heavily on the underlying business model. Chesbrough (2006a) states that the business model has two essential functions: (1) it creates value within the value chain and (2) it captures a share of the value for the focal firm in the chain. Sometimes, the company’s existing business model can present constraints on the use of open innovation. For example, if a company is committed to a closed product ecosystem, such as Apple, a relatively closed approach to product innovation may be the rational choice. Apple has succeeded in reaping the benefits of openness on the application side of the ecosystem, however, i.e., the App Store. As Chesbrough (2006a) points out, redefining the existing business model towards openness could create significant benefits for the company in terms of both cost savings (leveraging external resources) and additional revenue (spin-offs and licensing fees).

R&D management issues may also present challenges when applying openness to the company’s innovation and engineering processes. Greenstein (1996) points out that openness increases coordination costs because it requires the cooperation of multiple actors (e.g., suppliers, complementors). Almirall and Casadesus-Masanell (2010) argue that the degree of openness that is suitable depends on the complexity of the product under development. They state that very complex and very simple products are unlikely to benefit from openness. Simple products have little to gain from the more complex process, and complex products may be hampered by increased complexity and communication challenges between partners. In their view, the products that are best suited to open innovation are those of medium complexity for which the benefits of open innovation outweigh the negative effects. Boudreau (2006) found that in the case of complex systems, closed innovation is more successful in the early phases of the innovation process. Later when the complexity is reduced, however, different kinds of, for example, co-creation approaches are more successful.

2.6.2.2 Opening the Product

This activity encourages software companies to adopt a new kind of perspective when thinking about their products. Could opening up the product or parts of it provide novel opportunities for your firm? In some cases, the whole product can also be open, as in the case of pure open source products. What would be the benefits of, e.g., transforming a proprietary software product into an open development and integration platform and allowing your customers to make their own modifications to it as SAP did (Farhoomand 2007)? These decisions are related to the type and degree of openness of the product and are closely linked to the company’s business model.

A software product can be opened up in several different ways. One strategy is to make software products that feature a high degree of ‘connectivity’ to other products. This can be achieved, e.g., with open standards that companies create together to ensure that different products are interoperable. With regard to open standards, a company can even decide to try to create a new standard in the market.

Software companies can also consider making the product accessible through an open API. This approach can only be applied to parts of the product, e.g., for certain data sets that are not crucial to the company. By enabling different software to interact with each other, companies can also find new synergies and revenue-creation opportunities. Another approach to open APIs is to make the product as a mash-up that uses and combines information from several sources in order to create new value.

Open source software also creates many unique opportunities for software companies. The company can create the product entirely through open source or turn an existing product into an open source community. For example, the development of the software development environment Eclipse first started as an internal IBM project, but later on, the software was published as open source and a foundation was created to further the development of the software. Using software from open source communities can be a viable option to buying or building decisions. Open source communities can also be used as a channel for releasing software that no longer creates value in-house.

Ecosystem thinking should be considered in the activity of opening the product: in an open environment, products and services cannot be considered separately but as parts of the bigger product ecosystem. Products by different players can be combined if the combination yields more value than the individual components.

2.6.2.3 Co-creating

Here, openness at process level is called co-creation. It means interactive value creation with customers, users, partners and other stakeholders starting from the early phase of the innovation process (Prahalad and Ramaswamy 2004; Piller and Ihl 2009). Software companies can involve customers and other partners in direct collaboration during the ideation and software development phases. Customer involvement is essential, especially in the project-based software business. Customers’ ideas and needs must be heard, and they can be involved in development processes, e.g., using workshops in which developers and customers meet.

In addition to customers, the actual end-users of the software product offer huge innovation potential. They are the experts of the use situation and can therefore provide valuable insight into the way the software product could be developed. In the context of B2C software products, users can even be involved in the daily practice of software development via the Internet. New versions of the software can be opened for, e.g., a group of beta testers who provide feedback and improvement ideas for the developers. Users, as well as other software builders, can also participate in the actual software development either by modifying the original software, developing add-on components or integrating different components as mash-ups.

Co-creation activities can integrate the whole value network – not only customers and users but also suppliers and other software product builders, with whom an alliance can be created to target new markets. In the case of customized software products, other stakeholders can also participate in the customization, either in collaboration with the company or on their own if the company provides a toolset for customizing the software based on own needs.

Co-creation activities can be divided into closed and open co-creation. Closed co-creation involves known partners with established business relationships. The objectives of closed collaboration are twofold. First, closed co-creation networks can be used to increase intra-network knowledge and collaborative learning. Second, these closed networks can be used to achieve direct commercial gains. When the necessary level of trust between partners has been gained, the contractual agreements can be rather informal to ensure the innovativeness of projects. When dealing with open co-creation networks with unknown participants, it is essential to make sure that vital IP and tacit knowledge are protected with the proper level of agreements. Hence, the level of contractual protection preferred in co-creation networks will be higher the more unknown the network participants.

2.6.2.4 Creating Revenue from Openness

Openness at the strategic and business level is addressed in the activity of creating revenue from openness. The prerequisite for creating revenue from applying openness to software innovation is the reformulation of business models to adapt the openness perspective. As one of the key purposes of a business model is to identify how the company can capture its share of value creation, the inclusion of the openness perspective can help companies define new ways to create and extract value, e.g., through creating new open product ecosystems. An example of active new ecosystem creation is the FlexiDis project coordinated by Phillips Electronics in which the goal is to create flexible displays that can be bent, rolled up or even attached to clothing. Such flexible displays will create a plethora of new markets ranging from supermarket displays to e-readers.⁵

One of the main drivers of increasing openness is the possibility of gaining revenue streams from innovations that are discarded during the innovation process and are not used in the core offering of the company. Software companies are constantly making go and no-go decisions on their innovation and development projects. When targeting stable known markets, these decisions can be made with fairly complete information and, hence, the percentage of false project terminations (and the number of lost revenue opportunities) is marginal.

Due to the increasing speed of change in the business environment of the software domain, stable markets are becoming scarce and companies are being forced to venture into new uncharted markets. This means that companies are forced to make go-no-go decisions under increasing amounts of uncertainty: How will technological development change the markets? How will our customers’ needs evolve? What other potential markets exist for our inventions? This change in markets creates a challenge for companies: increased uncertainty leads to an increase in lost revenue potential due to less accurate decision-making.

Chesbrough (2003b) introduces the metaphor of playing poker to describe the management of innovation when facing uncertain markets. According to the poker metaphor, when faced with information uncertainty, companies need to find a way to reduce the probability of lost revenues due to false termination decisions. One way to tackle this challenge is to adjust the innovation strategies and business models to embrace openness.

Openness strategies in innovation exploitation, i.e., the inside-out strategies, are means for companies to manage the increased market uncertainty. These strategies include licensing or selling innovations that are not used in the company’s own products and establishing spin-off companies to commercialize the discarded innovations. The use of open source as a means to reach new markets can also create new revenue streams. At the end of the practice area, the case of Mahiti Infotech highlights the opportunities of open source. Sugar CRM and MySQL, discussed earlier, are good examples of this type of inside-out strategy. Due to these in- and outflows of ideas and knowledge and possible different licensing schemes, IP management plays a crucial role in the implementation of the defined strategies (de Jong et al. 2008; Chesbrough 2003a, 2006a) (Fig. 2.11).

Fig. 2.11

Types of transaction relationships (Paasi et al. 2010)

2.6.2.5 Managing Intellectual Property (IPR)

Intellectual property rights (IPR) are an obvious aspect affected by openness. In IPR management, two different practices can be recognized: external sourcing of innovation (protecting IPR when collaborating openly) and external commercialization of innovation (selling and buying IPR).

With regard to external sourcing of innovation, IPR and ownership of the products must be considered carefully before starting open collaboration. Among the organizations, contracts should clearly state the roles and rights for the outcome of the collaboration. When involving consumers and users in the innovation process, their rights for the innovation must also be expressed. The ownership of all the results of user-driven, open innovation typically belongs to the company, but users must also gain some benefits. In Internet-based crowdsourcing, in particular, users know that their contribution is voluntarily and for them it is enough to obtain better products instead of a share of the revenue.

There are different strategies and approaches for managing IPR in an open innovation context. IPR can be purchased and sold either directly between partner organizations or by using intermediaries. New innovations may also lead to the establishment of spin-off companies.

The awareness of issues related to IPR and its management should be communicated between all the layers of the company from management to product development. In software companies, the developers need to be aware of the consequences of, e.g., using open source components in the firms’ products or sharing company-sensitive information in open source communities.

2.6.2.6 Fostering (Organizational) Openness

As the foundation of all innovation is ideas and knowledge that reside inside the people involved in the innovation process, fostering corporate culture that nurtures openness practices within the company is crucial to increasing the possibilities for companies to benefit from the Art of Openness. In other words, companies should avoid the ‘not invented here’ syndrome by all means if they want their openness activities to succeed.

In making their R&D efforts suitable for applying openness, companies need to focus on both team and individual level motivation and working practices. Hence, this activity is closely linked to the Art of Innovation Stimulation. Ancona et al. (2002) showed that teams that are externally focused, adaptive and see positive results across a wide variety of functions and industries would be most successful. They state that successful teams emphasize outreach to stakeholders inside and outside the company boundaries and that this entrepreneurial focus will help them to adapt easily to a changing environment.

In addition to the organization of teamwork, motivation can be regarded as a key enabler of the Art of Openness in practice. According to de Jong et al. (2008), individual and team level innovativeness can be motivated by investing in employees’ ideas and initiatives, creating autonomous teams with dedicated innovation budgets or stimulating employees’ external work contracts in order to enhance opportunity exploration.

In an open innovation context, different partner organizations constitute a business ecosystem. Coordination and management are needed at the inter-organizational level in addition to each organization’s own processes. An essential task is to identify different stakeholders in the innovation ecosystem and define their roles (e.g., customers, users, competitors, subcontractors) and the importance to their own organization. Once the network exists, trust must be built among the participants.

2.6.3 Relations with Other Practice Areas

The Art of Openness practice area can be considered as a context for other practice areas. The decisions made about the type and timing of openness affect all of the other software innovation practice areas (Fig. 2.12).

Fig. 2.12

Relations of the art of openness to the other practice areas

The relationship between the Art of Openness and the Art of Focusing is twofold: first, the innovation goals and targets set in the Art of Focusing affect the decisions related to openness. Second, inputs (e.g., information, technologies) obtained by opening up innovation activities may have an impact on innovation goals.

The Art of Openness has a major impact on the kind of innovation stimulation activities that should be applied. Inputs obtained by openness may act as innovation stimulation inside the company. It is also important to foster such an innovation culture in which openness is encouraged.

With regard to the Art of Optimizing the Impact of Critical Experts, it should be remembered that by applying openness, companies are not only restricted to the resources inside the firm. Instead, depending on the type/degree of openness, they have the opportunity to access almost unlimited resources outside the company. If a company relies on external resources, they can also become critical.

It is necessary to be able to measure and evaluate the effects of the chosen openness strategy on products, processes and business in order to adjust the decisions. Thus, the Art of Improving Innovation is also very important from perspective of the Art of Openness.

The strategic decisions of the Art of Openness impact on idea harvesting, depending on the degree and type of chosen openness strategy. For example, it is important to plan, how the ideas are harvested and from whom. It should also be noted that the company could act as a source of ideas for others.

Furthermore, depending on the decisions made on the Art of Openness, it is important to determine, how the external ideas are evaluated and by whom, what kind of ideas can be shared or published and what will remain confidential.

With regard to the Art of Innovation Incubation, the type and timing of the Art of Openness offers new possibilities, for example, external resources can be brought into the incubation process. It is important, however, to determine which external people are involved in the incubation phase and how.

2.6.4 Questions

• What could drive you to make your organization more open?

• How could your product/organization benefit from external innovations? What kind of risks are there with respect to openness for your product/organization?

• Which forms of openness are relevant to your product/organization?

• At what stages or phases of your innovation process would openness be applied?

• To what extent do you involve different stakeholders in your innovation process? Could you involve them more?

• Do you know the end-users of your product? How could you use their innovation potential? What kind of value would they gain from co-creation?

• How could your company use social media and online communities to obtain external ideas?

• How do you make your product open?

• What is the role of open source in your business?

• Which stages or phases of you innovation process could be opened?

• What is the timescale of openness (continuous or in certain phases)?

• Which stakeholders and roles are needed (e.g., customers, users, competitors, subcontractors)? What is the importance of each stakeholder in each phase of the innovation process? Which innovation tools can be used?

• Which other resources are needed?

2.7 The Art of Optimizing the Impact of Critical Experts

• Nick Boucart,
• Vladimir Blagojevic,
• Olivier Biot,
• Wim Codenie,
• Peter Stuer &
• Jeroen Deleu 

1. Sirris, Diamant Building, Boulevard A. Reyerslaan 80, BE-1030, Brussel, Belgium

   Nick Boucart (Technology Adviser Software and ICT), Vladimir Blagojevic (Technology Adviser Software and ICT), Olivier Biot (Technology Adviser Software and ICT), Wim Codenie (Program coordinator software and ICT) & Jeroen Deleu (Director Sirris Brussels)

2. Spikes, Posthofbrug 10A, 2600, Berchem, Belgium

   Peter Stuer (Research Director)

2.7.1 Description and Scope

Imagine that you are the CEO of a software company. Your company has successfully brought a software product and accompanying services to the market. You faced some fierce competition, but in the end, you managed to establish your position in the market. You did not sit still to enjoy your victories; instead, you observed the market, the competition and the technology landscape. You realized that you need to stay on the bleeding edge. You have therefore identified a clear focus for your innovations and put forward some challenging innovation targets that your company needs to address (see Sect. 2.3).

You ask yourself: What are the critical resources that our software company needs in order to achieve our ambitious goals? Which activities are critical and who do we need to partner? Ultimately, who are the critical experts when it comes to realizing our innovation goals?

You quickly realize that answering these questions is far from trivial but that providing an adequate answer to them is crucial to success. You understand that new developments in software products can largely be traced back to the contributions of just a few (Greenspun 2002; Brooks 1995). You know that the difference in productivity and impact of innovation between an expert and an average software engineer can be as great as ten to one⁶ (an extensive discussion on the origins of the 10× productivity differences can be found in McConnel 2011).

At the same time, you know that these experts are scarce. The OECD has already reported that the acquisition of skilled human capital is seen as a key challenge in the software sector (Stryszowski 2009). Even if you could identify exactly the kind of experts you need to address your innovation targets successfully, you may have a hard time accessing them. Some of these resources will not be working for you. You may think of some earlyvangelists (Blank 2005b) or lead users (von Hippel 1986) who could help shape your new products and services, but you really wonder how to reach them and how to engage with them. Nevertheless, these people are critical experts to your innovation targets: they possess knowledge and experience that will be key to the success of your innovations.

You understand that your company should cherish experts who are critical to the success of your innovation targets and create an environment in which these experts can have their biggest impact. The Art of Optimizing the Impact of Critical Experts is all about creating such an environment in a software company.

Critical experts may be internal (software architects, software engineers, product managers, etc.) or external to the organization (customers, domain experts, etc.).

Which people can make the difference between a successful and a failed innovation in software development? The answer depends very much on the context in which a particular software company operates.

2.7.1.1 Critical Experts at the Technical Level

Technical experts have deep knowledge and experience of technical matters. In a typical software organization, experts can be identified in a wide range of areas. Senior software architects, software developers, testers … can all become critical experts at one point, depending on the needs of the project and the history of the product. In today’s complex software environment, many engineers are seen as critical, as few people have a complete overview of the situation.

2.7.1.2 Critical Experts at the Product Level

Product experts translate the market demands into tangible products and product functionalities. Their job is to define the product vision, translate that vision into a product roadmap and define the individual software releases that implement this product roadmap. Product managers will engage with many stakeholders, including sales, marketing, development, support and customers.

2.7.1.3 Critical Experts at the Business Level

Business-oriented experts are a third category of critical innovation experts. They include project, sales and marketing managers and CEOs. These executives are able to generate and pursue new business opportunities and may also be able to rethink the current business approach and innovate at the level of the company’s business model.

Three examples of companies and their critical innovation experts are presented below.

Example 1: A start-up company that wants to bring new software to the market.

Consider a start-up company. The innovation target of this new venture is to build a solid business around solving a pressing customer problem identified by the founders of the company. They envision a software solution as the answer to this problem. They realize that there is still a long way to go from idea to viable business however. They have identified the critical experts as:

• An entrepreneur that is strong in customer development. According to Steve Blank (2005b), customer development is about testing the founder’s hypothesis on what constitutes a product/market fit with the minimum feature set, thereby answering the questions: Does this product/service, as specified, solve a problem or a need that customers have? Is our solution compelling enough that customers will want to buy or use it today? You know you have achieved a product/market fit when you start receiving orders (Blank 2011).

• A committed and flexible software developer . In order to attain a product/market fit, prototypes may have to be built to test hypotheses. The start-up will need to have access to a committed software developer who can build these prototypes fast and without the need for formal specifications. Ideally, he/she can ‘hack’ together a prototype overnight, just in time for a crucial demo to a promising prospect.

Example 2: An established software company with a legacy out-of-the-box product.

The company in this second example has been active in the market for several years. It launched its flagship software product 6 years ago and has evolved it ever since. Today, it is shipping release 4.2. Under pressure from customer requests, its once simple product has evolved into a complex one overloaded with features. The company has decided to rethink its product fundamentally for its upcoming 5.0 release, whereby the product will be broken down into a suite of dedicated solutions targeting specific market niches.

They identified the most critical experts as:

• A strong product manager. The product manager’s task is to define the upcoming release. He/she has defined four targeted applications to be derived from the big monolithic product that is sold now. The product manager is constantly battling the urge to make the software more complex for the end-users. In parallel, he/she is preparing the existing customer base by explaining the new product vision and soliciting feedback. He/she works closely with the sales and support teams so that these teams are ready when the new version launches.

• An enlightened software development manager . The role of the software development manager is to guide the whole team through this tough transition. It is clear that release 5.0 is not just another release with some new features and re-factorings. The developers will have to reinvent the product, unlearning old assumptions and thinking patterns, and it will all need to happen under serious time pressure. The development manager will have to coach the team not to give up on good habits (the focus on quality, the collaboration in tightly knit Scrum teams) while shielding the team from the pressure inflicted by product management.

• Senior software architects. Only a few people in the company qualify as senior software architects. These architects joined the development team early on in the development of the product. They were responsible for selecting the architecture, the technologies used, the design, etc. In this new endeavour, the senior software architects await a difficult task. They need to ‘forget’ the product’s legacy architecture and rethink the product in terms of the new product vision. Some of them see this as an excellent opportunity to phase out some of the older technologies used in favour of state-of-the-art open source alternatives. Others will have a hard time letting go of the old, familiar product architecture and design. Notwithstanding these difficulties, the company needs to rely on the team of senior architects to redesign the product in a future-proof way and count on the architects to translate their years of experience into a new product vision.

Example 3: A project-based software company with a strong ambition to grow.

This third example presents a company that builds custom software. The company delivers all its software through customer projects. The company is very successful and has optimized the way it deals with these projects by deploying dedicated teams located at customer sites.

To realize its ambition to grow, the company cannot simply accept more projects. In fact, in its current business model, it can only generate more revenue by executing more projects, for which more staff are needed. This does not scale very well, especially when talent is scarce.

An alternative growth strategy is to develop new services and/or products of higher value. To realize this, the following experts are critical:

• Product visionaries in a service company: these are people with a strong vision of creating new, high-value offerings. They can see beyond the operational day-to-day project work and engage the organization to realize new offerings. They usually have a tough job arguing their case to the management to obtain enough resources to realize the vision. The management will have to balance an immediate return from ongoing customer projects and investing in new, more risky ventures. If such product visionaries are not endorsed by management, there is little chance that the company will allow experts to be allocated to high-risk, new service development instead of being deployed at customers’ sites where they generate revenue by the hour.

• Domain experts working at the customer’s premises: the project company deploys a large number of people at customers’ sites. Its best experts are often the ones who are most wanted by the customers. These are exactly the type of experts who can prove very valuable when the company intends to develop new services. Their domain knowledge in itself is invaluable and their knowledge of the customers and their needs is indispensible.

2.7.2 The Art of Optimizing the Impact of Critical Experts – Main Activities

Five activities across three phases must be mastered in the Art of Optimizing Critical Experts (see Fig. 2.13). Each activity is described in detail in the remainder of this section.

Fig. 2.13

Activities of the art of optimizing the impact of critical experts

2.7.2.1 Innovation Bottleneck Identification

Once a software company has defined its innovation targets (see Sect. 2.3), it needs to understand what kind of activities, resources and partners are key to realizing the targets (Osterwalder 2010). Some of these activities are straightforward to implement, while others may pose real innovation bottlenecks.

Some examples of innovation bottlenecks are presented below:

• Lack of customer insights when targeting a new market. A company aiming to serve a new market should ideally have strong knowledge of that market. Are there differences in legislation with respect to the home market? Do customers in the target market use the same vocabulary as customers in our existing markets? Do customers in our new target market understand technology like our current customer? Not having a deep knowledge about the new target market could seriously endanger the success of the endeavour.

• Lack of software technology expertise in non-software companies. An increasing number of non-software companies identify opportunities to enhance their current offerings with the support of ICT and software. Many of these companies are experts in their own domains but lack knowledge of ICT and software technologies. Four types of knowledge need to be acquired. First, these companies have to establish a technology scouting program to understand the complex software technology landscape (Rohrbeck 2010). Second, they have to be able to understand the opportunities of a particular technology in their context. Third, they have to master the specificities of the selected technologies. Finally, they have to acquire the necessary skills to manage software and ICT development projects. Without access to such critical experts, a company in this situation will have little chance of success.

2.7.2.2 Expert Spotting

Through expert spotting, companies are better able to understand who to look for when specific expertise is needed. Expert spotting is often a consequence of identifying innovation bottlenecks: once a company explicitly identifies certain innovation bottlenecks, it can start looking for people to address these bottlenecks, either inside the organization or outside it.

Different strategies are used by companies to spot experts. An in-depth overview of the expert seeking problem and a number of solutions is given in Yimam-Seid and Kobsa (2003). The authors state two reasons for seeking experts: the need for information and the need for expertise. Often both needs meet in one expert search quest. The former requires users to formulate their needs in terms of information, which typically boils down to translating the request in a search query on an information retrieval system. In the latter case the needs are more complex to state, since the expert’s skill levels often play an important role.

Traditionally, knowledge intensive organizations have been investing in creating and maintaining expert databases. These systems burden management and experts to encode and update their skills by hand. It is observed that these skills are often stated in a very generic way and are infrequently updated, while expert search operations tend to use very fine grained qualitative criteria (e.g., expressing the level of acquaintance with applying a certain technology in a very specific context under special restrictions). The scope of these systems is often the organization’s staff, which obviously disregards experts external to the organization.

Knowledge intensive organizations create more knowledge today than they will ever be able to document explicitly. Creating and maintaining an exhaustive and up-to-date corporate knowledge encyclopedia in the spirit of the French eighteenth century encyclopedists is an illusion. These knowledge repositories are however an important source of tangible and digitally accessible and transferrable know-how. In this context, the need for an expert often boils down to accessing undocumented knowledge, efficiently identifying relevant expertise, re-formulation of a problem into more directed search statements, or in interpretation of knowledge in a particular context.

Example Web 2.0 realizations of such knowledge repositories are IBM’s Wiki Central (IBM Wiki Central), a corporate wiki open to any participant, and IBM’s internal Blog Central blogging platform. Both platforms have tens of thousands of members today (Lewis 2008).

Identifying experts via knowledge management systems means searching for ‘know-who’ instead of ‘know-how’. By smartly combining Web 2.0 technologies with semantic technologies such as text mining and ontologies and social metrics, a host of expert search solutions have been proposed. An example is the Technorati blog search service (Technorati) which uses tagging and social metrics such as reference counts for determining a blog author’s authority for a given search query. A similar approach is presented in Dooley et al. (2002) where the authors propose a solution for accessing knowledge that is outside your own area of expertise.

Some companies encourage team members to ‘broadcast’ their whereabouts. In another words, the experts announce to the rest of the organization what they are working on, which lessons have been learned, etc. At a later stage, this can be used by other people in the organization to track the missing pieces of information or, at least, to locate the expert who may have a solution to a given issue. Scrum (Scrum) is an example of a process that promotes this broadcasting, as all team members have to communicate what they have been working on during daily stand-up meetings.

Another strategy is the use of innovation tournaments or innovation boot camps to spot experts. During boot camps, a team tests its new venture idea or validates the validity of an existing venture from fellow entrepreneurs. The team is simulated to assemble an entrepreneurial venture. An example of such a method is Innocoop, which is described in one of the case studies in this book (see Sect. 3.13).

Finally, an interesting technique for expert spotting was suggested by Sarma et al. (2009). This paper described Tesseract, a tool that mines data from software code source repositories and issue tracking databases, and tries to link experts to certain software artifacts. The tool provides an interactive visual exploratory environment that utilizes cross-linked displays to visualize the myriad relationships between artifacts, developers, bugs, and communications. Microsoft also has an initiative, Codebook, that uses social network techniques to find experts (Begel et al. 2010).

2.7.2.3 Engaging Critical Experts

Even when a company understands which people are most critical to successfully pursuing innovations, it does not mean that these people are accessible and available. They may be occupied on other projects, as is often the case in project companies. Alternatively, these critical experts may only be found outside the organization (e.g., lead users, external experts, etc.). Having access to these critical experts, if only for a very short period in time, can impact an innovation significantly. A software company therefore needs to understand how to access and, even more importantly, how to engage the critical experts in a timely fashion, carefully avoiding overloading them.

Three key questions need to be asked when setting up engagement with experts:

• When do you need to engage the expert? Timing is a crucial factor. It is important that experts are involved early enough, so that their contributions can make a difference. Involving a senior architect in code reviews 3 days before shipping a large release will not make a big difference. When the critical experts are not readily available, their involvement should be anticipated and prepared upfront.

• How will you access the critical experts ? Which channels will you use to reach out to them and trigger them? This may be easy when the critical experts are part of the team, but it can be much harder when you depend on experts outside the company.

• How will you obtain commitment from your experts ? You may know who your critical experts are, you may even know where to find them, but how are you going to ensure that they engage with your innovation challenge? How will you answer the ‘what’s in it for me’? question. In some cases, explicitly recognizing someone as an expert and simply asking him/her for an expert opinion is enough. In other cases, you may have to put in much more effort to obtain the proper engagement.

Consider two examples of how experts are engaged in software companies. The first example is based on the product owner in (Scrum Schwaber 2002) as a critical expert. The second example focuses on technical experts outside the company.

Example 1

Scrum recognizes the criticality of the product manager by introducing the explicit role of product owner. His/her role is to understand which features create most business value for the company. The product owner communicates this understanding to the team. Scrum introduced explicit access channels, timings and means to obtain commitment for the team and product owner: during the sprint planning meeting, the product owner and team sit together to discuss priorities and plan the next software increment. During the sprint review meetings, the team demonstrates the product increment to stakeholders, effectively creating an access channel to stakeholders, allowing the team to solicit feedback on its work.

Example 2

Today, technology makes it easier for software engineer to explore weak ties⁷ with experts outside the organization. Software engineers can connect to online communities in which experts in specific areas are present to exchange experiences. For technical software engineering questions, engineers can turn to a community like Stackoverflow (Stackoverflow), a Q&A community entirely devoted to solving technical software engineering challenges. Platforms such as LinkedIn (LinkedIn) or more recently Quora (Quora) offer like-minded professionals the ability to create groups around certain topics. Many software-related groups can be found there. Many of these platform support some form of reputation management, whereby users gain more recognition when they successfully engage with others.

2.7.2.4 Relieving the Experts

The pressure on the experts is high. Their knowledge and experience are often in high demand. Ideally, the software company will deploy measures to relieve the pressure off these experts, allowing them to concentrate on those tasks that absolutely require their expert input, while unloading less critical activities onto others. The experts can be relieved in many ways:

• Planning the availability of critical experts : By carefully planning and anticipating where and when experts will be needed, companies can hope to ensure the availability of those experts at the times when they are needed most. This will only work well when future expert needs can be anticipated correctly.

• Capturing expert knowledge : Some software companies ask experts to create documentation on the development processes, experiences, product architectures etc. The aim of this effort is to make expert knowledge available to all. Training is organized in which experts teach team members best practices, standard operating procedures, etc. Larger companies, in particular, apply this strategy, often forced by external factors such as safety or other types of certification (e.g., ISO, CMMI). Training sessions are organized through which team members gain expert insights in domain knowledge, technical expertise, etc. These are often supported by (online) tools such as wikis, frequently asked questions, etc.

• Formalization of processes: Companies often try to formalize processes to relieve experts from being involved all the time. By using checklists, best practices, etc., which are often developed by the field experts, companies hope to leverage experience and knowledge from experts, without the need to access the experts themselves. Another example of formalization is the development of common frameworks, in which software architects develop a common architecture for use in many projects. This reduces the critical importance of software architects in individual projects.

• Automation: Many companies seek to automate the contributions of expert resources. Automation is one example of the formalization of processes. An example of automation is test automation: while testing experts initially spend their time defining the best possible test suite for a given software product, they often end up performing these tests over and over again, leaving little or no time for inventing new tests. By automating the performance of the tests, test execution can run automatically (or at least be attended by less experienced testers), freeing up the testing experts to create more impact with new and better tests.

• Specific collaboration models: In some agile software methodologies, such as eXtreme programming, the use of pair programming and pair rotation is advocated (Beck 1999). With pair programming, each developer task is taken up by two people who share a computer. Combined with pair rotation (i.e., the developer pairs split up after the completion of their tasks to form new pairs for the next task), these collaboration models aim to make all developers experts or, to put it another way, to actually ensure that there are no critical experts at all. Although this can be helpful when a company has innovation bottlenecks in the development area, these models are hard to realize when the critical experts are outside the software development team.

• Critical resource community building : A promising new approach is to build online communities aimed at creating redundancy around the critical experts. Project companies deploy communities of practice around specific engineering topics. Out-of-the-box software companies, on the other hand, use customer communities to solicit feedback on products and services. This is illustrated in the next activity.

2.7.2.5 Expert Community Building

In order to keep the practice area of optimizing the impact of critical experts alive and sustainable, software companies tend to build communities around their most critical experts. This way, software companies hope to create enough critical mass around the individual experts, effectively lowering their criticality.

Many project-based software companies deploy communities of practice (Wenger et al. 2002) to bring together experts in domains such as software architecture, software testing, security, service-oriented architectures, etc. Companies do this to leverage the expert’s experiences beyond the project they are working on. This allows project-based companies to increase effectiveness and efficiency.

Example: Community of practice on software architecture. Steria, a large service organization, started a community of practice around software architecture. Software architects working on different customer projects were invited to join and discuss issues, best practices and experiences of different complex software architectures. The aim of the community was to ensure that experience and best practices did not become ‘trapped’ inside individual projects. The members of the community document and share their findings on an online platform, making their experiences accessible to a broader audience within the company. It is a trend that more and more software companies support their communities of practice with online Web 2.0-inspired tools, such as wikis, forums and Q&A platforms (McAfee 2009),

Many out-of-the-box and customized product software companies are interested in building user communities around their products or brand. The goal of such communities is to extract insights into how users perceive the company’s products and services. These insights then help product management to steer further development. Companies organize focus or user groups, and many out-of-the-box software builders organize yearly conferences to bring together customers and learn from them. In this area, Web 2.0 and social media are also increasingly used by software companies to solicit more and better feedback from customers. Dell’s Ideastorm (Ideastorm) is an example of one such online community.

2.7.3 Relations with Other Practice Areas

This practice area is supportive towards all the other practice areas. Two practice areas, in particular, interact with the Art of Optimizing Critical Experts:

• The Art of Openness. As already indicated in this chapter, some of the company’s critical experts may not be found inside the company. Engaging with these critical experts should be considered carefully and needs to be aligned with the organization’s stance towards openness.

• The Art of Focusing . Defining your critical experts with respect to innovation is hard when you do not have explicit innovation targets. It is only in the context of a specific innovation target that the innovation bottlenecks can be identified and start to be addressed. The Art of Optimizing the Impact of Critical Experts therefore has strong interaction with the Art of Focusing.

2.7.4 Questions

With respect to the Art of Optimizing the Impact of Critical Experts, company leaders should ask themselves a number of pertinent questions:

• Who in our software company are the critical experts when it comes to innovation? Are these experts technical people, people with excellent market and customer knowledge, our senior software architects? For each type of critical expert, why are they critical, what exactly makes their contributions so valuable?

• In our organization, how do we keep track of who is knowledgeable about what? What do we track with respect to knowledge and experience? Do we monitor and model technical skills, customer experience, product knowledge, etc.?

• How do we make sure critical experts are involved at the time when their impact is greatest? And, how do we do this without overloading them?

• What measures do we take to relieve our critical experts? Can we relieve them? Can we implement measures that will ensure that their impact increases without necessarily increasing the pressure and workload on them?

• How do we determine when expert advice is needed? When and how can our teams call on expert help?

• Do we have expert teams/champions/centres of excellence? Should we build some form of community around our most critical innovation experts?

2.8 The Art of Crafting Smart Products

• Jessie Dedecker,
• Wim Codenie,
• Jeroen Deleu,
• Stefaan Vermael &
• Pico Lantini 

1. Sirris, Diamant Building, Boulevard A. Reyerslaan 80, BE-1030, Brussel, Belgium

   Jessie Dedecker (Technology Adviser Software and ICT), Wim Codenie (Program coordinator software and ICT), Jeroen Deleu (Director Sirris Brussels), Stefaan Vermael (Technology Adviser Software and ICT) & Pico Lantini (Business Development Manager)

2.8.1 Description and Scope

Today, ICT technology is omnipresent in everyday environments, and it is used to support a broad spectrum of activities. It’s a Smart World ICT products are ubiquitous in industrial, public and private environments. A consequence of this successful adoption is that the number of ICT products used by a single person has soared. This is the case for professional as well as private use (a qualitative representation of this evolution can be seen in Fig. 2.14).

Fig. 2.14

Conceptual representation of the number of ICT devices associated with a single user

In contrast, the attention bandwidth of users has not increased. People have a limited capacity to absorb and control the ICT products with which they come into contact. A typical user understands merely a fraction of the possibilities that these ICT products can offer. What is more, for a typical user, the abundance of ICT products in his or her environment has reached an emotional and cognitive saturation point (Rutkowski and Saunders 2010).

This gives rise to what we call the bottleneck of the attention bandwidth. It leads to users who are saturated and intimidated by the number of ICT applications they have to use. Users have to divide their attention between many different products, so they have less time to spend on a single product (a product can be anything from an ICT appliance to a web service).

One effect of the attention bandwidth bottleneck is that users are becoming more receptive to software products that demand less attention and effort to use. This has consequences for the way in which product builders have to innovate in their product portfolio. Before the bottleneck arose, software innovation boiled down to feeding users with new functionalities to which they responded favourably. Due to the bottleneck, such a strategy is becoming outdated. The transition in user needs offers software companies a growing opportunity to revise their product innovation strategy with the aim of responding to the growing need to make their products more attention bandwidth-efficient (Norman 1998).

Another consequence is that it introduces a new dimension of competition for software companies. As there are so many software products available, it becomes increasingly difficult to stand out in this growing jungle of software products. This results in a race for customer attention. In addition to the normal competition model that governs their market, software companies now compete with many other products to receive the (limited) attention of the user.

The challenges presented above need not necessarily be perceived as a threat. On the contrary, they can present themselves as opportunities to exploit the possibilities offered by the new generation of ICT technology. We identified two families of opportunities:

• Opportunity 1: product innovations that respond to the problems of attention bandwidth pains of users. As argued above, the number of ICT products users have to deal with today is many times that of just a few years ago. Users are more conscious of the attention bandwidth problem and prefer products that either only require a limited amount of their attention bandwidth or increase it. An ICT product builder can differentiate its product portfolio by building products that help users to address this problem.

  Question 1: How can an ICT product builder innovate in its product portfolio to address the problem of attention bandwidth?

• Opportunity 2: product innovations that respond to the new level of competition between ICT products. This type of product innovations exploits the oversupply of ICT products. This oversupply generates a rich ecosystem of building blocks. A product builder can draw on multiple open data sources, available technological infrastructures and innovative business models (Osterwalder and Pigneur 2009). Companies can innovate in their product portfolio by responding to this new reality.

  Question 2: How can ICT product builders identify and exploit the existing sources in an ICT ecosystem and combine them with their own product portfolio?

  Question 3: How can ICT product builders reposition their product portfolio so that it can serve as a source for other players in the ICT ecosystem? (Bartels 2009)

Both opportunities boil down to a common industrial challenge: How do I innovate in my product portfolio to make it ‘smart’ or ‘intelligent’ with ICT?

This brings us to our definition of a ‘smart product’, which is a product that uses information about itself, the environment in which it operates or other products in its environment, with the aim of differentiating it in its market.

Smart products can address the attention bandwidth bottleneck in several ways. In general, the goal is to offer products that show proactive behaviour, i.e., they rely on the knowledge inside the product, the environment or other products to predict, detect and support the user’s intentions as closely as possible so that the user is relieved.

This can be done in different ways (Eggermont 2002):

• Monitoring: A product monitors an environment and only informs users about relevant opportunities in the environment, e.g., a surveillance system with motion detection that alerts the operator only when there is activity in the observed area. This relieves the operator from continuously having to scan the screens (hence addressing the user attention bottleneck).

• Advising: A product advises the users (proactively) about a particular strategy to realize an intention. Users are free to follow the advice if they wish, e.g., a car navigation system detects the user’s position and offers advice on how to proceed to a location.

• Assisting: A product is in constant interaction with the user during the realization of the goal. For certain tasks, the product actively assists the user during the execution, e.g., Toyota™ introduced an Intelligent Parking Assist System that allows the car to steer itself into a parking space with little input from the user.

• Intervening : A product can intervene when a user makes a wrong decision, e.g., in a chemical plant, a software system could stop the production line when a life-threatening situation occurs.

2.8.2 The Art of Crafting Smart Products – Main Activities

Seven activities across three phases must be mastered in this art (see Fig. 2.15). Each activity is described in detail in the remainder of this section.

Fig. 2.15

Activities of the art of crafting smart products

2.8.2.1 Smart Opportunity Spotting

The focus of this activity is on identifying the opportunities that a software company has for making its product smart or smarter.

Four strategies can be adopted to make products smarter with software. They are depicted in Fig. 2.16 and explained below.

Fig. 2.16

A framework for reasoning about opportunities for making products smart

• Self-Conscious Products : A self-conscious product is one that uses assets that are already available within it to offer new value to existing or different users. For example, Automatic Data Processing™ is a US-based company that processes payroll data. It possesses knowledge about the wages of personnel at different companies. This company aggregates these data (anonymously) in a new service called the ADP Employment Report™⁸ and offers them to investors, governments and HR departments. The company has made its product more self-conscious and has created an additional revenue stream by exploiting data that it already had in its possession.

• User-Conscious Products: A user-conscious product is a product that is designed to be aware of its users (e.g., user preferences, goals, intentions, emotions, etc.). Based on this information, the product can adapt its behaviour, i.e., to offer user bandwidth-saving functionality. For example, a provider of news content (e.g., an online newspaper) can analyse a user’s preference with respect to the kind of news articles he or she reads. Based on this information, it can offer a personalized news stream that contains the articles in which the user will be most interested. This relieves the user from having to search through the news items.

• Ecosystem-Conscious Products : An ecosystem-conscious product is one that is designed to be aware of other products and platforms that are (or can be) used together with it. Many different software ecosystems (e.g., AppExchange™, Apple App Store™, iGoogle Widgets, etc.) have become available. For example, Zoho CRM™ exploits the Google Apps for Businesses™ platform that integrates with Gmail™ so that account managers can track all emails sent from within the organization to an account. Besides such integration possibilities between these two cloud applications, the platform also acts as a marketplace for B2B products. An example is a hardware ecosystem around the ioHomeControl™ in which different businesses in home automation systems have jointly developed a standard that enables different home automation components to interoperate.

• Ambient-Conscious Products : An ambient-conscious product is one that uses information about the operating environment of a product to offer new value. This type of smart product exploits the wide variety of sensors that is available today. For example, a city-wide bicycle rental service could embed sensors in bicycles to gather information about the location of the bicycles. This would enable the bicycle rental service to recover bicycles that were not returned. If sensors were also added that could measure noise and other pollution, it would allow such a company to sell this information to governments. Note that the sensors do not necessarily need to be hardware sensors. The short geo-tagged messages from a service like Twitter™ could also be used as sensors. This would require the text messages to be analysed with text algorithms.

Applying this smart product framework to a product will usually result in a substantial list of opportunities that need to be filtered to a shortlist. When filtering opportunities down to such a shortlist, it is important to know where to put the focus (see Sect. 2.3). Such filtering can be done by scoring the opportunities according to the value they would bring and the risks associated with pursuing them (see Sect. 2.5).

2.8.2.2 Engineering Self-Conscious Smart Products

Engineering of self-conscious products is the extension of a product with ICT functionalities that exploit the assets available in that product in some smart way. In order to engineer self-conscious products, it is important to ask a number of questions that can provide an insight into how to approach such opportunities.

What is the inventory of available assets to exploit?

Engineering of self-conscious products starts from an in-depth analysis of the assets that are available within the product portfolio of the company. An asset can be data-oriented (e.g., a data set stored in a product), a community (e.g., a user community using the product) or an algorithm. It is important to understand which assets are unique with respect to the competition and which assets are a commodity. This can change over time, as illustrated by digital cartography.

Less than a decade ago, digital maps were unique and required huge investments (special trucks had to drive along all roads to chart the different roads and accompanying traffic signals). This made digital maps a unique asset. More recently however, efforts such as OpenStreetMaps⁹ have used public communities to create cheap and accessible alternatives so that the digital maps themselves became a commodity. Vendors of commercial digital maps were forced to partner with application providers (e.g., the acquisition of TeleAtlas™ by TomTom™) that could provide them with a community¹⁰ (e.g., TomTom™ enables its users to send updates about changed roads and traffic conditions, which enables them to update the digital maps much more frequently).

When drawing up the inventory of available data assets, the underlying structure of the data should also be taken into account because it can heavily influence the usability of the data for a specific purpose. Semantic technologies such as RDF, OWL and other metadata systems may provide solutions to bring the data into the necessary formats, perhaps also complemented with a partial redesign of the existing underlying data models.

In the example of the payroll software (see Sect. 2.8.2.1), customers of ADP™ will probably use different titles for their employees. In one company, an employee may be called a ‘software engineer’ whereas in another company an employee performing the same tasks may be called a ‘software developer’. To aggregate the information, these titles need to be matched.

Which available third-party assets can complement my assets?

In order to realize a value proposition based on the existing assets of the product, some data sets that are required to realize the value proposition will often not be in the possession of the company. Besides preparing the existing data models, it may therefore also be necessary to gather new types of information that are missing.

This information can come from third-party resources (e.g., address information can be looked up by querying the Google Maps™ API; a company called InfoChimps™ provides an API to access different kinds of data, allowing companies to share them).

Some information may at first not be readily available in the product itself but can be harnessed by redesigning parts of the existing product based on Crowdsourcing techniques. For example, Google™ optimizes search results by analysing user behaviour with respect to search results, i.e., after a search query, the user chooses to visit one or more links that the query has returned. These clicks can be considered votes by users on which results were relevant and which were not. By logging these clicks, they can be used to further optimize the results that were returned.

Finally, once all the necessary data are gathered in the required formats it may be necessary to process the data so that they are made available in the required format. This processing of information is not always straightforward from a technical point of view and may require the use of advanced AI algorithms, such as neural networks. For example, in the case of optimizing the search results by logging the clicked links, a multilayer perception network may be used to learn the ranking of a link for a given set of keywords.

How can the available assets be transformed into innovations?

A first option is to explore whether it is possible to use the available assets to offer functionality for a safe attention bandwidth for the user. The frame described in the introduction to this chapter can be used to do this:

• Monitoring: Can the assets be used to offer monitoring functionality?

• Advising: Can the assets be used to offer better advising functionality?

• Assisting: Can the assets be used to offer better assisting functionality?

• Intervening : Can the assets be used to offer intervening functionality?

A second option to explore is whether it is possible to ‘package’ the assets somehow as a new service in which other parties would be interested. An example is the ADP Employment Report™ service discussed above.

2.8.2.3 Engineering User-Conscious Smart Products

A user-conscious product is aware of its user and offers functionality that exploits this awareness.

A user intention is some kind of goal or purpose that a user wants to achieve and for which he or she will use the product (Why are users using your product?). Examples of intentions include business goals (e.g., generating a report, paying employees, increasing sales …) and personal goals (e.g., weight loss, learning to run a marathon …)

When realizing their intentions, users are influenced by different parameters. Examples include:

• The role of a user in a collaborative workflow. Is the user a decision-maker, an expert … Depending on the role, users will act differently.

• Emotion. Depending on the emotional state, users will act differently, e.g., Google offers a feature (Gmail™ Goggles) that prevents users from sending emails in a drunken state. A number of sensors have also become available in recent years to detect the emotional state of users (Conati et al. 2003; Alastair et al. 2008; Gill et al. 2009 Sebe et al. 2004).

• Stress level. Users under pressure will behave differently to those in a relaxed environment.

To provide advanced support for user intentions, software products should capture these parameters in order to understand the information related to a user who can influence the realization of a particular user intention (= the user state ). For example, in a stressful situation, the support of the software product may shift from merely ‘monitoring’ to ‘intervening’.

The crafting of user-conscious products requires insights into these two important aspects of the user: the user intentions and the user state.

The following questions need to be answered.

How will the user state and user intention be captured?

In some situations, the user intentions and user state remain the same throughout the use of the product. In this case, it can be considered during the requirements analysis phase and the design phase of the software product.

In other cases, it may be necessary to observe the user when he or she uses the product, so that the behaviour of the product can be adapted to changes in user intention and/or user state. Many options are possible:

• Attaching physical sensors to the user (e.g., to measure stress)

• Non-intrusive observation of users (e.g., with cameras)

• Observing how the product is used (e.g., by logging the actions users perform)

• Observing social software platforms in which the user is active (e.g., what can be derived from public information on Facebook™)

• Use of user profiles (e.g., asking users to provide a profile)

How will knowledge about the user state and user intention be used in product innovations?

First of all, it will be necessary to include a model of the user state and user intention in the software product (e.g., emotion model). The size and complexity of this model depends on the kind of information that needs to be captured: Which intentions are relevant for capture? Which emotions are relevant for capture? What information about the user is important with respect to the tasks that he or she is doing?

Next, this model has to be used to offer product functionalities. An example is the Volvo-On-Call-Plus™ system that detects car crashes. When a car crash occurs, it automatically sends the last known GPS location to a dispatching service and puts it in contact with the driver through a speaker system. After assessing the situation with the driver or, in the case that no one is able to respond, the dispatching service can warn the emergency services.

2.8.2.4 Engineering Ecosystem-Conscious Smart Products

Ecosystem-conscious products are aware of other products present in the user environment. They attempt to use this awareness to realize new value propositions. The result is a so-called product ecosystem in which each product has its own value proposition but can lever the value offered by the ecosystem to make its value proposition stronger.

Examples of ecosystems include:

• iPod™ Ecosystems: Apple has created different ecosystems around its iPod™ product. One such ecosystem is geared towards car manufacturers that enable the iPod to be controlled from the car audio system. Another ecosystem combines the iPod™ with Nike™ running shoes via a sensor in the shoes so that an iPod can select music based on the rhythm of the runner.

• Google for Businesses™ is a B2B platform that enables cloud-based business applications to interface with the different Google Business Applications. Different types of integrations can be made, such as access to Google Mail, Google Calendar, etc. The platform also acts as a marketplace.

You can either decide to participate in an existing ecosystem (such as Google for Businesses™, AppExchange™, Facebook™, etc.) or become an initiator of an ecosystem. Decision criteria include:

• The availability of assets (e.g., data, user communities, etc.) of interest to your product in other products used by your users. A product such as Google for Businesses™, which has gained a fairly large user community of SMEs, becomes interesting as a new channel to reach customers. It is also important to gain a good understanding of which products, besides yours, a user uses to perform his or her tasks. Once you have this insight, providing a smooth integration (from the perspective of usability and data) can help in addressing attention bandwidth bottlenecks.

• You have an asset to share with other products. Successful products may have assets that enable it to create an ecosystem around it. For example, Heroku™, a cloud-based platform provider, opened its platform to third-party component developers once it gained a critical mass of application developers. In this case, the asset was the community of application developers. In order for such an ecosystem to work, it is important to search for win-win combinations in which both the owner of the ecosystem and the participant have sufficient benefits.

• You capture information that would be better captured elsewhere. Another way of looking at it is to shift the capturing technology away from your product. Is there another product that does a better job of capturing the data that could be of benefit to your product? And, would/could you connect to it?

• You want to enter a new market. New markets have their own dynamics with which you may not be familiar, but you may have assets that are new and disruptive to this market. Finding an ecosystem that is already established in this market may offer a way to gain access to the required resources to address this market.

Three main challenges will need to be addressed.

What is the impact on the product from participating in an ecosystem?

Joining an ecosystem requires rethinking about the product in the context of the ecosystem. Below are some strategies on how the product can be rethought in the context of the ecosystem.

• Simplification of the product : joining an ecosystem can provide an opportunity to reduce the complexity of using a product. Users who make use of different products to work towards a goal can expect the different products in the ecosystem to cooperate towards achieving this goal. For example, consider a salesperson who needs to drive from one customer to another. The car navigation system can automatically set the destination by consulting the agenda on the salesperson’s mobile phone.

• Enhanced functionality : joining an ecosystem can also offer opportunities to differentiate the product by offering new functionality. One such example is the iPod™-Nike™ ecosystem, which enables an enhanced running experience that is impossible to achieve without the ecosystem.

How will the product interact technically with the other products in the ecosystem?

Besides the business aspects of creating an ecosystem, there are several technical aspects that have to be taken into account. The product has to be (re)designed so that it supports the interoperability vision of the ecosystem. Choosing the right architecture and technical interoperability standards can make or break the adoption of the ecosystem. For example, in hardware systems, standards can impose certain requirements on the chip or require certifications that increase the unit costs of the product. In pure software products, these issues usually do not play such a big role. In these, the challenge is to provide support for the rich variety of software implementation frameworks and technologies.

How do you set up alliances with other product builders in the ecosystem?

To what extent will other software providers need to be involved. In some situations, the other products may already provide an API or interface that you can use to hook up your product. In other situations, an alliance will have to be set up with one or more other software companies. Another important consideration is to understand the balance of power in the ecosystem. Apple™ was/is often criticized for its unclear policies with regard to the apps it allowed in its App Store™. The result was that several Mobile Apps were rejected or even removed from the App Store™. Policies could also change at any time so that there was great uncertainty for Mobile App developers.

2.8.2.5 Engineering Ambient-Conscious Smart Products

In this strategy, we aim to make the product aware of the ambient environment (the word ambient refers to the product’s surrounding environment and is used interchangeably in the text below) in which it operates. This strategy is implemented by augmenting the product with an interface to its ambient environment. Using this interface, it can make interpretations about its environment and use that knowledge in different ways.

Can you become a source of information about the surrounding environment to other parties?

In order to identify the possibilities of becoming a source, an inventory of existing activities and an understanding of the possibilities of ICT technologies with respect to collecting information about the surrounding environment (=potential ambient data-sets) are required.

For each of these, its value, uniqueness and sustainability have to be considered so that a business case can be developed.

Example: A bicycle rental company has different (automated) rental stations posted across the city. People enter their credit card into one such station to rent a bicycle and return it to one of the many stations posted throughout the city. The company considers integrating GPS tracking devices into the bicycles so that lost bikes can be found. It could go one step further, however, by integrating other types of sensors into the bicycles. Sensors that can measure air and noise pollution could be used to gain an understanding about its evolution over time. Such information has the potential to be sold to local governments.

Example: A mobile phone operator has multiple cellular network masts posted across a country. It has the ability to track the position and movements of mobile phones across the network, and by aggregating this information it can identify traffic congestions.

The examples above illustrate how existing business activities can be leveraged by fitting appropriate sensor technology to these activities. Note that the sensor technology that is used to collect the required information can be hardware sensors, as in the first example, or software algorithms such as the triangulation algorithms in the second example.

An important consideration when collecting ambient data sets is privacy. In both examples presented above, the tracking of individuals may be problematic from a privacy point of view. By aggregating the information and making it impossible to track information back to individuals, such issues can be handled.

How can the available ambient information be transformed into innovations?

The use of ambient information in applications can provide support for the attention bandwidth bottleneck problem. The examples given in Sect. 2.8.1 illustrate how ambient information can be used to support monitoring, advising, assisting and intervening.

Another option is to combine ambient information with information about user intentions.

Example: Consider an alarm clock, for example, that is made aware of the reason a user needs a wake-up call and can take advantage of this information. If a user is woken up with the aim of not being late for work, then it could consider the traffic conditions on the road to work. Based on this information, it could decide to wake the user up a little earlier (e.g., in the case of traffic congestion) or let the user wake up a little later (e.g., in the case of good traffic conditions).

2.8.2.6 Smart Technology Scouting

Several state-of-the-art technologies are available to support engineering of smart products. Examples of these technology domains include:

• Sensor technologies is a big domain that encompasses a wide range of sensors, such as positioning sensors for indoors (Hui and Wang 2006) and outdoors (Sun et al. 2005), sensors for measuring biological processes (Yang et al. 2006), sensors for detecting emotion (Conati et al. 2003; Alastair et al. 2008; Nicu et al. 2004) and software sensors (Fortuna et al. 2007).

• Ubiquitous computing (Weiser 1991; Poslad 2009), pervasive computing (Satyanarayanan 2001) and ambient intelligence (Aarts et al. 2001): these names refer to a post-desktop model of human-computer interaction in which information processing has been thoroughly integrated into everyday objects and activities. In this technology domain, we find technologies that help save attention bandwidth because the objects can process information for their users and interpret that information for them.

• The Semantic Web (Berners-Lee et al. 2001) is a collaborative effort between researchers and industry with the aim of providing a common framework that allows data to be shared and reused across application, enterprise and community boundaries. The data are accompanied by meta-information that enables automatic aggregation and reasoning. In this technology domain, we can find technologies that support sourcing of data and services by (semi-) automatically recombining data and services in a novel manner. Many different standards such as RDF, OWL, SPARQL and Microformats have been developed.

• Web 2.0 (O’Reilly 2005) is a commonly associated web application that facilitates interactive information sharing through collaboration. The technologies for creating web mash-ups are of a form in which information in services can be blended and moulded into a new web service. These technologies can be regarded as enablers for supporting sourcing of data and services in the context of the web.

For software companies to be successful at crafting smart products, the setting up of a smart technology scouting program is an important activity (Rohrbeck 2010). Actively hunting for new technologies and understanding the opportunities they offer is essential to remaining up to date and staying ahead of the competition.

Although many of these technologies have matured to the extent that it has become feasible to employ them in products, not many software companies are actually exploiting their use. This is especially true of smaller companies that cannot afford the resources.

There are so many ways in which these technologies can be used that it becomes difficult for software companies to understand their options and make choices. Some technologies are heavily promoted by the research community, while others are less well known, even though they may be very valuable options to explore. In the domain of ambient intelligence, for example, (wireless) sensors are being used to sense context information. For software companies in domains like home automation or mechatronics, there is clear innovation potential to incorporate these sensors into products. This is less obvious to software companies in the domain of banking and administrative software however. The differentiation approaches can therefore be very different dependent on the product and company context. An effective and efficient scouting program should take this into account and offer the necessary criteria to decide and steer the technology-hunting in the desired direction.

2.8.2.7 User Behaviour Scouting

Your software company will probably have installed processes to monitor its market and competitors so it can act in time when the market expresses new needs or competitors launch new innovations.

How much does your company actually know about the other (non-competitor) software products that your users are using today? And, how much do you know about the way your users use your product?

Gathering this information is important because it could provide the necessary knowledge to hook the software product up to other products or to create an enhanced user experience that results in bandwidth savings for the user.

Nagravision™, a company producing set-top boxes for digital broadcasting channels, has found that many users are actually sitting in front of their TVs with laptops, iPads, etc. While watching TV, they are interacting on social networks, looking up extra information on what is being broadcast, etc. In order to better support this combined use of so-called second and third screens with a set-top box, it has created a multi-screen consumption model. This enables the integration of cloud- and client-centric models to be combined with the TV watching experience. For example, users can obtain recommendations on what to watch, start watching a fragment on a second screen and flawlessly switch to the TV set and continue to watch it there.

Doing this on a continuous basis is important, as it will generate opportunities to make the product smarter (see Sect. 2.8.2.1).

A straightforward way to gather this information is just to ask your customer through periodical querying.

Other companies carry out brainstorming activities with their customers. One example is innovation games (Hohmann 2006). The innovation game ‘Me and My Shadow’ can be used to observe the way users use a product. Another interesting innovation game in this context is ‘Spider Web’. The product is placed in the middle of a spider web and customers are asked to what other products they think your product is related. These products are also put on the spider web and the relationships between these products are made explicit.

How and where is your product used?

This question explores the immediate physical space around the use of your product. Explore the possibilities this space could give you in added value by creating a collaborative system. Are there possible collaborations and connections you could make with other products in the environment?

2.8.3 Relations with Other Practice Areas

The Art of Crafting Smart Products relates to several other practice areas:

• The Art of Openness: opportunities that are identified in the Art of Crafting Smart Products may require the use of advanced technologies that demand in-depth understanding of the possibilities and limitations. This expertise can be built up entirely in-house or with help from outsiders. The technology scouting activity will provide an insight into choosing the right partners for sourcing the lack of expertise.

• The Art of Innovation Incubation: smart opportunities that are of a more disruptive nature or outside the established markets of a company may require an appropriate incubation process. For these opportunities, it is important to gain an in-depth understanding of the market needs and the adoption cycle.

• The Art of Focusing : after having identified multiple possibilities, it will be important to choose a focus and to keep that focus from conception to innovation.

2.8.4 Questions

In order to start thinking about the Art of Crafting Smart Products, you could ask yourself the following questions:

• What assets does your product have available in the inventory that are difficult for other parties to replicate?

• Which available third-party assets could complement my assets?

• How can the available assets be transformed into innovations?

• How can knowledge about the user state and user intention be used in product innovations?

• What other products are our users using together with our product? Is it possible to join or build an ecosystem around those products?

• Is it possible to become a source of information about the surrounding environment?

• How can the available ambient information be transformed into innovations?

• What are the technological trends? Who are the potential partners who can allow us to quickly gain the required expertise in these technologies?

• How and where is your product used?

2.9 The Art of Innovation Stimulation

Asta Bäck

2.9.1 Description and Scope

Very often in software engineering, innovation boils down to problem solving and firefighting without any real, long-term innovation culture. Instead, there is an attitude of high productivity and meeting deadlines. In the current competitive environment, companies must be involved in constantly renewing their products, services and processes. The increasing role of software in products and services, and the global business possibilities offer huge opportunities for new innovation but also make innovation imperative.

Many examples and much research show that the most successful companies are able to create new innovations continuously, not just randomly as lucky guesses. This practice area looks at what can be done in a company to stimulate innovation from a wide perspective. It does not only look at stimulating creativity at single events – such as brainstorming sessions – but at the whole company and what can be done to stimulate innovation on a continuous and systematic basis.

A software company should have continuous innovation activities to produce incremental and radical innovations. With regard to software, there are many different areas for innovation. Innovation may concern the purpose of and to whom software is offered; which standards, platforms and ecosystems the software is built on; what the business model is; how users interact with the application; what production methods are used; and solving various specific technical issues.

This chapter includes theoretical as well as practical aspects of innovation stimulation. Creativity and innovation are closely related concepts. Creativity is what is needed to get innovation started. The main activities relating to innovation stimulation are presented based on the theories behind organizational and individual creativity, and practical experiences.

The natural way to start is to analyse where the bottlenecks are to producing and sharing creative ideas and turning them into innovations. Some things, like the company climate, are slow to change, whereas other things, like learning to use a new creativity enhancement method, can be learnt quickly. For permanent, long-term improvements to the company’s creativity and innovativeness, all the levels must be seen to be in order. Quick results are also needed, however, in order to raise interest and keep the motivation up for further development.

2.9.2 Main Activities

Seven activities have been identified relating to the Art of Innovation Stimulation: two to the Starting phase, three to the Addressing stage and two to the Sustaining stage. Figure 2.17 shows all the activities involved in the Art of Innovation Stimulation and their relationships to the rest of the arts.

Fig. 2.17

The art of innovation stimulation and the activities involved

2.9.2.1 Evaluate Your Organization’s Creativity

The first step is to assess the current situation in order to find out what your organization’s strengths and weaknesses are in relation to creativeness and innovativeness. This way you can target the development work to tackle the issues that have the highest impact potential but, before measuring, it is crucial to know what creativity and innovativeness are and how they can be assessed.

In this book, we define creativity as the ability to produce new ideas and solutions, and innovativeness as the ability to produce new innovations. An innovation starts as a creative idea. Much work is then needed to turn the idea into a real, profit-making product or service. Creativity is also needed along the way from idea to innovation to solve all the issues that are faced during the innovation process.

Based on this definition, innovativeness can be measured by looking at high-level performance measures such as the number of new products and services that the company is able to bring to the market on a yearly basis and the revenue generated from them. These kinds of measures can also be used to give concrete targets to innovation stimulation, but they are slow and do not help to identify where the weak spots are. The company should therefore develop additional measures that shed light on issues dealing with creativity – the potential to come up with new ideas.

Seminal research relating to creativity in organizations was published in the nineties. Ekvall (1996) introduced the metaphor of climate to describe the organizational conditions affecting creativity, and Amabile (1997) the componential theory of individual and organizational creativity.

Ekvall’s theory (1996) identified nine climate dimensions. These climate dimensions have been shown to discriminate between the best and the worst environments and between the most and the least creative teams. The dimensions are involvement, freedom, trust, idea time, playfulness, conflict, idea support, debate and risk taking (Isaksen and Ekvall 2010).

• Challenge or involvement refers to the degree to which people are involved in daily operations, long-term goals and visions. High involvement indicates motivated and committed people.

• Freedom describes the independence and autonomy that people have in the organization with regard to their work.

• When trust or openness is high in the organization, people are more willing to share their ideas and to be frank and honest in their relationships with other people in the organization.

• Idea time is the time that people can use to elaborate on new ideas.

• Playfulness or humour is indicted in spontaneity and ease at the workplace, and these are conductive to innovation.

• Idea support refers to the way in which new ideas are treated and people react to each other’s ideas.

• Risk-taking describes the tolerance of uncertainty and ambiguity, for example, whether people can make decisions without being completely certainty and having all the necessary information.

• Debate refers to open disagreements between viewpoints and ideas. Debate contributes to sharing and combining different points of view and knowledge.

• Conflict refers to emotional tensions in the workplace. If conflict is high, people fight and plot against each other, which is naturally bad for creativity and productivity in general.

Amabile’s Componential Theory of individual/team and organizational creativity (1997) identifies three main components in both of these areas. Individual/team creativity is needed for organizational creativity, and the organization’s actions determine whether this creativity flourishes in practice.

The components at individual and team level are expertise, task motivation and creativity skills. The expertise component refers to knowledge and skills in the actual professional field in which innovation is looked after. There are two types of task motivation : extrinsic and intrinsic. Extrinsic motivation refers to factors like rewards or pressure, and intrinsic motivation refers to personal motivation to work because the person finds the work interesting, exciting and personally challenging. Creative thinking skills refer to the cognitive style that favours taking new perspectives on solving problems. Creative thinking skills depend, to some extent, on personality characteristics like independence, self-discipline, orientation towards risk taking, tolerance of ambiguity, perseverance in the face of frustration, and a relative lack of concern for social approval (Amabile 1997). The components of the work environment are organizational motivation, resources and management practices (Amabile 1997).

Ekvall (1996) and Amabile (1997) have both developed questionnaires that measure factors that their respective models of organizational creativity describe. In Moultrie and Young (2010), shortened versions of these question sets are presented, capturing the main aspects of these theories. Using these questionnaires, organization members can tell to what extent they agree with the presented claims. The results give an overall view of the way people in the organization see the current situation in the company, helping to pinpoint the areas to be improved.

2.9.2.2 Build on the Passion of Software Engineers

Software developers are often highly committed and proud of their work. This can be seen in many open source projects in which developers participate and cooperate in their own time to contribute to a common goal. These open source projects are also proof that it is the person’s intrinsic motivation that counts.

This is also in line with the previously mentioned Amabile’s Componential Theory of organizational creativity. According to this theory, expertise and creativity skills define what a person can do, and the third component, task motivation, defines what a person is willing to do. There are two types of motivation: extrinsic or external, and intrinsic or internal. Intrinsic motivation is partly a personality issue, but social environment can also have a significant, either positive or negative, effect on a person’s level of intrinsic motivation (Amabile 1997). As intrinsic motivation is hard to produce from the outside, it is important to hire people with high intrinsic motivation.

Extrinsic motivation can be used, to some extent, to increase motivation, but it cannot compensate for a lack of intrinsic motivation. It is also important to know that extrinsic motivation measures may even reduce intrinsic motivation. Rewards, recognition, better resources, more independence and frequent feedback on work are examples of extrinsic ways of motivation that are also likely to support and boost intrinsic motivation.

Giving software engineers the opportunity to explore new areas supports motivation and increases the likelihood of them coming up with new ideas. In any case, software engineers often work independently and are constantly making decision that, on the whole, may have a big impact on the final result. When intrinsic motivation and freedom can be aligned with your company’s goals to bring true value to customers, much creative energy will be available in the company.

2.9.2.3 Establish Processes and Tools for Innovation

Processes and tools, as well as communication and discussion skills are needed for creativity to bloom. Processes and tools do not make innovations, though a well-defined process for evaluating ideas has been found to stimulate innovation (DeSouza et al. 2009).

New innovations are hardly produced by one person alone. Collaboration and communication are therefore crucial throughout the innovation process. Even though new ideas often require an idea owner or champion who pushes the idea forward in the organization, the idea can only be developed in collaboration with different parties. This development work requires good communication skills. Mock-ups, demos and other concrete results are examples of so-called boundary objects that capture different people’s ideas and knowledge in one artefact and make communication between different partners easier. Managers should encourage their people to maintain formal and informal interaction, active listening and constructive controversy. It is also important that managers themselves show, in their everyday activities, that they value innovations and new ideas.

There is an optimal amount of discussion and debate. Closing the discussion too quickly is dangerous because important views of people with different knowledge and backgrounds may be missed, though discussing too many things or for too long without making decisions is also counterproductive and should be avoided.

Another important issue is to realise the difference between productive debate and conflict. There are different types of conflict. Task conflict refers to disagreements relating to work content and includes differences in viewpoints, ideas and opinions. Emotional conflict is characterized by anger, frustration or hostility among or between individuals on a personal level. Process conflict refers to disagreements over the approach to the task, the desired group processes and the method the group chooses to follow. The first type has been found to have a positive outcome on some research, but the last two clearly have a negative impact on the performance and creativity of an organization (Isaksen and Ekvall 2010).

No organization is completely free of personal tension and conflict, and a complete lack of conflict would probably indicate a complete lack of involvement in the work. The managers’ task is to introduce actions to alleviate possible tensions and provide training to people to teach them to focus on task conflict away from a personal level.

Face-to-face discussions are important to creativity, as are various types of tools that can support the collaboration process. In a software company, people already use many tools for communication and sharing of ideas. Communication using email and various other tools is likely be fragmented, however, and does not help in the accumulation of knowledge at company level.

Asynchronous tools like wikis provide means for storing ideas and building and commenting on them in turn, whereas synchronous, real-time tools like Etherpad¹¹ support co-creation by people in different locations or even face-to-face meetings, making co-creation more effective.

As well as tools for direct idea collaboration, tools that support finding people with knowledge are becoming increasingly important. The bigger the company, the more tools are needed to identify people with knowledge or interest. Various kinds of social networking tools play a key role here.

2.9.2.4 Build Creative Teams

Much of the work that is done on creative problem solving and innovation takes place in teams. In requirements engineering, for example, creativity often takes place in a team setting (Nguyen and Shanks 2009).Teambuilding is therefore crucial, and different aspects need to be taken into consideration when innovation teams are being created. The two most important aspects are finding the correct combination of skills and knowledge in the team and making sure that the team can communicate and cooperate well.

A good starting point is to involve people with high intrinsic motivation. The team should have people with different knowledge and backgrounds in order to increase the likelihood of them coming up with creative solutions. The risk of involving people with different backgrounds is that communication between them may become more difficult. Using design-based communication methods such as rapid-prototyping, modelling, storytelling and persona-based scenarios can mitigate this risk. These methods use many human senses and are able to capture some of the complexity of the real world (Steiner 2009).

The use of Agile methods in software development is one of the ways to stimulate innovation. There are two important factors contributing to this: rapid development quickly takes requirements into prototypes that can be evaluated by different parties, and the presence of the customer in the process provides quick feedback based on real needs.

In Cotterman et al. (2009), 32 of Business Week’s Top 100 Most Innovative companies were studied. The companies that produced disruptive innovations systematically were found to have organized innovation differently, in some ways, to the rest. One differentiating factor was that the most innovative companies had dedicated cross-functional groups for innovation, with members from, at least, the technical and marketing departments. They had also trained their people for their chosen innovation approach and techniques, which gave team members a common language. In addition to internal participants, customers were involved in innovation processes early on. The reward system also has to support innovation, not only at individual level but also at team level.

2.9.2.5 Introduce Creativity-Enhancing Techniques

Numerous methods have been developed to boost creativity in problem-solving sessions. Some examples and practices are presented here to get stimulating innovation started. Information about these methods can be found on websites like Ideaconnection¹², MyCoted¹³ and Gamestorming¹⁴. The frequent use of creativity-enhancing methods is more important than which methods are used.

Future foresight gathers information about future changes in the societal, economic and technical environment, and this material has the potential to stimulate creativity. One way of doing this is through trend spotting, which involves gathering pieces of information that may be indicative of bigger changes and new trends. They may be gathered from the web or events, by visiting innovative companies or just by observing media and life. Gathering and sharing observed things such as photos or notes is important to inspire creativity and accumulate different people’s observations into a shared resource.

Future scenarios are a way of combining information and visions of future opportunities. Scenarios are typically built by first gathering information about trends and weak signals and then combining and structuring them into alternative futures. Scenarios have the potential to reveal future trends that provide new opportunities or pose threats (Meristö and Laitinen 2009, p. 16).

Brainstorming is probably the best-known method for producing creative ideas. The key is to separate idea generation from idea valuation so that participants also become encouraged to present their funny and crazy ideas. Another basic assumption is that when there is quantity there is also quality. Typically, the first ideas that come up are old, well-know ones, but as the ideation continues, new ideas will emerge. The ideation is typically performed in groups of 6 –12 people in order to bring different points of view into a single group and to give participant the opportunity to build on each other’s ideas.

De Bono’s Six thinking hats ¹⁵ is another well-known method of ideation. The hats represent different points of view, such as facts, feelings, optimism and criticality. The method can be used either by selecting different roles for different people or by going through the different points of view together.

Distant thinking models is a method that tries to create new ideas by combining the topic of ideation with some item that is not obviously connected to it. For example, if the task is to improve a sports event, a fishing trip could be selected as the distant thinking model. First, the features and associations are listed for the distant model. As the second step, wild combinations are created by attaching these features to the topic of ideation. Finally, the wild combinations are elaborated further into more practical features or applications (Ojasalo et al. 2009).

Excursion technique can be used when generating new ideas, but it is not very successful. It can be carried out by picking a random object and asking participants to start generating associations and features relating to this randomly chosen object. At a time when the listing by the associations is going well, the leader of the workshop stops and picks the latest association and asks participants to combine it with the topic of the ideation (Ojasalo et al. 2009).

Recently, spaces have been specially built for innovation. They are often called innovation labs. These may be built within a company for internal use or offered as a service to a house innovation session. In Madagley and Birdi (2009), the effectiveness of such a lab was studied in the UK. There seemed to be a positive impact, though the impact was dependent on several factors. The use of a special external facility gave the participants the time and place as well as the technical support and human facilitation to concentrate on creative activities.

Virtual spaces, particularly 3D worlds like Second Life seem to hold a promise for creative work. They make it possible for people to meet across distances, and a virtual world can be used to visualize such future products or services that do not yet exist in real world.

Even though the company atmosphere and people’s attitudes are of utmost importance to creativity, the daily physical environment can also be used to enhance creativity. Space for free discussions on a comfortable sofa, and surprising creative and inspiring objects and media are examples of concrete support for creativity and innovation.

Competitions are a popular form of innovation stimulation, and there is much, though not unanimous, evidence that competition can increase innovation. Competitions may be organized internally or externally, and they can be used in connection with a short or long duration innovation activity. For example, a brainstorming session may be modified into a competition between groups in order to boost the total number of ideas created during the session.

Internal competitions may take the form of an internal challenge to solve issues that are of importance to the whole company or bring new ideas onto the table on a wide front. Internal competitions and challenges also stimulate innovation by showing the management’s real support for innovation, assuming that the admitted ideas are handled in a constructive and transparent way.

When designing an actual innovation competition, many aspects need to be decided (Bullinger and Moeslein 2010). Important issues are the competition environment – is it online, mixed or offline – how strictly is the task specified, and what should be presented as the entry – is it enough to present an idea or should it be developed further into a prototype?. Another important aspect to consider is whether the participation is meant for individuals or teams and whether collaboration between contestants is encouraged. If collaboration is encouraged, it is important to support it clearly and well (Bullinger et al. 2010).

Another variant of competitions is to invite students and hackers to participate in a live innovation camp in which people gather during an intensive period to code together and quickly build prototypes to demonstrate their ideas.

Before launching a competition, it is important to make sure that your company really needs what the competition is asking people to produce. For example, if the competition is aimed at generating new ideas for future products or services, you need to be ready to invest time and effort to evaluate the results and take the most promising ideas into further development. This is likely to be more resource consuming than initially assumed.

2.9.2.6 Give Time and Resources to Innovation

As we have mentioned in the previous paragraphs, Amabile’s Componental Model identifies three key elements: resources, management practices and organizational motivation. We have already talked about the last two. The resources element refers to different kinds of assets, such as time to innovate, people with expertise and funds (Amabile 1997).

Lack of time and competing task are a constant problem, and the recommendation is that the same people should not be involved in developing both existing and new products. If they are, the existing products will tend to take too much of their time, making the innovation project suffer (Cotterman et al. 2009).

In Lindeke et al. (2009), the time dedicated to innovation and cross-functional teams is pointed out as a key factor in innovation, and a model – The Temporal Think TankTM (T3^TM) – is proposed as a solution. In this model, creative people from different functions are assigned to work solely on new product development. For a small company, collaboration with other companies is suggested as a way of making it financially feasible to participate in cross-functional innovation.

Events like downsizing (reducing the number of employees in the department or organization) are likely to have a negative impact on creativity. The impact on creativity seems to recover more slowly than performance indicators such as productivity. The biggest drop in creativity is seen when downsizing is expected. Disruptions in teams, i.e., interruptions to people’s normal collaboration patterns and networks, also have a negative impact (Amabile and Conti 1999).

2.9.2.7 Get Connected

Liu (2011) has looked at the way network structures affect innovation. Alliances play a key role in promoting inter-firm, information sharing and creation. A broad network connection was found to have a positive effect on innovation performance. This can be explained by the fact that a large number of network ties and being well positioned in a network improve diversified information sharing among partners. Broad connections may give unique access to a variety of information and knowledge.

Both the social network view and organizational learning theory confirm that diversity in information and knowledge access is a necessary premise of acquiring and internalizing external resources. Networks also give partners the opportunity to interact, share innovation ideas and to develop mutual understanding and trust. Innovation alliances give companies an opportunity to learn from each other and to exploit that learning in order to develop new knowledge and produce new goods and services, thus obtaining superior innovative performance.

Networking with other companies is important, not only to get new ideas and information but also to be able to meet new customer requirements and seize new opportunities quickly. In Johannessen and Olsen (2010), a claim is made that, in the future, Connect and Provide (C&P) will increasingly replace Research and Development (R&D) as a way of creating new offerings. Using the term coopetition, coined by Raymond Noorda, they emphasize the importance of finding new ways to operate by balancing cooperation and competition. Cooperation is needed for creating, sharing and accumulating knowledge, and some competition is necessary to keep companies active in developing their cost-efficiency.

In the context of software industries, especially web-based applications, it is often possible, without too much effort, to gather data on how people use them. This information can be vital for new innovations to be introduced into the product/service, and it may help the company identify its lead users for closer co-development. Combining this with social media tools to collect customers’ opinions and needs can be a great source of information to boost innovations.

2.9.3 Relations with Other PAs

Due to its broad scope, innovation stimulation is connected to many ‘The Art of Software Innovation’ -book practice areas.

The intrinsic motivation and passion for software engineers is an important asset for creativity. It is crucial that this enthusiasm is focused on things that are useful and interesting to the company and its customers. The Art of Focusing supports channelling of this creative potential in the right direction.

The activity ‘Introduce innovation collaboration’ supports the Art of Idea harvesting and the Art of Innovation Incubation. Collaboration and communication skills contribute to improving and combining many people’s ideas and thereby lead the way to better ideas for harvesting.

The activities in ‘Introduce Creativity-Enhancing Techniques’ and ‘Use Competitions and Games’ are connected to the Art of Idea Harvesting. These activities support the actual act of generating ideas.

The need for innovation stimulation is not only about more creativity when generating new ideas. Creativity and creative problem solving are needed along the process to turn ideas into real innovations. Building Creative Teams, Introducing Innovation Collaboration and Introducing Creativity-Enhancing Techniques are activities that contribute to the Art of Innovation Incubation.

The Art of Openness is one important way of stimulating innovation. Information coming from outside the company about users’ and customers’ needs and requirements is an important source of new ideas and a source of feedback during the development phase. New solutions can also be sought with the help of open innovation from users and professionals from outside the company. The Art of Openness supports the activity to ‘Get connected’.

The Art of Optimizing the Impact of Critical Experts relates to the Art of Innovation Stimulation in the sense that innovation requires resources and time. The most motivated and creative people should not be completely tied to carry out urgent tasks but should also have some time and freedom to explore new ideas and opportunities.

2.9.4 Questions/Checklist

• What are the bottlenecks limiting your organization’s creativity?

• Is there a common definition and understanding in your company about what is meant by an idea?

• Is the passion of your software engineers aligned with your organization’s goals?

• Do the people in your organizations know how to build on each other’s ideas and debate constructively? Are there opportunities for that? Are there tools to support this collaboration?

• Do your employees have good communication/creativity skills? If not, do you have any training initiative to improve this?

• Are different skills, knowledge and backgrounds represented in your innovation teams?

• What motivates people in your company to innovate?

• Which creativity techniques are used regularly in your organization?

• Would your organization benefit from setting up an internal innovation challenge or an open innovation competition?

• How do you obtain feedback from customers or potential users?

• Are your company and its people well positioned in external networks?

• Is your organization ready to start to work on ideas or new solutions that come from outside the company?

2.10 Jose Antonio Heredia and Minna Pikkarainen

2.10.1 Introduction and Scope

Imagine that you are the CEO of a software company. You launched a product successfully a while ago, released version after version, and gradually captured more market share. Still you do not feel comfortable: new, unexpected players emerge on the market, sometimes with unconventional solutions or business models. They undermine your position and eat away your top line. You realize that your current way of innovating (incrementally producing release after release) will never yield drastic or radical innovations. The art of innovation incubation comes down to this: how can I organize my company so that there is room to go beyond incremental innovation?

Innovation is a series of activities from new idea to new product design, manufacture and marketing (Hui and Wang 2006). Based on the innovative activities, the innovation can be divided into incremental and radical innovation (Hui and Wang 2006). Incremental innovations are progressive and continuous innovations that are caused by the improvement of the existing products or services (Hui and Wang 2006).

For many software companies, the word “innovation” often means adding new features to the product. Some techniques such as total quality management (TQM) principles, lean manufacturing techniques or six sigma techniques provide a basis to manage the incremental innovations (Dismukes, et al. 2009 ). Although, software companies are typically good at managing incremental innovations, these incremental feature additions to the existing products do not always help a software company to create growth or move into the new markets. According to Dismukes et al. (2009) “focus on incremental innovation will be less effective and potentially counterproductive in the twenty-first century environment”.

Radical innovations are fundamentally different to incremental innovations (Hui and Wang 2006). Therefore, it is not surprising that for many software companies it is quite a new game to manage radical breakthrough innovations that will launch the company into new markets and enable rapid growth or a high return on investment. As a consequence, many software companies are now forced to leave their comfort zone of incremental innovation in search of more radical innovations.

Anyone who has purchased a cell phone in the past few years can see how quickly new types of phones are launched on the market (Chesbrough 2006b). However, radical changes to cell phones (e.g. invention of the phone itself) happen only very occasionally. Typically, radical innovations are linked to the entry into new and emerging markets and the adoption of new technologies. In fact, for new industry, radical innovations are often the gateway to new successful markets. (Hui and Wang 2006).

Historically, radical innovations emerged rarely and took decades to reach the market (Dismukes et al. 2009). Nowadays, however, the possibility of using software technologies, more rapid telecommunication, and the open innovation environment (see The Art of Openness practice area) have significantly increased the commercialization time of radical innovations (Dismukes et al. 2009). The faster time to market of radical innovations has also increased the need of software companies to establish more systematic ways of managing radical innovations (Tellis et al. 2009). In this new situation, the companies simply cannot simply rely on incremental innovations. Sometimes a company only needs one successful radical innovation to guarantee a leading position in the market (Kim and Mauborgne 2005). After a long period of incremental innovation, we have seen software companies investing a large amount of money in incubating radical innovations. Sometimes these large-scale initiatives are successful, but too often they fail, causing the company loss in terms of their investments. The reason for the situation is that either the emerging ideas are poorly conceived or the projects are not properly managed (Tucker 2008).

In some studies, ‘incubation project’ refers to those projects that were novel for the company and required significant investments from critical experts (Leifer 1998). In the context of this chapter, we will use the term incubation to refer to the process of realizing radical innovations. We refer to an Incubation project as a project in which a radical idea is turned into a profitable business solution.

An incubation project can give several outputs for a company. In reality it may be a new product or service, a new product line or even a new spin-off company. Incubation projects are typically characterized as projects that begin with a high-level technological uncertainty and risks. While working with software companies, we have observed that the typical deployment of an incubation project requires many organizational changes and some increase in the company competences:

• Incubation projects require a different organization: If they are not incorporated into a distinct organization or venture, incubation projects have to fight for internal funds on the same terms as other incremental investments in the core business. As maintenance of the actual business is often seen as critical to survival, incubation projects may only receive marginal funds.

• Incubation projects require different skills: Companies may have to look for different skills that are not available inside the company. In the case of incubation projects that involve the adoption of new technology, particular technological skills need to be acquired. In the case of an incubation project, attempts to enter a new market and find the necessary entrepreneurial competence for the new endeavour may be a challenge.

• Finding the right window of opportunity: It is important that the incubation project is launched at the right time and in the right market segment. If the radical innovation enters the market too early, it may be difficult to find other complementary players to support the innovation development. If the radical innovation enters the market too late, there is a risk of losing the opportunity because the market has already been taken by the competitors (Kim and Mauborgne 2005).

• Incubation projects require networking competence: Internal and external networking is critical to the success of an incubation project (Chesbrough 2006b). Internal networking is necessary to ensure that the radical idea is communicated appropriately. External networking permits access to complementary resources but requires careful management (see the Art of Openness practice area, Sect. 2.6, in this book).

For software companies, it is therefore important to understand which management practices they should apply to incubation projects. How can these initiatives be made shorter, less expensive and less uncertain?

2.10.2 Activities of Radical Innovation Incubation

There are several ways of carrying out incubation projects depending on the target markets and the radical idea itself. According to our observations, however, the incubation projects needs to be addressed with the following activities:

• 1. Radical idea opportunity spotting

• 2. Experimenting

• 3. Uncertainty management

• 4. Business model design

• 5. Venturing

• 6. Incubation climate and environment building.

In the following sections, the Art of Innovation Incubation steps are explained further (Fig. 2.18).

Fig. 2.18

The art of innovation incubation and activities involved

2.10.2.1 Radical Idea and Opportunity Spotting

It is mentioned in the Art of Idea Harvesting practice area (see Sect. 2.4) that the amount of radical innovations do not necessary correlate with the general amount of produced ideas because the probability of ending up with radical ideas does not usually increase with the quantity. Radical ideas can also merge as part of the idea capturing process. It is important for software companies to be able to separate radical ideas from incremental ideas.

Radical breakthrough innovation assessment is a method of evaluating if your idea is radical or not. With a brief look to the literature, we can find few examples concerning radical breakthrough innovation assessments. For example, a company called General Electric developed a light bulb guided by effective technological and cost assessment (Dismukes et al. 2009). Setting of assessment criteria is important for the companies to understand if an idea is radical or not. Often these criteria are company-specific but related either to the new markets or to technologies.

• Market-related criteria: Are your competitors doing similar things? Is your idea addressing a completely new market?

• Technology-related criteria: The radicalness may be based on the technical content and the ways in which an invention’s technological content differs from the already existing technological state of the art (Dahlin and Behrens 2005).

2.10.2.2 Uncertainty Management

Incubation projects have a high degree of uncertainty, from the technical as well as the marketing side.

2.10.2.2.1 Uncertainty Related to Market Transformation

Compared to incremental innovation, radical innovations demand more expensive and time-consuming market studies. Moving to a new market can be difficult. When marketing a radical innovation, it is impossible to predict which will be the successful market segment in the future (Leifer 1998). Each market segment is different and requires separate analysis of the customer and user values and needs in the specific market sector.

There are two sources of great uncertainty related to the market transformation. Firstly, companies lack the necessary knowledge for moving to the new market segment. Secondly, they lack communities of key players and customers in the new market sector.

“For example, moving from the telecommunication sector to the automotive field demands a huge amount of knowledge about the safety standards and key car manufacturers in the automotive field.”

2.10.2.2.2 Uncertainty Caused by New Technology Adoption

In incubation projects, some of the critical and central technologies may be new or need to be developed during the incubation project itself. It is uncertain whether the technology idea will work, whether the technology itself can work, or whether there is a product market based on the particular technology.

Most incubation projects require a flexible management style (e.g., agile), due to the uncertain nature of the technologies. Another way of dealing with uncertainty is experimentation, as it is a core instrument for understanding risks caused by launching radical innovations. Experimentation can be used as a way of reducing market risks by checking if the developments are aligned with the market (i.e., potential users’) needs and expectations.

Product development involves thousands of decisions. In incubation projects, in particular, the decision-making process needs to be managed explicitly. For example, Leifer (1998) argues that decision-making is more difficult in the early phases of radical innovation than in the corresponding phases of incremental innovation: “decision making is associated with uncertainty and ambiguity in the context and situation requiring decisions” (Leifer 1998 ). The uncertainty is caused by a situation in which it is difficult to ascertain whether the technology will work and which are the customer segments. Ideally, decisions should be delayed until the very last moment in order to maintain flexibility as long as possible and have all available information on which to base the decision.

2.10.2.3 Experimenting

Pursuit of knowledge is the rationale behind experimentation, and all experiments yield information that comes from understanding what does and does not work. For centuries, researchers have relied on systematic experimentation, guided by their insight and intuition, as an instrumental source of new information and advancement of knowledge. Nevertheless, experimentation has often been expensive in terms of the critical expert’s time involved, even if it has been essential for innovation (Thomke 2003).

Effective experimentation should not be a random walk of trial and error. There should be integrity in experimentation that needs to be understood. At the same time, experimentation trials need to be coordinated with the objectives of the enterprise and integrated into the overall innovation process.

In software companies, different kinds of experiments can be envisioned:

• Experiments to test new technologies

• Experiments to evaluate a new product concept

• Experiments to understand the product market fit (Blank 2006)

• Stress testing: overloading a machine to see what breaks [note. You also do stress testing when doing incremental innovations as a footnote]

A common way of experimenting in software companies is to build fast and sometimes small-scale prototypes (Thomke 2003). A prototype is a version of a product with reduced features and limited functionality for the purpose of validating key concepts. Typically, prototypes are built to understand the constraints of the radical innovation idea. They enable faster time to market and lower development expenses. Depending on the type of company and the new product, techniques for developing the prototypes may vary (Thomke 2003). Examples of the different types of prototyping techniques are Mock-ups, Beta testing (Neff and Stark 2002), perpetual beta, Living Lab (Følstad 2008), A/B testing,¹⁶ lead users (von Hippel 1986) and pilots. Early prototypes can be as simple as sketches of screens, storyboards or slide presentations. These can usually be made quickly. More mature prototypes include html mock-ups, mash-ups and patchwork prototypes (Thomke 2003).

Approximately 80% of software features are rarely or never used (Hibbs and Sullivan 2009). One way to solve this problem of unused features is to increase the involvement of users in software product development, which is why many software companies organize experiments in which they involve their customer base.

Google Inc., for example, nowadays runs 50 –200 software experiments at any given time. In one case, Google asked selected users how many search results they would like to see on a single screen. ‘More’, said the users, ‘many more’. So, Google ran an experiment that tripled the number of search results per screen to 30. The company found that traffic declined. What happened? On average, it took about a third of a second longer for the search results to appear – a seemingly insignificant delay, but one that nonetheless upset many of the users. The greater number of results also made it more likely that a user would click on a page that did not have the information he or she was seeking.

For experimentation to be a reliable and effective element of company decision-making, companies need to create an infrastructure for making it happen. They need training programmes to sharpen competences, software to structure and analyse the tests, a means of capturing learning (Thomke 2003), a process for deciding when to repeat tests, and a central organization to provide expert support to all of the above.

For instance, Living Labs are environments for innovation and development in which users are exposed to new ICT solutions in (semi-)realistic contexts (Følstad 2008). A Living Lab is about experimentation and co-creation with real users in real life environments in which users, together with researchers, firms and public institutions, look for new solutions, new products, new services or new business models.

For example, the Finnish telecom giant has created a lead user community called Nokia Beta Labs that has been given the opportunity to pre-test and give feedback on new products and services that have not been launched on the public market and are still under development. This not only provides Nokia with critical and valuable information on new offerings that are developed but also strengthens its customer relationship with those customers who are qualified to become part of the community.

As more people become involved in experimentation, companies will need to change their focus on education and training efforts for innovation. Instead of merely getting workers to interpret large volumes of data creatively, companies will need to help them develop the skills to design rapidly and provocatively.

2.10.2.4 Venturing

Venturing is the process of creating and evolving a venture. The term venture is often used to refer to a risky start-up or enterprise company. Ventures can range from internal corporate ventures through joint ventures to spin-offs (Burgelman 1984). Corporate ventures are more appropriate when organizations need to exploit internal competence while retaining control over the business. Joint ventures and alliances involve working with external partners and therefore imply autonomy.

A spin-off of a new business is convenient when there is little relatedness between the core competences of the organization in which the idea originated and the new venture (Tidd and Bessant 2009). One type of venture that is often used by software companies is a community venture. In this situation, multiple software organizations create a community together and bring innovation to the market as an ecosystem. Innovation ecosystems take many forms. Instead of using the closed innovation approach, the companies in the innovation ecosystems search inside and outside the company to find the best resources and business models. Knowledge shared inside the community ventures can be significant especially for new start-up companies and spin-offs (Stuer et al. 2008).

The open source movement is a specific way of launching ventures in the software development field. Most software innovations seem to occur in a social context. In Denning’s (2004) words, software innovation has a “social life”. An example is the Apache Software Foundation¹⁷ with its suite of products for software developers and administrators. In this community, the developers are also expert users with a strong need for new product features to manage their own work lives.

Some examples of the open source movement, successful communities such as GNO,¹⁸ Mozilla¹⁹ and Eclipse foundation,²⁰ have a significant impact on innovation. For example, Eclipse is an industrially driven community involving more than 100 companies, universities and contributors. Many of these communities follow various incubation processes. In the first phase, the sponsor evaluates the proposals which are either accepted or rejected. In the second phase the actual incubator checks the project status. At this stage the project is rejected, continued or engaged with other projects. Both proposal evaluation and project status checking can be seen as an entry point to the idea valuation.

2.10.2.5 Business Model Design

A business model is a translation of the strategic issues, such as strategic positioning and strategic goals, of the company into a conceptual model that states explicitly how the new business functions. The business model serves as a building plan that allows the business structure and systems that constitute the company’s operational form to be designed and realized. Business model implementation and management include the ‘translation’ of the business model as a plan into more concrete elements such as an organization (e.g., departments, units, teams), business processes (e.g., workflows, responsibilities) and infrastructure and systems (e.g., rooms, hardware) (Brews and Tucci 2003). Furthermore, the implementation of the business model must be financed through internal or external funding (e.g., venture capital, cash flow).

A business model describes how a company creates, delivers and captures value. Osterwalder’s Business Model Canvas (Osterwalder 2010) is a useful strategic management tool that allows the development and adaptation of business models to changes in the business environment. The Business Model Canvas is divided into nine building blocks that together outline the business model elements of the company’s business:

• Key Activities

• Key Resources

• Partner Network

• Value Proposition

• Customer Segments

• Delivery Channels

• Customer Relationship

• Cost Structure

• Revenue Streams

Recently, business model design has moved from traditional business model creation to identification of different business model innovation opportunities (Loebbecke and Soehnel 2010). One example of an innovation that provides an opportunity to design new business models is eBooks. In general, there are several players along the value chain of the eBook business. For instance (Loebbecke and Soehnel 2010):

• “Authors are willing to adopt eBooks and the possibilities of self-publishing when they benefit from increasing revenue shares and audience sizes”

• “Traditional publishers receive economic benefits from ePublishing, as manufacturing costs decrease due to the digital delivery and elimination of the printing process”

• “Consumers can enjoy a recognizable look and feel as reading an eBook has become almost as comfortable as reading a traditional book.”

Amazon differentiated themselves from their competitors by utilizing the new business model innovation integrated with a new technology solution. They created a Kindle Shop containing more than 4,00,000 eBooks. Books can be downloaded free using a Whispernet mobile data connection. Users are more likely to make impulse purchase decisions using the mobile device (Loebbecke and Soehnel 2010).

2.10.2.6 Incubation Climate and Environment Building

Companies need a great deal of information before they can make decisions about radical innovations. In incubation projects with high uncertainty, the requirements may often change once development has started.

Three broad strategies exist for increasing development flexibility: adopting flexible technologies, increasing management flexibility and exploiting product architecture as a tool to increase development flexibility. One way to manage uncertainty is to reassess the requirements and design uncertainties after each milestone, development cycle or sprint.

Example: In the Internet-software industry, a common practice is to build a low-functionality version of the product, put it into customers’ hands at the earliest possible stage and adopt an iterative approach to adding functionality. It illustrates the importance of having a development team with experience of multiple projects and implies the creation of a product architecture that facilitates flexibility.

A good practice in incubation projects is to allocate contingent resources or buffers to respond to unexpected difficulties and delays (Loch et al. 2006). This allocation could even be as much as 50% in projects with high uncertainty (Shenhar and Dvir 2007). Oliveira (2009) conceptualized a project as a process whose goal is to reduce uncertainty. Ideally, it should start by addressing market uncertainty, for example, clarifying customer requirements. The process of learning customers’ needs and acquiring the necessary technological capabilities gradually turns incubation projects with high uncertainties into projects with lower uncertainty levels.

One problem with radical innovations is that typically the breakthrough does not produce return of investment until years later. To support the funding of incubation projects, software companies can tap into the many funding opportunities that support radical innovations in the domain of software engineering. Examples of such European research programmes that support incubation projects in software companies are ITEA 2,²¹ Artemis,²² FP7,²³ Medea,²⁴ Eniac²⁵ and Celtic²⁶.

2.10.3 Links to Other Practice Areas

There is a link between the following practice areas:

• The Art of Idea Harvesting

• The Art of Idea Valuation

• The Art of Openness

• The Art of Innovation Stimulation

• The Art of Optimizing the Impact of Critical Experts

• The Art of Idea Harvesting

  The art of incubation has an impact on the Art of Idea Harvesting practice area. Radical innovations can be collected and stored in the same way as with incremental ideas, but their origin and identifier are likely to be different.

• The Art of Idea Valuation

  Valuating radical ideas can be even more challenging than valuating incremental ideas. This is because decision-making difficulty is associated with an increase in the degree of uncertainty and ambiguity in the decision- making context. Decision about radical idea launching can change the whole future of the software company.

• The Art of Openness

  The Art of Openness practice area provides companies with activities for enhancing competitiveness using external knowledge. In the case of radical innovation the utilizing of external experts is often even more important than in the case of incremental innovation. Thus, being successful with incubation can require some of the activities in the Art of Openness practice area to be addressed.

• The Art of Innovation Stimulation

  Innovation stimulation is an important way of supporting company innovativeness, increase the opportunities of the companies for radical innovation creation. Incubation projects need to be stimulated in a particular way. Insights can found in the chapter on the Art of Innovation Stimulation.

• The Art of Optimizing the Impact of Critical Experts

  In the case of radical innovation, the companies need an ability to reconfigure resources to match to the needs of the new situations. Each radical innovation is different. Each time when the radical innovation are valuated, there is need for the different competences from inside and outside of the software company.

2.10.4 Questions

• What does radical innovation mean to your company?

• What does incubation mean to your company?

• How do radical innovations differ from incremental innovations?

• How do you manage incubation projects today?

• How do you deal with risk today?

• How do you manage uncertainty?

• What could venturing mean in your context?

2.11 The Software Innovation Canvas

Minna Pikkarainen, Wim Codenie, and Leire Orue-Echevarria

At this point in the book, we have explored the eight practice areas. Together, they introduce 47 practices for software innovation. The Software Innovation Canvas consolidates this in a single drawing (see Fig. 2.19). The canvas provides an overview of the activities that you, as a software company, can consider to innovate in your software. You can use the canvas as a kind of compass to help you to find the right direction for your journey towards improved software innovation.

Fig. 2.19

The software innovation canvas

As a company, software companies can use this canvas several ways. For example, software companies that are highly engineering-driven today can use the canvas to explore how to become more innovation-driven. Non-software companies that consider including software in their product offering can use the canvas to explore the various innovation opportunities that software can offer.

Perhaps the most important use of the canvas is as an instrument for innovation improvement. In several of the industrial cases described in this book, the innovation canvas was used to improve the innovation capabilities of software companies. For example, in Metso (sect. 3.6), VTT coached several innovation improvement projects.

In software process improvement literature, deployment paradigms such as QIP (Basili 1989), and IDEAL (McFeeley 1996) have been widely used to support improvement actions in software engineering. It was noticed,while working with companies, that innovation improvement involves the five key steps that have similarities with the traditional software process improvement approaches. The steps are as follows:

• Step 1: Set goals and choose practice areas for your improvement activities. Metso had two innovation targets. The first target was to make the customer idea management even more efficient and provide quicker responses to customer requests and wishes. The second target was to find more systematic ways to manage innovation in the software context by defining and deploying a new software tool to support identified innovation actions and improvements. Based on these targets, three practice areas were selected as a focus for the innovation improvement activities: the art of idea harvesting (sect. 2.4), the art of valuation (sect. 2.5) and the art of openness (sect. 2.6), as the goal of the study was to look at the customer communication aspect of idea harvesting and valuation.

• Step 2: Understand how you are going to deal with the activities today (as-is). At Metso, VTT’s staff carried out nine interviews aimed at company sales, marketing and product management. For the interviews, a set of questions related to the art of idea harvesting, valuation and openness were adapted to be better suited to Metso context. Remove:, was used. To help you as a company define your own questions we provide a set of questions at the end of each practice area that you can use as inspiration.

• Step 3: List the challenges you currently experience in the area of this activity. At Metso, VTT researchers recorded all the interviews, analysed them and summarized the results in a presentation that was later shown to the company’s sales, marketing and management. Examples of the challenges in the analysis are listed below:

  • The marketing and customer support staff do not use the innovation tool (the potential of customers is not made full use of when making business plans and roadmaps).

  • No feedback on ideas, and the innovativeness/motivation of the creativity of the actors is disappearing.

  • Ideas and customer demands are sometimes documented vaguely (not focused), making the analysis difficult.

  • Idea evaluation and prioritization are time-consuming due to the lack of collaboration.

• Step 4: Examine the improvement needs in your company in terms of these activities. This book provides 21 industrial cases about software innovation (sect. 3). The cases are provided to help software companies to define innovation improvements / targets. In Metso case, VTT researchers used some cases presented in this book as inspiration for the improvements identification. For example, the Steria case (Steria, ‘Focusing Innovation in a Large ICT Company’) was used as an inspiration to organize a workshop in which the innovation targets were defined for the selected Metso programme. In addition, some experiences from the Mobideas case (‘Mobideas – Co-creating B2C software together with end-users’) were used to identify ideas on how to improve innovation openness. While your company situation will undoubtedly differ from that faced by the companies in our experience reports, some aspects of their experiences are likely to be relevant to your context.

• Step 5: Prioritize and plan. In the Metso case, a workshop was organized on software innovation challenges and improvements during the workshop. VTT researchers presented the results of the key innovation challenges and needs and collected feedback from Metso’s sales, marketing and management. At the same meeting, the marketing, sales and management at Metso had the opportunity to vote on the priorities of the innovation ideas and improvement needs in the area of software innovation. More information on the results of the case can be found from the section 3.6 ‘Harvesting product ideas as part of a global innovation process’ in this book.

The canvas is not only useful to industry; it may also be relevant to the research community. The innovation canvas and experience reports can be used as inspiration to start new research initiatives in the domain of software innovation. The practice areas and activities from the canvas can be investigated from the research perspective: What does this activity mean from a research perspective? The experience reports introduced in the following chapter can provide support to find some new practical angles for research in the domain of software innovation.

The research on software innovation is still relatively new, which means that all aspects of software innovation may not yet be addressed in this canvas. In fact, we may have missed some activities or even practice areas. If you as a representative of a software company have any ideas on how to develop this further or if your research or practice generates new software innovation angles, please feel free to discuss it with us and others in the SinnoBok.Org community.