1 Introduction

By exploiting the niches and offering novel products and services, enterprising individuals with economic initiatives may create the resource for further employment. Hence the entrepreneurship and innovative activities is perceived to be a key factor in economic development [1]. However, the failure risks of start-ups are high and among the indicated reasons are the lack of realism in business ideas [2], i.e. not enough examination of end user needs, which are prone to change rapidly and neglect of the real world context. The lack of realism when modelling business ideas needs to be tackled by the enterprise modelling community. One way to bridge this gap could be the application of a modelling method that allows an integral view and supports different business perspectives, such as the needs of the entrepreneurs and end users, the sequence of activities to be followed to fulfil the needs, as well as the contextual factors influencing the procedures.

Recently, modelling and management of capabilities have been proposed as a way to cope with the challenges in dynamic environments. In that respect, a EU-FP7 project Capability as a Service in Digital Enterprises (CaaS) addresses methods and approaches with which the organisations may adapt to the changes and secure a competitive advantage [3]. To enable digital enterprises to sense and take advantage of changes in business context, CaaS engineers the Capability Driven Development (CDD) method. The CDD has been applied in various case studies for the evolution of information systems that need to incorporate context aware capabilities. Osterwalder & Pigneur states that “a business model describes the rationale of how an organisation creates, delivers and captures value” [4]. By adopting this definition, organisations are start-ups. Concerning the value creation part, we focus on the specification of business processes, goals, business capabilities, and contextual constraints for venues. In this paper we present the application of CDD for helping entrepreneurs in the analysis, design and specification of start-ups. We explore CDD as a business tool that can complement current suites of business tools like the ones proposed in [4].

To shape our research, we conduct a design science project [5]. We perform the first iteration of a design cycle from the problem investigation to the design validation (see Fig. 1). The first step is the problem investigation, which investigates the lack of modelling methods as a threat of start-ups shutdown. The second step corresponds to the treatment design, in which an exploratory exercise to apply CDD for entrepreneurship is performed. The third step corresponds to the treatment validation, which applies the CDD to two case studies of start-ups. Following the results, a reprise of the treatment design step is performed by creating LightCDD.

Fig. 1.
figure 1

Overview of the research methodology

The paper explores of the suitability of the CDD for start-ups, i.e. whether it helps the entrepreneurs to reason on their business ideas and design. For this, we report on the application of the CDD in two exploratory case studies of start-ups, present the results of a survey regarding the method support for start-ups and then present the LightCDD, which is a simplified version of CDD aimed at the enterprise modelling activities of start-ups. The paper is structured as follows. Section 2 discusses the main threats on start-up failures, outlines the related work, and presents the performed survey. Section 3 begins with the background information on the CDD paradigm, details its application in two case studies, and reports from the experiences gained during the application of CDD in practice, which motivates the LightCDD. Section 4 introduces the LightCDD and Sect. 5 concludes the work.

2 Problem Investigation

The problem investigation is centred on the research about the lack of realism and the risks of not considering contextual and operative constraints for start-ups. We performed a literature review to investigate about the reasons of start-ups’ failure. Also, we conducted a structured interview to investigate start-up failure reasons from the point of view of counsellors or managers of start-ups incubators.

Studies and analysis show that encouraging the entrepreneurship and innovative activities in small businesses is a key factor in economic development [6]. By exploiting the niches and offering novel products/services, enterprising individuals with economic initiatives sustain high level of profitability, which may create the resource for further employment [7]. Based on this fact, the legislative bodies support the entrepreneurs to set up their own companies and consequently, the number of start–ups raise rapidly worldwide. However, the high start-up birth rates go hand in hand with a great risk of failure, it’s estimated that nine out of 10 start-ups fail [8]. As stated in [9] “the failure often surrounds five key dimensions: customers, business model, product, financials and team”. Chorev & Anderson identify 8 top key topics and reports that team commitment, team expertise, marketing, customer relationships, core team expertise and management, strategy, R&D and idea have high effect factors on start-ups success [10].

Among the various factors leading to the start-up failures, wrong estimations on the market need is one of the most important cause. Many start-ups focus too much on product, and not enough on examining the needs of the end user, which is prone to change rapidly. Another observed cause for failure is that the entrepreneurs underestimate the importance of planning, before entering the market [11]. Hence, due to the lack of realism in business ideas, many start–ups fail. To be more specific, different scenarios are neglected; the activities are captured in a single high-level process and the processes are not specified. Moreover, the objectives motivating the ideas and wishes are not captured, which should help to find a proper solution. Instead, the entrepreneurs rely on the subjective, and often biased, perceptions when creating a new business [12]. As such, business planning may help as a decisive factor for the success of the start-ups.

We have asked two experts in enterprise incubation to answer our questions on the reasons for start-up failureFootnote 1. The respondents were the manager of a start-up school (pre-accelerator), and the manager of an incubator who is also lecturer of a course named ICT Entrepreneurship. Both managers have from 3–10 years of experience running incubators. We now elaborate on the findings.

To conclude, we found various evidences on the need to provide lightweight and integrative modelling supports for start-ups. In the following sections we explore the applicability of CDD for entrepreneurship support and start-up modelling.

3 First Experiences on Applying CDD for Enterprise Development

3.1 Capability as a Service in a Nutshell

CaaS project aims to create an integrated approach consisting of a method, tools, and best practices that enable digital enterprises to sense and take advantage of changes in business context. The CaaS methodology for capability- driven development (CDD) consists of various components addressing different modelling aspects, such as context modelling, business process modelling, pattern modelling, and adjustments modelling. The method is supported by the CDD environment, which comprises of a Capability Design Tool (CDT) incorporating a context modelling module, a Capability Context Platform (CCP) to monitor the contextual values at run-time as well as a Capability Delivery Navigation Application (CNA), which enables adjustments in line with the service delivery context and reusable best practices [3].

Three use cases in the sectors of e-government [3], energy [13] and insurance [14] prove that the methodology is successful when applied to full-fledged enterprises that intend to become more context-aware and adaptive. However, studies on the application of the CDD and its effects in innovative start-up projects in entrepreneurial settings are missing.

3.2 Two Practical Start-up Cases

Digital technology powered by the growth in the digital economy caused an increase in the number of young entrepreneurs and innovative ideas. This specifically can be observed between the two main sectors, namely telecommunications and IT [7]. We have launched the yes!PoEMFootnote 2 seminar for entrepreneurs, in which the DELITELABSFootnote 3 start-up school has participated. This section focuses on the two innovative start-ups in IT field for which we apply the CDD paradigmFootnote 4:

3.3 Applying the CDD in Full

The CDD supports different entry points and offers three strategies for capability modelling, namely goal-based, process-based, and concept-based approaches [15]. The procedure that describes the application of CDD to the two cases (case 1: Let’s Get Better and case 2: UpLite) is depicted in Fig. 2.

Fig. 2.
figure 2

CDD application procedure for the two start-up cases

Before starting the modelling sessions, the authors explained the teams the CDD concepts in detail, i.e. the terms business processes, context, and capability were defined. After that, both the Let´s Get Better team and the UpLite team were asked to provide us with the business processes (see Procedure 2 in Fig. 2). The results were generic and did not quite reflect the actual implementation of their business ideas.

CDD allows for different strategies when modelling capabilities [15]. To select the right strategy, we analysed the qualitative data provided by the entrepreneurs (see Procedure 3 in Fig. 2). The data included the descriptions of the use cases as well as the explanations of additional concepts, key activities, resources and stakeholders. Following that, we meet with the teams in an interactive group setting. Based on the gathered information, we identified that the goals were not reflected at all or only expressed ambiguously. Regarding the organizational structures, both teams had clearly defined roles and responsibilities. However, in terms of key concepts, the teams lacked a shared understanding, thus further work was needed to clarify such concepts. In this respect, the teams received an additional task to create a glossary of terms before starting with the capability modelling sessions. In contrast, we identified that in both use cases the teams possessed knowledge on the key activities. Consequently, the process-first capability design strategy seemed to be the most suitable one.

Using the CDD method, first the business process models were updatedFootnote 5. In the next step, we identified the core capabilities and together with the teams, we prioritized them and selected one capability per use case. Following that, the goals of the team alongside with the end user needs are analysed and modelled, these are related to the capability and to the business process models. Finally, based on the gathered information, the contextual factors that might effecting the service provision were explicated and modelled. In each iteration, additional context elements were identified and their effect on the business idea were discussed. The results were used as an input for a new interaction with the entrepreneurs, i.e. the steps regarding the modelling of the business processes and goals were revisited (see Procedure 9 in Fig. 2).

3.4 Lessons Learnt, Experiences

Looking back at the success factors as introduced in Sect. 2, the application of the CDD led to a more committed team with a shared understanding and clearly defined objectives. In particular, the modelling activities enhanced the communication between the core team. The developed models contributed to an overview of the core product & service and how to offer it, the management had useful instruments to define their strategy. Moreover, goal models reflected not only the objectives of the start-ups, but also of the potential customers, which is expected to improve the customer relationships, probably opening new marketing channels. The whole CDD practice helped to enrich the business idea and minimize the risk of a false start.

Concerning the causes of the failure, the CDD improved the start-ups in the identification of the real world factors in the business. To exemplify, the UpLite team did not consider the context of the user in different scenarios, so their app did not incorporate the required functionalities, such as the user profiles, willingness to share, ratings from other users, distance to energy providers and battery status. For the Let´s Get Better Team, the capability model provided them with the information they needed to start developing an algorithm for the app, which was not considered before.

In line with the findings from the literature, another important failure factor was that the entrepreneurs tend to form simple processes. In both cases, the procedures were vaguely defined and many gateways were not considered explicitly. After applying the CDD, the core business process models are updated. Each meeting with the entrepreneurs resulted in a more matured process model and addressed additional discussion points for the teams in terms of a concrete implementation of the activities.

We interviewed the CEOs of the two cases that have applied CDD. Both of them did not have previous experience with enterprise modelling before the application of the CDD. Below we present the research questions that stand for the structure of the interview, and the insights providing answers to the research questions:

figure c

In general, CDD helped them to find out further configurations of their products and services by analysing their business ideas from the capability point of view. The entrepreneurs identified gaps in the distribution and revenue models, which were optimized (cf. RQ2). Nevertheless, applying the CDD in full had a few drawbacks. First, the entrepreneurs were initially unsure on how to apply CDD to their projects, which is mainly related to the number of method components. The CDD focuses on the application scenarios of mature enterprises that intend to become context-aware and adaptive, which necessarily requires engineering of a comprehensive method with a number of components. For the two cases, the CDD was not applied in full and just some method components were selected for their application. Second, the method terminology was rather confusing for them and needed review. The teams were not able to apply the CDD by themselves, which created a complicated CDD application procedure, the intervention of the researchers to the modelling processes was required, and the created models are analysed with the entrepreneurs (cf. Fig. 2). To overcome these drawbacks, we propose the LightCDD, which balances the trade-off between the simplicity and expressiveness.

4 Light CDD for Enterprise Modelling of Start-Ups

As a result of the application of CDD in two start-up projects, we found that it is feasible to apply CDD for start-ups projects. As we presented in Sect. 2, all respondents of the questionnaire agree that the entrepreneurs are more focused in the design than in the analysis during the development process of their ventures; and this lack of proportion is a cause of failure. Thus, methods to analyse their idea should be provided to the entrepreneurs. Regarding the characteristics of such methods, they should support graphical representation of the business idea, be lightweight and simple. Moreover, it is required to provide mechanisms to represent contextual constraints that help entrepreneurs anticipate and mitigate risks of failure, and provide integrative view of goals, activities, and contextual constraints.

Taking into account the interview responses (cf. Sect. 3.4), we propose the LightCDD, which is a simplified version of CDD with a different purpose, i.e. not providing support in a full-fledged company, but rather in a start-up design. To meet the demands of the start-ups, the LightCDD incorporates the context modelling, goal modelling and business process modelling components. The important concepts that the LightCDD is based on are illustrated with a meta-model in Fig. 3. This is a simplification of the meta-model used in the CaaS project [3].

Fig. 3.
figure 3

The meta-model of the LightCDD

LightCDD consists of procedures that are classified into three phases, namely preparation, analysis and design phases, which are defined in the following (Fig. 4):

Fig. 4.
figure 4

LightCDD procedure

Preparation phase

The entrepreneurs are provided with a LightCDD guide. The guide consists of the information, what enterprise modelling in general is, and how this could help to improve their case. Moreover, it includes the meta-model (cf. Fig. 2), the definitions of the CDD terms in a tabular form as well as a simple example, where the method is used.

Analysis phase

The core proposition of the business idea is expressed as a capability. Then, key activities regarding the implementation of the capability are enumerated. Next, the goals are listed that needs to be fulfilled. Following that, the contextual factors influencing the objectives or the key activities are analysed. The gained information might require an update in the core proposition of the capability or result in additional capabilities, which is why the analysis phase may be iterated more than once.

Design phase

The key activities are modelled as BPM and objectives are captured as goal models. The key performance indicators (KPI) are added to the goals. Based on the capabilities, the BPM and goal models are related to the context models, which represent the contextual constraints of the business environment.

The prerequisites for the method application are not taken into consideration. This should be fulfilled with the activities in the preparation phase. Likewise, the stakeholder types that participate to the different phases of the CDD were excluded in this version, due to the fact that the start-up teams include smaller number of individuals. As mentioned in Sect. 3, the CDD is supported by a number of tools including the CDT, CCP and CNA. For the LightCDD, the focus is on the enterprise modelling phase, hence the CDT is required for the method application, which is a graphical modelling tool for supporting the creation of models according to the simplified meta-model shown in Fig. 2.

5 Conclusions and Discussion

Studies and analysis show that the digital economy is growing worldwide and holds huge potential for European entrepreneurs. Encouraging the entrepreneurship and innovative activities in small businesses is a key factor in economic development [6]. However, the high start-up birth rates go hand in hand with a great risk of failure.

In this paper, we analysed the current problems of start-ups and focused on the lack of properly modelling methods as a threat for shutdowns. In other words, we investigated how methods and techniques for enterprise modelling could help on the development process of new ventures. We reviewed the literature and conducted a survey to know factors of failure when establishing start-ups. We have performed an exploratory application of CDD in two start-ups projects. As a result of this experience, we found that CDD is a feasible method for start-ups support. We interviewed the CEO of the two start-up projects to know their perceptions about CDD, and how it impacted their projects. Thanks to the evidences collected during the application of CDD, the survey, the interview to the CEOs, and literature related research; we found evidences on the need to design a lightweight method for start-ups. As a result, we proposed the LightCDD, a simplified version of CDD for entrepreneurship support, which is designed based on the following principles:

  1. i.

    The users of LightCDD should be supplied with the information of what enterprise modelling in general is and how this could help to improve their case. Here, the specific terms regarding the capability modelling should be described. If possible, the description should be enriched with the examples from the cases.

  2. ii.

    The LightCDD should focus on the goals, context and processes. The pattern modelling method component is excluded, since the business idea is somewhat unique and no best practices in the application field are expected. The adjustments modelling method component is also excluded due to its strong focus on the implementation of the business idea, which is the run-time aspect.

  3. iii.

    From the CDD tool suite, CDT seems to be the only one that the entrepreneurs can use. This is advocated by the reason that for the business design, they only need CDD tools that support enterprise modelling.

We gained interesting feedback from the CEOs of the two projects in which CDD was applied, and the incubators’ managers. Due to entrepreneurs’ context sensitive approach, we predict that the respondents address the ability of CDD to overcome challenges in changing situations, i.e. if it is a relatively stable environment for the start-up, such as selling of a certain product with certain features, the method might be too complex to use.

LightCDD is going to be further developed and evaluated in new start-ups. In this respect, future work is going to focus on a few aspects. First, the guidelines and best practices for BPM are going to be improved and incorporated. This requirement stems from the feedback that the application of the (Light) CDD in further entrepreneurial projects depends on such support. Second, the CDD concepts are going to be refined and simplified. Third and last, important aspects such as the revenue models, channels, key resources, and team expertise is going to be addressed, which were mentioned during the interviews, but always remained out of the CDD boundaries.