Keywords

1 Introduction

The terms digitization and digitalization are used interchangeably in the literature. However, for the purposes of this paper, a clear distinction is made between digitization and digitalization. Digitization refers only to the conversion of analog information, such as a paper document, into a digital format such as a pdf document [1]. Digitalization is a more encompassing term and refers to the ongoing transformation of business processes because of new digital technologies [2]. Organizations have long recognized the importance of managing key resources such as people and raw materials. Now, information has moved to its rightful place as a key resource. Decision-makers understand that information is not just a by-product of conducting business; rather, it fuels business and can be the critical factor in determining the success or failure of a business [3]. Until recently, there has been slow progress towards leveraging information as a resource amongst small South African businesses, perhaps the result of more than half of its citizens living below the poverty line [4]. However, since the onset of the Covid-19 pandemic SMEs, which make up over 98% of businesses and employ more than 50% of workers in South Africa, have begun their digital transformation [5]. In 2018 PWC’s Strategy and Global Digital Operations study found that only 10% of global manufacturing companies were considered “Digital Champions”, whilst almost two-thirds had barely begun or had not yet begun the digital transformation journey [6]. In 2022, the race toward digitalization is in full swing, but the truth is that most small South African businesses lack the resources and skills to make the transition to a digital, data-driven business model [7]. If these businesses are to compete in the modern digital environment, then harnessing the power of the data they generate will be paramount. However, this poses a difficult question “How do small businesses rapidly harness the power of their data at low cost, with low skills, and in an environmentally sustainable way?”. Digitalization is a resource-intensive process and involves the production of computing equipment, the design of software and database infrastructure, and the cost of maintaining and operating a system once in place [8]. The environmental impact of constructing server rooms, writing software, and maintaining the systems themselves is huge [9]. Moreover, alternatives such as Software as a Service (SaaS) can be prohibitively costly. The solution lies in being able to construct information systems in a low-cost, low-skill manner and bring them to life using sustainable cloud infrastructure. Not every company can afford to power its servers with renewable energy, but Google can.

2 Literature Review

2.1 Concept

Digitalization is defined by Gartner [10] as “The use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business.”. This covers the implementation of the technology required to support digital systems, as well as the updating of business models to synergize with the capabilities of the new technology. The image of factory workers laying down their hand tools and learning to operate automated machines springs to mind. Digitalization can be divided into 4 overarching levels [11]: (1) process level: streamlining processes by adopting new digital tools and reducing manual steps, (2) organizational level: offering new or improved services and discarding obsolete practices, (3) business domain level: changing roles and value chains in ecosystems, (4) societal level: changing societal structures (e.g., type of work, means of influencing societal decision making). The framework discussed here is germane to the process level of digitalization.

2.2 Benefits

Globally, the application of digital technologies in SMEs has disrupted and revolutionized many industries and organizations [12, 13]. There are a variety of benefits associated with digitalization including replacing manual steps in information-intensive processes, resulting in more streamlined and effectual actions [11]. Moreover, data tracked in real-time allows workflows to become more transparent [14], and identifies areas in need of process improvement, which can result in cost reduction [15, 16]. The more parts along the value chain that are digitalized the greater the resource savings as fewer people, less work, and more data visibility enable greater control, foresight, planning, and decision making [17]. Without the means to implement information systems small businesses in South Africa are left at a disadvantage.

2.3 Limitations

Digitalization has great promise, but it is not without its limitations. Digitalization typically requires advanced computing infrastructure like servers, and or datacenters. Usually, the associated software must be created or bought from other companies. Creating on-site information systems requires highly skilled workers, time, and money [18]. Buying software and offsite infrastructure often limits the capabilities the organization might be able to derive from the system and comes at a premium, often recurring, cost [19]. Neither of these solutions hold much promise for a low income and technologically limited small business owner.

2.4 Sustainability

As the use of information technology becomes more ubiquitous, the need for data processing and storage capabilities increases. This results in the construction and operation of large data center facilities that house thousands of servers and serve as the backbone for all types of computational processes [20]. Unfortunately, as processing power and storage capacity increase, so do the corresponding power and cooling requirements of the data centers. Several studies have examined the efficiency of data centers by focusing on server and cooling power inputs, but this fails to capture the data center’s entire impact [21,22,23]. To fully account for the environmental impact of these resources the materials, manufacture, and transportation of the servers themselves should also be considered. Large, centralized data centers can offset the emissions of manufacturing by distributing the required compute over many servers and using algorithmic control of power supplies, minimizing idle time, and maximizing resource utilization [24, 25]. For many small businesses, the capital involved in this is prohibitive. However, many do have access to at least one computer or a mobile phone, which could be used as a link to an outsourced data center.

2.5 Mobile and Cloud

A promising solution to the problem of high energy consumption is the use of “green data centers”. That is, data centers that run primarily on green renewable energy. Google has been carbon neutral since 2007, currently matches 100% of its energy consumption with renewable energy and has eliminated its entire carbon legacy pre-2007 through the purchase of high-quality carbon offsets [26]. Not all companies can afford to run such a clean data center and thus the prospect of outsourcing the hardware needs to Google is attractive. Furthermore, small businesses stand to benefit from the suite of free cloud-based applications like Google Sheets, and Google Sites, which are all integrated into the Google Cloud ecosystem. The use of these applications requires little to no training, and they are accessible for free to anyone, anywhere, anytime. Moreover, the fact that it is cloud-based and mobile-friendly means that the user would need little more than a smartphone to leverage these services.

2.6 Existing Research

Previous research has focused on implementation in companies that are well established and have the economic resources to develop or buy their own information systems [27]. Furthermore, the high investment requirements for new I4.0 applications and limited availability of skilled staff are regarded as the biggest obstacles to I4.0 implementation [28]. The purpose of this paper is to explore the potential of using free cloud-based software to allow low-income, unskilled business owners to build their own information systems. Research in this area is sparse as it is generally assumed that financial resources are a prerequisite for the development of an information system [29]. However, the emergence of the cloud has opened new avenues that may potentially allow these unskilled individuals to leverage technologies previously inaccessible to them. Using Google as the model of a cloud-based “green data center” and their suite of free cloud-based applications and tools the proceeding methodology seeks to design and implement an information system that could be replicated by a small business, even without advanced skills or large capital outlay.

3 Methodology

3.1 Candidate Selection and Analysis

A candidate business was selected on the grounds of its apt representation of a small, paper-based business in South Africa. The business was analyzed and discussions with the owner and employees were conducted. Key areas of interest were identified and added to the system to maximize its utility without allowing the system architecture to become overcomplicated. The business processes associated with the new system were analyzed, improved, and redesigned to interface with the system.

3.2 System Specifications

Interviews and discussions with the stakeholders of the business eventually generated a list of requirements for the system. Potential additions to the system were scrutinized and only the requirements with the greatest potential return on investment were used to minimize complexity. The user requirements were further processed into a set of system requirements which were then finally reduced to a set of specifications that the system must meet to satisfy the needs of the business.

3.3 System Architecture

The tools used for synthesizing the system were restricted to those that are freely available and mobile friendly. The ecosystem of applications used included Google Forms (data capture), Google Sheets (data storage), Google Data Studio (data processing), Google Sites (interfacing host), and Scan2Web (QR code scanner). The system was designed to be usable with only a smartphone and is almost entirely cloud based apart from the QR scanning app which must be installed onto the user’s phone.

4 Results

Fig. 1.
figure 1

A collection of screenshots of the mobile friendly interface showing the UI and chart outputs for some dummy data.

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The resulting information system was focused on kitchen stock control. The user interface takes the form of a website, hosting forms for data capture and reports displaying graphical analysis of the data. The stock level of the freezer and fridge are shown as line charts which can be filtered by product and aggregated at various time intervals. Several KPIs including spoilage and stock days remaining are calculated and displayed on the website (see Fig. 1, above).

4.1 Candidate Selection and Analysis

Fig. 2.
figure 2

A comparison of the old and new business processes (ROP stands for Re-Order Point).

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“Chisa nyama (also spelled shisa nyama or chesa nyama) is a Zulu word - literally meaning ‘burn meat’ - used to describe a popular ‘buy-and-braai’ style of venue found across South Africa, particularly in townships. At a chisa nyama, you choose your own meat from an attached butchery and then have it barbecued, or in some cases ‘braai’ (barbecue) it yourself.” [30]. A chisa nyama operating out of Bellville, Cape Town was selected. The small business was paper-based, and the owners did not have access to anything beyond a smartphone and a cash register that can print receipts and sales reports. Analysis of the current business processes, including discussions with the owner and employees, eventually led to the coda that tracking of kitchen stock levels held the greatest potential for improvement. This choice was motivated by high uncertainty surrounding the true stock levels in the kitchen, excessive theft, spoilage of stock, and disproportionate labor allocation towards stocktaking activities. The associated business processes were redesigned to incorporate the new technology and streamline the tasks of the worker (see Fig. 2, above).

4.2 System Requirements and Specifications

See Table 1

Table 1. A table summarizing the conversion of user requirements into system specifications.
Full size table

4.3 System Architecture

The system was split up into three distinct modules, namely data capture, data processing, and data visualization. The first module relied primarily on the use of web forms created in Google Forms, in addition to a QR scanning app, to capture data from business operations. It consists of three forms for capturing purchases, sales, and stocktakes and the app for tracking freezer stock. The second module processes that data with Google Sheets into normal data tables. The normalized data tables were used as a database to feed Google Data Studio which then output visualizations of the data in the form of charts and KPI’s. Lastly all three modules were hosted in a Google Sites website for easy navigation between capturing and viewing data.

5 Discussion

The reception from employees was positive with many stating the system had eased their workloads. Furthermore, management reported that they had greater control over their stock and were able to eliminate or decrease several sources of waste. The owner is grateful for the mobile interface as there was no need to buy a computer.

6 Conclusion

The methodology proved to be a viable way for a small business to begin their digital transformation. The benefits were tangible and achievable. It is recommended that anyone attempting to replicate this methodology research relational databases and systems design. The system whilst successful still suffers from several limitations. Developing complex algorithms or logic using only Google Sheets is challenging. Further, the row limit of one million data entries per sheet means that the database would eventually need to be cleaned out to avoid obsolescence.