Trend 11 to

DEMOCRATIZING SOFTWARE DEVELOPMENT

Facilitating Application Development and Workflow Automation Through Low-Code and No-Code

No-code (NC) technologies enable users without prior coding experience to quickly build applications and products. Low-code (LC) tools allow users with limited development experience to undertake more complex projects. Low-code/ no-code (LC/NC) technologies rely heavily on visual modeling tools, which lowers the barrier to entry for software development [1]. As SMEs face the challenge of attracting and educating the labor force with technological skills, LC/NC (low-code/no-code) solutions offer a smooth transition into software development, thereby enhancing the capabilities of the current workforce. Using LC/NC solutions results in faster time to market and higher agility. LC/NC tools can create value across diverse sectors of SMEs via the development of e-commerce platforms for retail, hospitality, and B2B (Business-to-Business) manufacturers, thereby boosting customer engagement. They also democratize the development of mobile apps, employee interfaces and even advanced internal tools aiding chemical production, construction, or agriculture.

Facts:

■ 70% of new enterprise applications are expected to use low-code and no-code by 2025 [6]. ■ The market for low-code development platforms is expected to grow to $125.3bn USD by 2030 implying the further advancement of the technology [7]. ■ Companies with high organizational speed outperform slower competitors by 4.8 times when it comes to innovation and three times with regard to growth [8]. Using Low-

Code tools can reduce development time by 50-90% [9]. ■ 72% of SMEs reported a lack of technically skilled workers to advance their digitalization efforts [10].

Key Drivers:

■ LC/NC solutions often need to interact with company-internal systems through Application Programming Interfaces (API). More than 90% of developers globally expect to use more APIs in 2022 compared to 2021 [11]. ■ Recent advances in AI-based language models allow generating source code based on simple prompts. This further reduces entry barriers to software development and increases employee productivity. The capabilities of such models are expected to Improve significantly in the coming years [12]. ■ Overloaded IT departments at Mittelstand companies are unable to cope with employee requests. Therefore, employees outside of IT tackle challenges themselves and start building their own digital products and tools using no-code/low-code [13].

Challenges:

■ Due to the low entry barrier for developing software with

LC/NC tools, the employees are able to create software without the approval or even awareness of the IT department. This poses security, data privacy, and financial risks to companies [14]. Therefore, LC/NC efforts demand further scrutiny and resources by IT departments. ■ Currently, no-code platforms can only be used for simple use cases because they are limited by the capabilities of the visual interfaces. Low-Code development offers significantly more customization but might still require coding skills for more complex tasks. ■ Companies report requiring extensive training for employees using low-code development tools.

Impact on the Mittelstand:

LC/NC development tools address many of the Mittelstand companies’ most pressing problems, particularly the lack of skilled IT employees and the struggle to keep up with digitalization. Companies embracing LC/NC will be able to make use of an empowered labor force while simultaneously staying true to their values of investing in current employees without major reeducation requirements. Mittelstand companies will be able to innovate faster and more flexibly, grow more quickly, and stay competitive in a global market. In the future, the capabilities of LC/NC tools will increase significantly as AI progresses, decreasing the barrier to entry even further.

DATALEVERAGED PRODUCTION

Future-Proofing Mittelstand Supply Chains and Production by Advanced Data Usage

The generation and management of data are expected to rise across industries [15], [16]. Consecutively, access to technologies capable of making sense of vast amounts of data (e.g., AI) is projected to increase [17]. This opens a wide range of opportunities for Mittelstand companies to enhance production operations. Due to recent advances in computing capabilities, sensor quality [18], and improved digital infrastructure, companies can accelerate and streamline processes on multiple scales [19], [20]. Data collection and aggregation enable the creation of digital representations of physical processes on a micro level via digital twins. Real-time performance monitoring and detailed simulations with ever-enhancing machine-learning models facilitate scenario prediction, which then can support decision-making and process implementation [21]. These can impact a multitude of sectors ranging from retail with the simulation of facility usage [22] to construction or agriculture with external condition scenarios projected on digital representations of physical infrastructures [23], [24]. On a macro level, data-leveraged processes can make entire supply chains more robust and resilient by decreasing reaction times and risks. Simulations of the whole supply chain can enhance production efficiency and equipment allocation, thereby further reducing costs [25], [26].

Facts:

■ Mittelstand companies are aware of the value created by digital process enhancement [27]. Boards increasingly facilitate data-leveraged production methods, thereby showing fundamental openness [28]. ■ Data-leveraged production tech can lead to a revenue increase of up to 10% and improve product quality by up to 25% [20]. ■ The market for digital twin technologies can reach ca. 48bn EUR worldwide and approximately 7bn EUR in Europe alone by 2025, with an annual growth rate of 30 to 45% [15], [20].

Key Drivers:

■ Entry barriers are decreasing with advancements in sensor fusion and machine learning. Companies can collect valuable data on small-scale applications from current equipment without having to invest in replacement [19], [29]. ■ Underlying technologies for data-driven production, such as AI, IoT, digital twins, or cloud/edge computing, gain recognition [17]. This improves accessibility, and its development is projected to advance even further [15]. ■ The COVID-19 pandemic plays a central role in the growth of data-driven processes as sectors recognize a need for robustness and digitization across supply chains [15].

Challenges:

■ Mittelstand companies must map and facilitate the harnessing of meaningful data across multiple process steps in structured ways to create the foundations for data-driven simulations and leverage them [19]. ■ Using data to enhance processes along production can require initial time and financial investments. As projects are constrained to specific processes, applications can be narrow and thereby have limited scaling potential [30]. ■ A lack of internal competencies can lead to dependency on scarce, external capabilities for the implementation of data-leveraged processes. In complex cases, this can lead to the tempering of the realization of such undertakings [30].

Impact on the Mittelstand:

The meaningful harnessing of data is crucial for Mittelstand companies across all sectors to keep or establish a competitive advantage both against local as well as global competition. The facilitation of data leveraged processes will, however, not simply lead to the creation of enhanced, more resilient, and efficient future operations. With rapid advances in IoT, AI, and digital twin technologies, investment in data-leveraged production will also form a solid foundation for still obscured potential to be unfolded in the future [15].