An Approach Towards Securing Future Viability Of SMEs In A VUCA World Using Artificial Intelligence To Increase Resilience

Global crises pose major challenges for production companies: Rising material and energy costs, supply bottlenecks and the lack of planning certainty due to the dynamics of a pandemic or war weaken the planning stability. In this volatile, uncertain, complex and ambivalent environment (VUCA world), companies need responsible employees who recognise the individual need for action and initiate concrete measures early to increase a company's resilience. These measures affect multiple divisions. For example, disruptions in the supply chain are mitigated by various configuration elements such as expanding the supplier network or increasing stock in the company's own production. Therefore, measures encompass every element of the value network, whether in production or logistics. The example also shows that measures to increase resilience can influence other target characteristics of a company: Inventory increases can buy resilience at the expense of resource efficiency. Thus, measures must be defined for each design element depending on individual requirements in terms of resilience and must consider the scope for action of the respective company. This poses a great challenge, especially for small and medium-sized enterprises (SMEs). Here, decision-making is done by generalists who often do not have the detailed knowledge for this specific problem or the capacity for this additional task. The danger is that SMEs will take insufficient measures that do not secure their future viability in a VUCA world. In this paper, a solution approach for a methodology is presented, that allows to derive influences on production companies from the developments in a VUCA world and measures to increase resilience can be identified depending on individual company characteristics. Furthermore, a possible conceptualisation of the methodology in an AI-based software product is presented, which supports SMEs in the outlined complex problem by enabling them to apply the methodology. Both will be realised in a research project.