How can the potential of data be used effectively?
In today's globalized economy, supply chains are more complex and prone to disruption. Small and medium-sized enterprises (SMEs) in particular face special challenges, as they often have fewer resources and less negotiating power with suppliers. Well thought-out risk management can help here by identifying and assessing potential risks at an early stage. In the webinar "Intelligent Supply Chain Risk Management - iSCRM: Harnessing the potential of data", two presentations will show how crucial effective risk management can be for the success of companies.
Especially for SMEs: Intelligent supply chain risk management
Prof. Dr. Michael Krupp heads a research group at the Augsburg University of Applied Sciences which, among other things, deals with the topic of supply chain risk management with a focus on SMEs. In his presentation, he points out that interest in risk management has increased significantly in recent months, including in SMEs. Although the iSCRM research project is currently in an ongoing phase, the first relevant results have already been obtained.
What the Supply Chain Pressure Index means
How have various indicators such as delivery times, freight costs and stock levels developed in recent years? Prof. Krupp explains this using a graph of the Federal Reserve Bank's Supply Chain Pressure Index. Among other things, it shows that globalization has led to a significant increase in global risks in the supply chain since the 1990s. An illustrative example is the blockade of the Suez Canal. It illustrates the impact of such events. However, structural changes are also influencing supply chains, which is clearly reflected in the index.
VUCA world and risk identification
Today's world is often described as a "VUCA world" - a volatile, uncertain, complex and ambiguous environment. In this environment, it is becoming increasingly difficult to clearly identify risks. It is often unclear where exactly a risk lies - be it at the port, with suppliers or elsewhere in the supply chain. This uncertainty makes it difficult for companies to respond adequately to risks. Even with preventative measures, there is still the possibility that problems in the supply chain will have an impact. The aim of risk management is to identify and name risks and to be able to react to them in an agile manner. This requires precise analyses and consistent implementation.
One option is the iterative risk management cycle. It begins with risk identification, followed by risk analysis and assessment, before finally taking measures to reduce or control risks. This cycle must be run through continuously to ensure constant improvements. The Supply Chain Act, for example, places new requirements on companies and entails additional risks if it is not complied with.
Challenges for SMEs: collecting and using data
Prof. Krupp sees a key challenge for SMEs in the low prevalence of digital tools in risk management. A study shows that only four out of ten companies use digital technologies for risk management - and Excel is the most frequently used tool. Smaller companies in particular often do not exploit the full potential of their existing data, even though it could be used for risk analysis. The aim of the research project is to use this data efficiently and develop a system that supports decision-making. To this end, relevant data is to be collected, processed and converted into useful information. As part of the project, extensive literature research was carried out to record the risks described in the specialist literature. This risk map serves as a guide for companies to identify relevant risks. Specifically, the aim is to determine which risks are significant, how serious they can be, how likely they are to be detected and ultimately how likely they are to occur. On the other hand, there is the question of what data is available to effectively monitor these risks. Three points in particular have emerged as key challenges for SMEs in supply chain risk management: the cost-benefit ratio of investments, the complexity of the supply chain and a lack of flexibility, e.g. by focusing on just one supplier.
Influence of artificial intelligence (AI)
Another field of investigation in the project is the use of artificial intelligence (AI) in risk management. Prof. Krupp emphasizes that AI will play an increasingly important role. The research group has asked itself which specific functionalities of AI can be used in risk management. Particular attention is being paid to the prediction of risks and the evaluation of large amounts of data (big data). In the future, AI-supported tools will become increasingly important, particularly in the areas of risk identification and analysis. By using the right data, risks can not only be better identified, but also managed more efficiently. The decisive factor here is the integration of data into meaningful decision support systems.
Data analysis and data visualization in SCRM via dashboards
In his presentation, Kai Uwe Stahl discusses the importance of data analysis and
visualization in order to support data-driven decisions. He emphasizes that optimization potential in companies is strongly linked to data and that well-designed dashboards are crucial to exploiting this potential. At the same time, however, he advocates that companies should be "inspired" by data instead of being "driven" by it alone. Data provides valuable insights and enables well-founded decisions to be made, but it should not be the sole decision-making factor. People remain at the center of decision-making, with data serving as a helpful tool to gain deeper insights and guide actions.
More clarity through visualizations
Visualizations are essential for quickly filtering out relevant information from large amounts of data. One example shows how visual representations make it much easier to recognize the strengths and weaknesses of locations, in contrast to pure text or tables. Well-designed visualizations make it possible to identify trends and developments more quickly and react to them in a targeted manner. An important aspect here is standardization: dashboards should not be overloaded, but should have a clear and simple structure. Colors should be used in a targeted manner to highlight important information without causing confusion.
Data quality and practical implementation
Data quality is a key issue. Instead of waiting for ideal data, companies should work with existing data and define realistic business cases in order to create targeted added value.
Two types of dashboards: Eagle and Dolphin
Mr. Stahl describes two basic dashboard types. The Adler dashboards provide an overview of important key figures and are designed for managers to make decisions quickly. These dashboards work with simple visualizations and provide quick insights into larger trends. The Delfin dashboards, on the other hand, enable deeper analysis where users can interactively dive into the data to answer specific questions through filters and drill-downs and understand complex developments. A structured dashboard design and an intuitive user interface help to use the data efficiently. Tools such as Power BI, Tableau or SAP SAC are often used for this purpose, but the choice of tool is less important than the right methodology and data strategy.
How can supply chain risk management be introduced and used efficiently?
A key topic in the ensuing discussion among all participants was the question of the introduction and use of tools, especially dashboards, and the existing backlog in many SMEs. The main obstacles to the introduction of supply chain risk management systems were highlighted: high costs, the implementation effort and the time required to integrate the new technologies into everyday working life in a meaningful way.
The experts emphasized that a step-by-step approach is crucial for success. Companies should start with small, manageable data projects in order to achieve initial success and thereby convince management of the necessity and benefits of these tools. It is important to use existing and easily accessible data in order to avoid unnecessary complexity and make it easier to get started.
Another key point of the discussion was the social aspects of risk avoidance. It was emphasized that different risk types within an organization - from people who report risks immediately to those who try to solve problems on their own - pose a challenge for risk management. These differences in risk communication can hinder processes. It is therefore important to introduce formalized risk management processes that promote open communication. In addition, the IT skills of many employees need to be strengthened, especially among older generations, who often have difficulties with new technologies. For success, it is necessary to prepare data in such a way that it can also be understood and used by people who are not deeply versed in data analysis. Collaboration within the team is essential here.
Finally, it was pointed out that long-term success can only be achieved through clear objectives and the systematic collection of relevant data. Smaller projects and gradual expansion of data analysis should be at the forefront in order to promote sustainable acceptance and motivation within the company.
The webinar series "From research into practice"
In the webinar series "From research into practice", research institutions and companies provide insights into current research activities and discuss these with participants. The aim is to support small and medium-sized companies in particular in making meaningful use of digital technologies in their production processes and engineering.
You can contact the team from the Mechatronics & Automation Cluster of Bayern Innovativ in person or via the email address CMA(at)bayern-innovativ.de.
Contact details of the speakers
Prof. Dr. Michael Krupp
Professor of General Business Administration,
Focus on Logistics and Supply Chain Management, Augsburg University of Applied Sciences
Contact by email: michael.krupp(at)tha.de
Kai Uwe Stahl
Managing Director "BI or DIE"
Author & lecturer, focus on analytics and dashboarding
Contact by email: kai(at)biordie.com
