Data Management in the VUCA World of SAP

The effects of current events such as the invasion of Ukraine or the Corona pandemic reach deep into the supply chains, sales markets or work organization of companies. Our SAP world represents a slice of reality. How can the complexity of the data model and the mapped processes be addressed and the turnaround in data management be achieved?

We find ourselves in a world that the acronym VUCA tries to describe: Volatility, Uncertainty, Complexity and Ambiguity increasingly complicate actions and decisions in companies. The term was coined in the 1990s to describe the multilateral world after the end of the Cold War. Globalization and digitization have since added a previously unimagined dynamic to this.

SAP ERP already maps extensive business processes and uses a complex data model for this purpose - complex in the sense that not all dependencies between the data contents are recognizable to users by a long shot. Another dimension is added to the external complexity, namely that in the company's own data model. This is also due to the sheer number of data fields: The material master alone knows over 1000 fields. The ERP system cannot necessarily be blamed for this, as it attempts to represent a model of reality. However, this realization does not help the overwhelmed user.

The fact that correct master and transaction data are decisive for the success of a company is now universally accepted. Further requirements are added by Industry 4.0 topics. AI systems, which are also finding their way into companies, are also dependent on conclusive training data. Data quality is important - but how to achieve it? What makes sense to escape the complexity trap and regain more ability to act? How can those affected become participants and ultimately active co-creators?

It is helpful to relieve users with intelligent data maintenance tools. A first step would be dashboards with diagrams that clearly visualize data. This can be, for example, the quantity, age or frequency of change of certain data - as well as charts that show evaluations for certain data errors. Cyclically performed analyses illustrate trends. But the clear presentation of work steps in the creation and maintenance of data also helps. Who has to do what and when? Here, too, clarity must be created. 

No user should have to deal with field values that can also be determined via rules or formulas. There is often astonishing potential to be tapped here, which opens up scope for strategic tasks. In addition, user errors are avoided.

In the SAP world, we ideally have a consistent and comprehensive data model. Therefore, it is crucial to take advantage of it. Unfortunately, the real world is not ideal. Then islands form with supposedly simpler and more manageable shadow systems such as Excel or flanged-on tools. To prevent misinterpretations or simply incorrect data, it is advisable to integrate tools directly into SAP as add-ons. 

I have often seen large, strategically designed data governance projects in a kind of deadlock, caused by the complexity described at the beginning. In the case of long project durations, the requirements often change during the course of the project due to the volatility described above. There is then a risk that these projects will go live either with unmet requirements or with schedule and resource overruns.

I recommend a pragmatic (agile) project approach here. Measures to improve data quality or data maintenance processes should produce tangible results in a short time. Based on the experience gained in this way, roll-out decisions can then be made more effectively, for example for further data objects (material, bill of materials, routing, info records, etc.).

Data management remains an ongoing task for management and users, especially in the VUCA world. The task of system providers and consultants is to provide suitable tools and methods for more data transparency and user convenience. 

Then we can succeed in filling the acronym VUCA with new content. How about vision, understanding and clarity instead of volatility, uncertainty and complexity? And ambiguity can be countered with agility.