If you look at all the technological trends and opportunities, regardless of industry and company size, everything currently revolves around transformation. It can be a digital transformation, a business transformation or a new business segment that needs to be established. The ability to understand and manage data so that you are ready for any type of transformation is key to staying competitive. The foundation for this is a data strategy linked to the business strategy.
A data strategy is much more than an understanding of your current data assets. It defines how your data can support your business strategy in its implementation. The prerequisite for this is a clear understanding of your goals and the metrics to measure how well they are being met. Once that is achieved, the next step is to verify that your data assets are sufficient and complete. To guarantee this, you should ensure that everyone in your organization understands your data and why they are maintaining it at the defined granularity.
To bring this about, data glossaries are often used. This specifies what the data describes, where it is created, who creates it, what attributes are assigned to it, whether there are any restrictions from a data protection point of view, what should be paid attention to, and more. The goal is to provide everyone in your company with a detailed overview of your data.
A central component of your data strategy is also a mature data governance concept. This defines the framework conditions for ensuring that the data strategy is achieved. This includes the definition of clear responsibilities for maintenance processes, data quality and compliance with data governance policies. Furthermore, it should clearly define the choice of systems, as well as the integration rules between the systems. The question you need to ask yourself is how detailed and how strictly you want to control and monitor your data governance.
Once you have defined your data strategy, described your data transparently and completely for your organization in a data glossary, and defined your data governance concept, it is time to implement it.
When creating your data strategy, you will have noticed inconsistent data sets, inefficient maintenance processes, missing data attributes or even completely missing data. These gaps need to be addressed in order to lay the foundation for achieving your data strategy. In doing so, the infamous Big Bang is not recommended, as the change and the associated effort is usually too great to accompany it successfully, depending on its scope. Rather, you should roll out your data strategy in stages to be able to share successes early on and draw lessons learned from your organization's feedback. If upgrading from SAP ECC to SAP S/4HANA is part of your business strategy, one of the things you need to do beforehand is introduce SAP Business Partner. The prerequisite is consistent customer and vendor master data. Thus, the creation of this condition must be a part of your data strategy.
After you've implemented your data strategy, you can start getting value from your data. Introduce a new technology or implement data analytics that you didn't implement before. What you should take away from this is that data is the foundation for all of your processes and therefore your success. This article should give you an overview of the size and relevance of the topic. In the following articles, we will introduce you to the individual sub-areas in detail.
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