Data-Driven Business

Intro

At first glance, the concept of a data-driven organization may seem new and challenging. In fact, however, data and information have always been decisive factors within a company. The core idea of a data-driven organization is that decisions should be made on the basis of existing data. Although this is a desirable situation, it is not always the case in reality in a wide variety of companies. It is often different quality levels of data quality and unbalanced processes that hinder companies in their development. Data is the linchpin of many companies. As part of the ongoing digitization of business processes, more and more data is being generated, which is required by different instances. Data forms the core construct, which must be reinterpreted every time data particles are added or dropped in order to help the company achieve success.

Data, People, and Processes

To make a data-driven organization successful, it requires three interlocking elements in particular: data, the people who handle this data, and the associated processes.

For a data-driven organization, improving the significance of the data used and reducing any scope for interpretation is a top priority. Data quality is a crucial element and should be of central importance for all parties involved. Many factors that determine the overall success of the company depend on data quality, such as process efficiency, customer experience or supply chain transparency. Modern technologies and systems are required to achieve a high level of data quality. The type of technology and systems used varies depending on the area of work. Possible examples include product information management, digital asset management, or customer relationship management systems. However, using the right technology alone is not enough, because rules must also be defined for how data is generated and used. This basic stipulation is formulated in the area of data governance and lays the foundation for all current and future actions relating to data.

Data alone is not enough to make a data-driven organization a harmonious whole. The people who work in this organization and whose actions have a direct influence on the quality of the data and, above all, on its further use are much more important. Each actor must be able to interpret the data generated in their own work environment and in their own work processes and contribute to maintaining a consistently high level of data quality. The main task here lies with the company management, which must ensure that every employee involved has a basic understanding of how to handle data or is trained.

The last step, after organizing the data and the people who care about it, is using the data as such to create value from it. The success of a company depends not only on the database or the trained employees, but on how these two basic elements together set the data in motion in the processes.

Master Data Management

The Master Data Management (MDM) approach is anchored one step further in the background: One data set for every single element of the company — no duplicates, no incomplete data sets, always kept up to date. Keeping the data sets themselves clean and up to date is a good approach, but it is only when the data sets are placed in context and a causality is established between them that the approach can be successful. Incomplete data and missing correlations generally lead to misinterpretations, misunderstandings and thus to actions with serious consequences that can jeopardize the overall success of the company.

Since there can be different perspectives on the context, a multi-domain approach for master data management is recommended. Multi-domain MDM makes it possible to make the right strategic decisions by taking into account different perspectives on an issue. This avoids an ill-considered relocation of problems – challenges are always addressed at the source. The multi-domain approach increases work efficiency overall: Current costs are reduced because systems and processes are used effectively, and this also leads to increased sales, because every area of a company can benefit from efficiency.

Conclusion

The goal is clear: a data-driven organization with clear structures, processes and people who act in line with these processes and structures in the company. The idea of a data-driven organization is formulated quickly, and implementation is an even more difficult and complex process. The transformation of corporate culture can be initiated and implemented by management; for the system-side part of the transformation, it is advisable for companies to secure the support of experienced, holistic software integrators. They have a special view from outside and can therefore address all important system-related factors and take them into account accordingly.

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