PoC provides the basis for recommendations for action

In this project, we advised an internationally successful company in the manufacture of manufacturing systems with over 8,000 employees and an annual turnover of more than one and a half billion euros. In recent years, the company has already begun to rely on data-driven decisions by increasingly using dashboards and reports. Especially in controlling and manufacturing, dashboards play a decisive role for customers in analyzing and managing business processes.

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While the first steps towards a data-driven corporate culture have already been taken, it has been shown that there are definitely weaknesses in the use and preparation of the reports and dashboards mentioned above. In order to overcome the existing challenges, the status quo was already examined and summarized in a previous project. As part of our assignment, we carried out a compact version of our data audit. In doing so, we held targeted discussions with key stakeholders in order to systematically record their assessments of weak points, structural and technical frameworks, and future-oriented solutions.

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In this context, we were able to identify targeted solutions for all three aspects of our framework — organization, culture and architecture — for our client. In the context of organization, it became apparent that, on the one hand, there was no clear point of contact for data issues. On the other hand, the roles and responsibilities in the creation process for developing dashboards or reporting requests were not clearly defined and anchored in the organization. As a result, there was continuous redundant workload and requirements were often processed uncoordinated and inefficiently. In the focus of the second aspect, Kulturm, we noticed a lack of standards and inconsistent processes for implementing reporting requirements. This resulted in similar inquiries being resolved differently in different departments. This not only created unnecessary redundancies, but also an inconsistent data base, which in turn had a negative impact on the comparability and reliability of reports. Another point was the lack of a uniform definition for company-relevant key figures. Different departments interpreted the same KPIs differently, which led to contradictory statements in the dashboards and made company-wide management difficult. In an architectural context, we were able to determine that the existing IT infrastructure was not optimally designed for effective use of data. The strong dependence on the central SAP system and the IT team operating within it led to unwanted workarounds and unstable data queries.

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To address these challenges, we have defined several key measures for all three aspects that support the company on its way to a modern, data-driven organization. All proposed measures are a so-called proof of concept, which includes specific recommendations for action, but has not yet included the final implementation of the proposed strategy.

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As a first step, we defined clear role profiles with specific responsibilities for implementing reporting requirements. As a result, we were able to ensure that there are clear responsibilities for every phase of the reporting process and that requirements are handled in a structured manner. In addition, we have outlined a future organizational structure based on the hub-and-spoke model. This model combines centralized control with decentralized contacts, which enables better coordination and more efficient implementation of reporting requirements. For us, another central component for solving cultural challenges was the suggestion of a standardized process for requirements recording, data modelling and report preparation (see diagram). This process ensures that all reporting requests can be processed according to a uniform methodology and thus ensure a high level of data consistency. In addition, we defined meeting routines that ensure close coordination between the stakeholders involved and promote a continuous improvement process. In addition, we have developed special ticket types for receiving requests in order to structure and speed up the request processing process.

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We also developed a best practice guideline for implementing reports in Power BI. This guideline now serves as a guide for creating dashboards and reports and ensures consistent and high-quality data visualization across the company.

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In addition to these organizational and cultural measures, an architectural extension of the SAP-centered existing landscape also played a decisive role. Using modern cloud technologies such as Azure Data Factory and Snowflake, we built an exemplary PoC infrastructure. This platform enables efficient integration and modeling of data, particularly from SAP, and provides a powerful basis for using the data in Power BI. Through these measures, we were able to create a scalable and future-proof data architecture that allows the company to make data-driven decisions on a reliable and consistent database.

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With the successful implementation of our holistic approach, we were able to set a decisive milestone in digital transformation for our customer. By closely combining organizational, cultural and architectural measures, we have created a powerful basis for a modern, data-driven corporate culture.

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