Leading German Fashion Company : Development and Implementation of a Holistic AI, BI & Data Strategy

A company in the lifestyle and fashion industry was facing significant challenges in data management and business intelligence. After introducing a new data and BI stack without a clear strategy, governance, or prioritization, an unstructured landscape of non-standardized reports emerged, accompanied by significant performance issues. The quality and reliability of BI services noticeably declined. Growing demands for data analytics and data usage, combined with increasing dissatisfaction within the business, led to the initiation of a consulting project. 
The original goal was to define a new BI system landscape. However, it quickly became evident that technology itself was not the core problem. Instead, the focus shifted to developing a holistic AI, BI & Data strategy: one that would ensure centralized and harmonized data processing, define the vision and mission for overall data management, and establish strategic guardrails for implementation within the operating model. This would lay the foundation for long-term efficiency, automation, and competitiveness. 

The solution approach was based on a proven framework for developing a holistic AI, BI & Data strategy. Key elements included defining a clear vision and mission as well as strategic guardrails for design and implementation. Building on this, a hybrid operating model for modern data and BI services was developed, covering processes, roles, and organizational structures. 
In addition, a modern data platform with an integrated data model was created, along with a reporting framework to support the structured development of data products. To anchor the strategy sustainably, a comprehensive enablement concept was implemented, consisting of role-based training and the establishment of a data community to strengthen data literacy across the organization. 

The project resulted in a clearly defined, modern target architecture as well as a roadmap that structured the implementation. The introduction of a unified data foundation enables consistent and reliable analyses. A transparent demand-management process ensures that resources are focused on developing high-value solutions, such as data products. Through the technical implementation and the creation of initial data products, usability is ensured. At the same time, the risk of bottlenecks within BI and IT teams is reduced, as processes and responsibilities are clearly defined. This enables the organization to use data effectively and respond flexibly to new requirements.