Data platform decision with method: future-proof BI strategy through service design thinking

How an industrial company used a service design thinking workshop to create the basis for a clear data platform decision - and thus paved the way for a future-proof business intelligence strategy.

Customer

Customer benefits

Sound decision-making basis for the data platform strategy
Clear cost and license transparency for Qlik vs. Microsoft Fabric
Reduction of redundant systems and processes through governance framework
Future-proof roadmap for the introduction of a central BI and data platform

Technology stack

"Thanks to the structured approach, we were able to bundle all of the departments' requirements for the first time and now have a sound basis for our data platform decision."

Management

Challenges of the customer

The company was faced with a crucial decision: should the existing Qlik environment be modernized or should it be upgraded to Microsoft Fabric be converted? Different departments were using different BI tools, data sources and authorization systems in parallel. This led to high license costs, inconsistent processes and more difficult data management. Governance. The aim was to use a structured approach to develop a fact-based and neutral Data platform decision with a view to costs, integration capability, governance and future-proofing.

Our approach

As part of a multi-day Service Design Thinking-workshop, specialist departments, IT and management were involved in order to systematically analyze requirements, pain points and scenarios.

Stakeholder analysis

At the beginning, the roles involved were systematically recorded. Responsibilities, interests and interfaces were made visible in a stakeholder matrix. This ensured that all perspectives - from the specialist departments to management - were included in the subsequent process.

As-is analysis and modeling of the system landscape

In the next step, the existing BI and data architecture was recorded in detail. Data sources, integrations and workflows were visualized and jointly evaluated. This made it possible to identify weak points such as redundant systems, performance bottlenecks or inadequate interfaces at an early stage. At the same time, the requirements of the specialist departments were translated into target scenarios and pain points were clearly identified.

Development of a governance framework

Based on this analysis, a governance model was developed that clearly defines roles, decision-making processes and responsibilities. With the help of a RACI matrix, responsibilities could be mapped transparently. This created a clear basis for efficiently controlling data management, authorizations and future developments.

Evaluation of the technology options

One focus was on the comparison of possible platforms. The options of Qlik, Microsoft Fabric and hybrid scenarios were examined on the basis of criteria such as license costs, scalability, integration capability and expected growth prospects. This structured evaluation made it possible to compare the opportunities and risks of the alternatives in a comprehensible manner.

Recommendation for action and roadmap

Finally, the results were consolidated and prepared in a decision paper for the management. This included concrete recommendations for action, a transparent license and cost strategy as well as a roadmap with suggestions for pilot projects and proof of concepts. This provided the company management with a reliable basis for decision-making for the future BI and data platform strategy.

Results for the customer

Reduction of potential license and operating costs

0 %

Reduction of internal coordination effort through clear governance and role models

0 %

Further results:

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