Data strategy for After Sales.
After Sales is a central value lever for automotive manufacturers. A specific data strategy raises the economic contribution in a targeted way and systematically prioritises data-based use cases.
The question
How does the data potential in After Sales become a measurable economic contribution, rather than scattered individual ideas without prioritisation?
Our answer
We developed a specific data strategy that supports the long-term business-field strategy in After Sales. To do so, we assessed the strategic goals for how well data, analytics and AI can support them, derived concrete and measurable objectives from them, and defined suitable use cases for each objective. We then prioritised these by business value, described them functionally and technically, and translated them into an implementation plan with concrete measures.




What we delivered
Business strategy examined for data potential.
Strategic goals assessed and translated into concrete, measurable data and AI objectives.
Defined, assessed, prioritised by business value.
Concrete use cases developed for each goal and ranked by business value and feasibility.
From identified needs to a concrete roadmap.
Measures defined and translated into a step-by-step implementation plan.
What it achieved
- Clear strategic objectives defined for the effective use of data and AI.
- Relevant use cases with high business value identified and prioritised.
- Concrete measures derived for implementing the data strategy.
- Implementation plan created for a step-by-step rollout.
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Learn moreLet us talk about your objectives.
In 25 minutes you will understand whether we can help. No slides. No demo.
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