Mindset: We show you ways to develop an awareness of the value of data and the willingness to rethink established products and historically grown workflows with disruptive ideas.
Competencies: Data scientists, data engineers or product owners – The strategy developed with us shows which resources are needed in the short and medium term for the next steps. In addition, we support you in the question of how you can develop this know-how in your company.
Location: If data science competencies are available, it is important to integrate them meaningfully into the company processes in order to efficiently get from the idea of a specialist department, to the development of the analysis models, to the roll-out and operation of the analyses.
Data pool: Data availability and quality in particular can become decisive hurdles on the way to achieving digital milestones. The data science strategy provides answers to how these hurdles can be overcome.
Toolset: In order to make the most of the potential of data science, analytics solutions must be seamlessly implemented in business processes. A structured IT infrastructure tailored to the requirements of analytics pays off and is an important prerequisite for the professionalization of data science.
Use cases: In view of the expected benefits for the achievement of objectives, the analytical complexity and the existing data situation, it is necessary to identify the most promising use cases for the use of data science and the development of data products that are profitable for you.