Build your strategy
We are here to help you get more data-driven.
BackgroundWhy you require a data strategy.
Data roadmapWhat are the major milestones and steps.
MetricsWhich metrics you need to track to stay the course.
GoalsWhat results your data strategy should deliver.
Risk and success factorsHow to ensure the project succeeds.
Business caseWhat value will be unlocked.
Budget estimatesWhat are the estimated costs for each activity.
How Clients React
Assem Memon-Managing Director
Kweri explored possible data sources and validated their quality, which helped us make better business decisions.
Jappe van der Zwan-Head of Innovation Lab
Kweri’s expertise with data and digital prototyping increases the pace of innovation at NEN
Herzog Badenhorst-Operations Director
Kweri forecasted customer demand for our steel coils. This will enable us to make more data-driven decisions around production planning and inventory management.
Train your team
In this course you will gain knowledge on the process of data science and learn how to translate business challenges into analytical use cases.
- Models and metrics
- Data science workflows
- Technical challenges
- Innovation strategy
- Value propositions
- Business challenges
Data-driven value propositions
- In-person or via Miro
- Succesfully identifying data science use cases
- Mapping data science use cases to the value chain
- Prioritizing data science use cases
- Defining clear data goals and success criteria to assess solutions
- Create data-driven value propositions and define underlying assumptions