Design Thinking for Data Driven Business
Lead your business step by step to data-driven success.
Design value adding analytics solutions from a user's perspective.
Design new business models and check the viability of business cases.
Optimize you customer journey to attract more customers, increase revenue, increase their loyalty and get more recommendations.
Unleash the full potential of your data sources and discover new data providers.
Increase Data Quality as well as Data Availability and ensure Data Privacy as well as Data Security.
Turn your data into corporate assets and increase your company's productivity.
Plan and illustrate your data strategy workshops.
Wir treiben Ihr Unternehmen voran.
Plan your data strategy projects and document the current state.
Identify new growth markets and tap the full potential of new technologies.
Stay focused on the relevant and important tasks, projects and ideas.
Identify the relevant decision-makers.
Find the right way for your company to make your vision come true.
Identify relevant customers and tap new business opportunities.
Create unique products and services.
Cards for data strategy design
Help us improve the impact and usability of this tool! What do you think of this collection? Have you used it? Why? How? What worked well? What would you change? Join the discussion!
Sign up or log in to add feedback.
During a conference a couple of years ago, I was lucky enough to see Martin Szugat talk through an example workshop using the first canvasses in this series. I've used them ever since and I'm pleased to see that the original set has been expanded. I've found them useful for building consensus with peers, showing execs we have business focussed rigour, and for reflection on strategy, communication and value. If you are working towards data as an asset or trying to monetise data (by using or complementing your own data sets) you will find these canvasses useful. Try mapping some of your existing products or services and see what happens when you corrupt/delete/loose/screw up the source data sets; you might be able to start putting a value on the data you have and get better traction on your future data initiatives.
Do you have feedback? Are you interested in workshops & training to help you get started? Please let us know what you think.
Thank you for your message. We will get back to you as soon as possible!
Hi, we are Datentreiber,
the people that shared this collection.
Have a question?
- Datentreiber Team
Hi visual thinker!
Try Creatlr now and get a free 14-day Creatlr Professional trial. Unlock the full power of Creatlr!
Get PRO now!
There seems to be a connectivity problem. Please check your internet connection and refresh this page.