Complicated or complex?
Big data analytics or smart human expertise?

Big data analytics is excellent for solving complicated problems. Why? Because such problems allow you to clearly identify the problem and run a thorough analysis. You can apply ‘if-then’ rules that always lead to a result or solution.  Complicated problems can be solved with specialist knowledge – and are eminently well suited to algorithms.

Complex problems, on the other hand, always relate to a system with individual elements that exert reciprocal influences to create a multi-layered dynamic. In seeking a solution, it’s important to understand the system as a whole – merely reducing the complexity isn’t enough and will distort the results. Instead, you need to understand how the individual elements interact. It takes a great deal of flexibility and the ability to tune into this dynamic and its consequences to find a solution. This is where human beings are better by far – especially in a team that links existing technical expertise with an open, far-sighted and flexible outlook, and uses this expediently to understand causes and correlations and come up with solutions.

Innovation development is a complex problem requiring a step-by-step approach that relies on understanding the fundamental problem (i.e. the jobs to be done).

The JU-KNOW problem-solving approach based on systems thinking and user- and client centricity unlocks the complexity without simplifying it to such a degree as to produce solutions that are random and interchangeable. The modular set-up follows the milestones of the innovation development process and enables teams to access the specific support they need for successful developments.

We are experts in decoding the motives, expectations, attitudes and habits of future target groups, and can couple these insights with the results of big data analyses for meaningful interpretation.

Read how we support innovation teams under ‘How to’ Learning & Coaching or with our Modules for the  Innovation Process.