People, even the smartest, are terrible at making good decisions whenever more than a couple of interdependent factors are involved.
Our world is full of such complex problems.
We are working for a future in which knowledge workers can perform complex analyses in a fraction of the time required today. We want to enable a rich, more efficient transfer of knowledge.Request a demo
We see solving complex problems and making strategic decisions as a continuous cycle of four steps, condensing a vast cloud of factors into concise, well-reasoned, and actionable solutions.
In solving a problem, we have to formulate and continuously refine our understanding of what we are trying to achieve, as well as all the factors and constraints influencing our solution.
Initial observations warranting further investigation have to be backed up by supporting material such as calculations, empirical studies or theoretical models—thus building up coherent lines of reasoning.
Separate areas of analysis are put into relation with one another in order to arrive at a holistic understanding of the problem. This enables a substantiated, model-driven discussion of solution candidates under clear assumptions.
The rationale behind conclusions is often lost. This impedes depth and speed of comprehension that is crucial in detecting argumentative flaws, sharing context, and reusing acquired knowledge.