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Why and how does WiQQi fan out solutions?

Why and how does WiQQi fan out solutions?

Solutions are collaboratively fanned out to broaden your view.

WiQQi fans out different approaches to show the range of possible solutions. We are thus dealing with the problem of "functional fixation". Broadening approaches can mean that we are looking for approaches that deal with the causes of a problem - or approaches that take into account the effects.

  • Problem/objective: Sometimes we face the problem that the apple we want hangs too high in the tree.
    • Causal solutions would deal with eliminating the height difference. By climbing, a ladder, an arm extension or with long-term consequences by cutting down the tree.
    • Question symptomatic solutions, why we want to reach this apple. The focus can also be based on the fact that we saw the apple first. But the purpose is that we just want to satisfy hunger. In this case, it is worthwhile to see whether there are apples attainable height. Maybe there is an accessible apple hidden behind the leaves or on the floor?

WiQQi is looking for different solution options because this provides clarity about the problem and the goal. This broadens the view of ethical and professional reflection. Solution approaches should be as different as possible. The solutions within an approach should be similar:

  • Diversity: The full range of possible solutions can be compared - this makes fundamental questions visible.
  • Similarities: Similar solutions can be compared - detailed questions become visible.
  • Diversity of perspectives: Solutions can be conceived or tested in different contexts - this makes fundamental and detailed questions visible.

For all the benefits, fanning out also means more effort. So that the work remains manageable for the individual, we work together and always fall back on the work once done:

  • Collaboration: Someone always knows a good solution to a problem.
  • Sustainability: We collect existing solutions in the WiQQi database. The more solutions we have collected in the database, the faster the fan-out will work. In the database, all solutions are assigned to a problem-target-resource constellation, i.e. we can learn from other cases with similar problems, similar goals, or similar resources. Just like we do it in real life.

Important questions are:

  • Problem analysis: What are the experiences from other cases? What have we overlooked so far? Which questions are still open?
  • Clarification of objectives: Is the objective formulated in an understandable way? Can it be measured? What misunderstandings does our wording entail?
  • Research: Which search terms are still missing? Which could help?
  • Experience: Which solutions have already proven themselves in similar cases or have they failed? Which solutions could be transferred to the case to be solved? What do we have to pay attention to?
  • Criteria: Which decision-making criteria can be derived from existing experience? How are the criteria formulated to guide decisions?
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