Heuristic techniques for problem solving

Quick take
Summary of ways of thinking about problems.

Commonly used heuristics, from George Pólya’s 1945 book, ‘How to Solve It’.

  • If you are having difficulty understanding a problem, try drawing a picture.
  • If you can’t find a solution, try assuming that you have a solution and seeing what you can derive from that (‘working backward’).
  • If the problem is abstract, try examining a concrete example.
  • Try solving a more general problem first (the ‘inventor’s paradox’: the more ambitious plan may have more chances of success).

Jonathan Bendor at Stanford University has developed a toolkit approach using some core heuristics. It is a very loose way of using a set of heuristics to solve a problem.

The idea is that problem solvers mix and match the cognitive shortcuts to discover their solution.

  • Decomposition – start small and break the overarching problem into smaller pieces.
  • Local Search – learn from experience, look for known, similar solutions and adapt them.
  • Seriality – getting from A to B. Make one small change first, then move on to the next.
  • Multiple Minds – many hands make light work. Don’t work on a problem alone, find out what others think, and use them as resources.
  • Imitation – don’t reinvent the wheel, find out what other organizations are doing and copy them.
  • Recombination – mix and match. Combine a number of different ideas to create a solution.

Using these heuristic elements is a not bound to being a linear or cyclical process;

They can be used in any order, and as many times for different purposes as needed.