Heuristic Techniques for Problem Solving

Heuristic techniques are not a formal problem-solving model as such, but can be used as an approach to problem solving, where solutions are not expected to produce a perfect or optimal solution.

Heuristic Techniques for Problem Solving

Heuristics are usually mental shortcuts that help with the thinking processes in problem solving. We have either learnt these techniques – usually informally, or they are hard wired for survival. We often use them automatically to solve a problem.

Relying only heuristics to solve a problem works well as a quick fix or when the alternative solution is impractical – it may cost too much, be unusable in the current environment, or be a long-term project. Examples of heuristics include using:

  • A rule of thumb
  • An educated guess
  • An intuitive judgment
  • Stereotyping
  • Profiling
  • Common sense

They can also be used as part of creative problem solving techniques, but should only be used as one of the ways to generate ideas, or overcome a barrier.

Examples of Heuristic Techniques

Formal method problem solvers should always be aware that relying too heavily on one or more heuristics can introduce error or bias, and may constrain creativity and innovation.

Overview

Heuristics are physiological concepts for simple, efficient rules that help to explain how people solve problems. These rules usually work but are prone to preconceptions, and can introduce errors. For example, an educated guess is based on knowledge and experience, but excludes what you have yet to learn.

Heuristics are physiological concepts for simple, efficient rules

Heuristics do not aim for novel solutions, but to implement the known, readily accessible, loosely applicable. It essentially limits problem solving in human beings, to focus on the immediately doable. It often uses trial and error to find the solution that works.

Here are a few other 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).

Heuristic Techniques

Toolkit

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.

Jonathan Bendor's Toolkit Approach

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.

Not every element needs to be used for every problem as shown in the example – ‘people missing dentist appointments’.

Initially, the problem solving group might include the office manager, the receptionist and the dentist. Later on it might include other stakeholders, like patients (Multiple Minds). The problem solving group ask the wider team what they feel has worked well in the past and any experiences they have of working elsewhere (Local Search).

The team looks at how other dentists, GPs and Hospitals have dealt with missed appointments (Imitation). Then the problem solving group will then be assigned to smaller, individual tasks – survey, reminders, answering phones etc. (Decomposition).

Findings – this is not a heuristic in the toolkit, but a necessary part of problem solving.

Research reveals that reminder letters are not effective, as people still forget appointments. Patients often can’t get through on the phone to cancel appointments or change them, or don’t like leaving messages. People lose their appointment cards. The team discover that automatic SMS reminders people have been used elsewhere, and are relatively inexpensive.

The team will implement a system where an SMS messages will be sent out as reminders, replacing letters – a week before and a day before. The patients can message back to cancel the appointment. Additionally, people will be able to email in cancellations. This should reduce the pressure on phones and allow other people to get through to cancel appointments. (Recombination)

This is not a final solution. This has moved the practice from A to B. Now it needs to move from B to C. Once it is implemented, a solution for those that do not have access to mobile phones or email will need to be found and implemented (Seriality).

Heuristic techniques are not a formal problem solving method. They can be used alone, or in combination with other heuristics. The theory of heuristics is complex but are essentially the clichés of problem solving.

They do not seek to find a final solution (although they may do). They are often a process of trial and error. If a rule of thumb fails, you may then use experience to try a different solution. If this fails, you may bring in multiple minds to help you solve it, and so one.

The advantage of heuristics is that they can rapidly solve a problem, but it may often result in an immediate, but ‘temporary fix’. Heuristics are prone to bias and introducing errors. They should be used with care, and as a trigger for formal problem solving, to develop a better, longer-term solution.

Key Points

  • Heuristics are usually mental shortcuts that help with the thinking processes in problem solving.
  • They include using: A rule of thumb, an educated guess, an intuitive judgment, stereotyping, profiling, and common sense.
  • Heuristics do not aim for novel solutions, but to implement the known, readily accessible, and loosely applicable.
  • The advantage of heuristics is that they can rapidly solve a problem, but it may often result in an immediate, but ‘temporary fix’ as they are prone to bias.
  • Heuristics should be used with care, and as a trigger for formal problem solving, to develop a better, longer term solution.

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