Supply chain operations decision making techniques

  • Game Theory – For complex strategic decisions where it is beneficial to take into account the likely response of outside participants(e.g. customers, competitors, government), Game Theory provides a potentially valuable decision making
    technique. Game Theory approaches can be considered extensions to Influence Diagrams. It’s most significant limitation is in the simplifying assumptions needed to reduce a decision to a solvable game problem.
  • Multi-voting – This technique is used for group decisions to choose fairly between many options. It is best used to eliminate lower priority alternatives before using a more rigorous technique to finalize a decision on a smaller number of options.
  • Cost/Benefit analysis – This is limited to financial decisions or can provide the data for evaluation of financial criteria in other decision making techniques.
  • Net Present Value (NPV) and Present Value (PV) – Net present value and present value calculations are often used for capital budgeting and investment decisions. NPV is sometimes considered a single criteria decision technique.
  • Linear Programming (LP) – Generally used to optimize limited resources, linear programming is a mathematical technique where requirements are represented by linear equations. Useful problems in operations research can be addressed using this
    technique.
  • Conjoint analysis (same or related techniques: stated preference analysis, choice modelling, discrete choice) – A statistical technique used in market research, conjoint analysis is used to estimate the psychological trade-offs made by consumers for
    features and/or attributes of a product or service. This can be helpful in forecasting consumer acceptance and determining market positioning.
  • Affinity Diagrams (same or related technique: KJ Method) – Address information overload by organizing many ideas and large amounts of data using this technique. This technique is typically used as part of a brainstorming exercise.
  • Trial and Error – This approach to learning has provided the basis for decision making from our childhood. Main limitations are that consequences for decision failure should be small, and proper reflection must be done after the trial and error to ensure that correct cause/effect relationships are identified in the learning.
  • Heuristic Methods – These are trial and error decision making approaches that start with a model that is refined with on-going experimentation. Because they aren’t accurate, use heuristics to reduce options or save time when approximations will be
    acceptable.
  • Scientific Method – Typically used to explore scientific questions, this problem solving technique also can be used to make decisions. As experiments are used to further confirm or refine a hypothesis, this technique could be considered a heuristic
    method.
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