Decision-making software

Decision-making software (DMS) is used to help individuals and organizations with their decision-making processes, typically resulting in ranking, sorting or choosing from among alternatives.

An early example of DMS was described in 1973.[1][2] Before the advent of the World Wide Web, most DMS was spreadsheet-based,[2] with the first web-based DMS appearing in the mid-1990s.[3] Nowadays, at least 20 DMS products (mostly web-based) are available.[4][5][6]

Though DMS exists for the various stages of structuring and solving decision problems – from brain-storming problems to representing decision-maker preferences and reaching decisions – most DMS focuses on choosing from among a group of alternatives characterized on multiple criteria or attributes.[4]

Purpose

DMS is a tool that is intended to support the analysis involved in decision-making processes, not to replace it.[5] "DMS should be used to support the process, not as the driving or dominating force."[7] DMS frees users "from the technical implementation details [of the decision-making method employed – discussed in the next section], allowing them to focus on the fundamental value judgements".[7] Nonetheless, DMS should not be employed blindly. "Before using a software, it is necessary to have a sound knowledge of the adopted methodology and of the decision problem at hand."[8]

Methods and features

Decision-making methods

Most decision-making processes supported by DMS are based on decision analysis, most commonly multi-criteria decision making (MCDM). MCDM involves evaluating and combining alternatives' characteristics on two or more criteria or attributes in order to rank, sort or choose from among the alternatives.[9]

DMS employs a variety of MCDM methods;[7] popular examples include (and see the table below):

Naturally, there are significant differences between these methods[7][9] and, accordingly, the DMS implementing them. Such differences include:

  1. The extent to which the decision problem is broken into a hierarchy of sub-problems;
  2. Whether or not pairwise comparisons of alternatives and/or criteria are used to elicit decision-makers' preferences;
  3. The use of interval scale or ratio scale measurements of decision-makers' preferences;
  4. The number of criteria included;
  5. The number of alternatives evaluated, ranging from a few (finite) to infinite;
  6. The extent to which numerical scores are used to value and/or rank alternatives;
  7. The extent to which incomplete rankings (relative to complete rankings) of alternatives are produced;
  8. The extent to which uncertainty is modeled and analyzed.

Software features

In addition to helping decision-makers to rank, sort or choose from among alternatives, DMS products often include a variety of additional features and tools;[3][4] examples include:

Comparison of decision-making software

Notable software includes the following.

Software Supported MCDA Methods Pairwise Comparison Sensitivity Analysis Group Evaluation Web-based
1000Minds PAPRIKA Yes Yes Yes Yes [5]
Ahoona WSM, Utility No NoYes Yes [11]
Altova MetaTeam WSM No No Yes Yes
Analytica No YesNo Yes [5]
Criterium DecisionPlus AHP, SMART Yes Yes No No
D-Sight PROMETHEE, UTILITY Yes Yes Yes Yes [5]
DecideIT MAUT YesYes Yes Yes [5]
Decision Lens AHP, ANP Yes Yes Yes Yes
Expert Choice AHP Yes Yes Yes Yes [5]
Hiview3 No Yes Yes No [5]
Intelligent Decision System Evidential Reasoning Approach, Bayesian Inference, Dempster–Shafer theory, Utility Yes Yes Yes Available on request [5]
Logical Decisions AHP Yes Yes Yes No [5]
Loomio ? ? ? ? Yes
M-MACBETH MACBETH Yes Yes Yes No [10][12]
PriEsT AHP Yes Yes No No [13]
Super Decisions AHP, Analytic Network Process Yes Yes No Yes [14][14]

See also

References

  1. Dyer, JS (1973), "A time-sharing computer program for the solution of the multiple criteria problem", Management Science, 19: 1379-83.
  2. 1 2 Wallenius, J, Dyer, JS, Fishburn, PC, Steuer, RE, Zionts, S and Deb, K (1992), "Multiple criteria decision making, multiattribute utility theory: The next ten years", Management Science, 38: 645-54.
  3. 1 2 Koksalan, M, Wallenius, J, and Zionts, S, Multiple Criteria Decision Making: From Early History to the 21st Century, World Scientific Publishing: Singapore, 2011.
  4. 1 2 3 Weistroffer, HR, Smith, CH, and Narula, SC, "Multiple criteria decision support software", Ch 24 in: Figueira, J, Greco, S and Ehrgott, M, eds, Multiple Criteria Decision Analysis: State of the Art Surveys Series, Springer: New York, 2005.
  5. 1 2 3 4 5 6 7 8 9 10 Oleson, S (2016), "Decision analysis software survey", OR/MS Today 43(5).
  6. Ishizaka, A.; Nemery, P. (2013). "Multi-Criteria Decision Analysis". doi:10.1002/9781118644898. ISBN 9781118644898.
  7. 1 2 3 4 Belton, V, and Stewart, TJ, Multiple Criteria Decision Analysis: An Integrated Approach, Kluwer: Boston, 2002.
  8. Figueira, J, Greco, S and Ehrgott, M, "Introduction", Ch 1 in: Figueira, J, Greco, S and Ehrgott, M, eds, Multiple Criteria Decision Analysis: State of the Art Surveys Series, Springer: New York, 2005.
  9. 1 2 Wallenius, J, Dyer, JS, Fishburn, PC, Steuer, RE, Zionts, S and Deb, K (2008), "Multiple criteria decision making, multiattribute utility theory: Recent accomplishments and what lies ahead", Management Science 54: 1336-49.
  10. 1 2 Bana e Costa, CA, De Corte, J-M and Vansnick, J-C (2012), "MACBETH", International Journal of Information Technology & Decision Making. 11(02):359-87.
  11. http://create.usc.edu/sites/default/files/publications//dmsocialnetworkswithcover.pdf
  12. "www.m-macbeth.com"
  13. Siraj, S., Mikhailov, L. and Keane, J. A. (2013), "PriEsT: an interactive decision support tool to estimate priorities from pairwise comparison judgments". International Transactions in Operational Research. doi: 10.1111/itor.12054
  14. 1 2 "www.creativedecisions.org"
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