Decision-making software explained

Decision-making software (DM software) is software for computer applications that help individuals and organisations make choices and take decisions, typically by ranking, prioritizing or choosing from a number of options.

An early example of DM software was described in 1973.^{[1] [2]} Before the advent of the World Wide Web, most DM software was spreadsheet-based, with the first web-based DM software appearing in the mid-1990s.^[3] Nowadays, many DM software products (mostly web-based) are available^{[4] [5] [6] [7]} – e.g. see the comparison table below.

Most DM software focuses on ranking, prioritizing or choosing from among alternatives characterized on multiple criteria or attributes. Thus most DM software is based on decision analysis, usually multi-criteria decision-making, and so is often referred to as "decision analysis" or "multi-criteria decision-making" software – commonly shortened to "decision-making software". Some decision support systems include a DM software component.

Purpose

DM software can assist decision-makers "at various stages of the decision-making process, including problem exploration and formulation, identification of decision alternatives and solution constraints, structuring of preferences, and tradeoff judgements."

The purpose of DM software is to support the analysis involved at these various stages of the decision-making process, not to replace it. DM software "should be used to support the process, not as the driving or dominating force."^[8]

DM software frees users "from the technical implementation details [of the decision-making method employed], allowing them to focus on the fundamental value judgements". Nonetheless, DM software 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."^[9]

Methods and features

Decision-making methods

As mentioned earlier, most DM software is based on multi-criteria decision making (MCDM). MCDM involves evaluating and combining alternatives' characteristics on two or more criteria or attributes in order to rank, prioritize or choose from among the alternatives.^[10]

There is currently a great deal of interest in quantitative methods for decision making. Many decision analysts argue for multi-attribute decision analysis as the gold standard to which other methods should be compared, based on its rigorous axiomatic basis. Some other MCDM methods include:

• Aggregated Indices Randomization Method (AIRM)
• Analytic Hierarchy Process (AHP)
• Analytic network process (ANP, an extension of AHP)
• DEX (Decision EXpert)
• Elimination and Choice Expressing Reality (ELECTRE)
• Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH)
• Multi-attribute global inference of quality (MAGIQ)
• Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA)
• Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE)
• Evidential reasoning approach for MCDM under hybrid uncertainty

There are significant differences between these methods and, accordingly, the DM software implementing them. Such differences include:

1. The extent to which the decision problem is broken into a hierarchy of sub-problems;

1. Whether or not pairwise comparisons of alternatives and/or criteria are used to elicit decision-makers' preferences;

1. The use of interval scale or ratio scale measurements of decision-makers' preferences;

1. The number of criteria included;

1. The number of alternatives evaluated, ranging from a few (finite) to infinite;

1. The extent to which numerical scores are used to value and/or rank alternatives;

1. The extent to which incomplete rankings (relative to complete rankings) of alternatives are produced;

1. The extent to which uncertainty is modeled and analyzed.

Software features

In the process of helping decision-makers to rank, prioritize or choose from among alternatives, DM software products often include a variety of features and tools; common examples include:

• Pairwise comparison
• Sensitivity analysis
• Group evaluation (teamwork)
• Web-based implementation

Comparison of decision-making software

DM software includes the following notable examples.

Software	Supported MCDA Methods	Pairwise Comparison	Sensitivity Analysis	Group Evaluation	Web-based
						^[11]
	MAUT, SMART
	AHP, SMART
	PROMETHEE, UTILITY
	MAUT
	SMART
	Evidential Reasoning Approach, Bayesian Inference, Dempster–Shafer theory, Utility				Available on request
						^[12]
						^[13]

A good summary of the capabilities of various software packages is available in the Decision Analysis Software Survey conducted by the Institute for Operations Research and the Management Sciences (INFORMS). The software packages listed in the survey range from free to commercial or enterprise-level packages.

See also

• Collaborative decision-making software
• List of concept- and mind-mapping software
• Project management software
• Strategic planning software

Notes and References

1. Dyer, JS (1973), "A time-sharing computer program for the solution of the multiple criteria problem", Management Science, 19: 1379-83.
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. Koksalan, M, Wallenius, J, and Zionts, S, Multiple Criteria Decision Making: From Early History to the 21st Century, World Scientific Publishing: Singapore, 2011.
4. Weistroffer, HR, and Li, Y, "Multiple criteria decision analysis software", Ch 29 in: Greco, S, Ehrgott, M and Figueira, J, eds, Multiple Criteria Decision Analysis: State of the Art Surveys Series, Springer: New York, 2016.
5. Oleson, S (2016), "Decision analysis software survey", OR/MS Today 43(5).
6. Amoyal, J (2018), "Decision analysis software survey", OR/MS Today 45(5).
7. Book: 10.1002/9781118644898. Multi-Criteria Decision Analysis. 2013. Ishizaka . A. . Nemery . P. . 9781118644898.
8. Belton, V, and Stewart, TJ, Multiple Criteria Decision Analysis: An Integrated Approach, Kluwer: Boston, 2002.
9. 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.
10. 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.
11. Web site: Archived copy . 2015-08-02 . 2015-05-26 . https://web.archive.org/web/20150526121007/http://create.usc.edu/sites/default/files/publications//dmsocialnetworkswithcover.pdf . dead .
12. 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
13. http://www.creativedecisions.org "www.creativedecisions.org"