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. Prior to the advent of the World Wide Web, most DMS was spreadsheet-based, with the first web-based DMS appearing in the mid-1990s. Nowadays, at least 20 DMS products (mostly web-based) are available.
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.
DMS is a tool that is intended to support the analysis involved in decision-making processes, not to replace it. "DMS should be used to support the process, not as the driving or dominating force." 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". 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."
Methods and features
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.
DMS employs a variety of MCDM methods; popular examples include (and see the table below):
- Aggregated Indices Randomization Method (AIRM)
- Analytic Hierarchy Process (AHP)
- Analytic network process (ANP, an extension of AHP)
- 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)
- The Evidential reasoning approach for MCDM under hybrid uncertainty
- The extent to which the decision problem is broken into a hierarchy of sub-problems;
- Whether or not pairwise comparisons of alternatives and/or criteria are used to elicit decision-makers' preferences;
- The use of interval scale or ratio scale measurements of decision-makers' preferences;
- The number of criteria included;
- The number of alternatives evaluated, ranging from a few (finite) to infinite;
- The extent to which numerical scores are used to value and/or rank alternatives;
- The extent to which incomplete rankings (relative to complete rankings) of alternatives are produced;
- The extent to which uncertainty is modeled and analyzed.
- Time analysis and time optimization
- Sensitivity analysis and fuzzy logic calculations
- Risk aversion measurement
- Group evaluation (teamwork)
- Graphic or visual presentation tools
Comparison of decision-making software
Notable software includes the following.
|Software||Supported MCDA Methods||Pairwise Comparison||Sensitivity Analysis||Group Evaluation||Web-based|
|Altova MetaTeam||WSM||No||No||Yes||Yes|||
|Criterium DecisionPlus||AHP, SMART||Yes||Yes||No||No|||
|Decision Lens||AHP, ANP||Yes||Yes||Yes||Yes|||
|Super Decisions||AHP, Analytic Network Process||Yes||Yes||No||Yes|||
|Intelligent Decision System||Evidential Reasoning Approach, Bayesian Inference, Dempster–Shafer theory, Utility||Yes||Yes||Yes||Available on request|||
- Decision engineering
- Decision support system
- Project management software
- List of concept- and mind-mapping software
- Strategic planning software
- Dyer, JS (1973), "A time-sharing computer program for the solution of the multiple criteria problem", Management Science, 19: 1379-83.
- 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.
- Koksalan, M, Wallenius, J, and Zionts, S, Multiple Criteria Decision Making: From Early History to the 21st Century, World Scientific Publishing: Singapore, 2011.
- 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.
- McGinley, P (2014), "Decision analysis software survey", OR/MS Today 41(5).
- Ishizaka, A.; Nemery, P. (2013). "Multi-Criteria Decision Analysis". doi:10.1002/9781118644898. ISBN 9781118644898.
- Belton, V, and Stewart, TJ, Multiple Criteria Decision Analysis: An Integrated Approach, Kluwer: Boston, 2002.
- 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.
- 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.
- 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.
- 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