Decision-making software

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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.

Contents

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, [2] 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. [4] Thus most DM software is based on decision analysis, usually multi-criteria decision-making, and so is often referred to as "decision analysis" [5] [6] or "multi-criteria decision-making" [4] 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." [4]

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". [8] 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 [8] include:

There are significant differences between these methods [8] [10] 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;
  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 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; [3] [4] common examples include:

Comparison of decision-making software

DM software includes the following notable examples.

SoftwareSupported MCDA MethodsPairwise ComparisonSensitivity AnalysisGroup EvaluationWeb-based
1000minds PAPRIKA YesYesYesYes [4] [5] [6]
Ahoona WSM, Utility NoNoYesYes [11]
Altova MetaTeam WSM NoNoYesYes[ citation needed ]
Analytica MAUT, SMARTNoYesNoYes [4] [5]
Criterium DecisionPlus AHP, SMARTYesYesNoNo [4]
D-Sight PROMETHEE, UTILITYYesYesYesYes [4] [5]
DecideIT MAUTYesYesYesYes [4] [5]
Decision Lens AHP, ANP YesYesYesYes[ citation needed ]
Expert Choice AHP YesYesYesYes [4] [5]
Hiview3 SMARTNoYesYesNo [4] [5]
Intelligent Decision System Evidential Reasoning Approach, Bayesian Inference, Dempster–Shafer theory, UtilityYesYesYesAvailable on request [5]
Logical Decisions AHP YesYesYesNo [4] [5] [6]
M-MACBETH MACBETH YesYesYesNo [4]
PriEsT AHP YesYesNoNo [12]
Super Decisions AHP, Analytic Network Process YesYesNoYes [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

Related Research Articles

<span class="mw-page-title-main">Multiple-criteria decision analysis</span> Operations research that evaluates multiple conflicting criteria in decision making

Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making. It is also known as multiple attribute utility theory, multiple attribute value theory, multiple attribute preference theory, and multi-objective decision analysis.

<span class="mw-page-title-main">Analytic hierarchy process</span> Structured technique for organizing and analyzing complex decisions

In the theory of decision making, the analytic hierarchy process (AHP), also analytical hierarchy process, is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. It was developed by Thomas L. Saaty in the 1970s; Saaty partnered with Ernest Forman to develop Expert Choice software in 1983, and AHP has been extensively studied and refined since then. It represents an accurate approach to quantifying the weights of decision criteria. Individual experts’ experiences are utilized to estimate the relative magnitudes of factors through pair-wise comparisons. Each of the respondents compares the relative importance of each pair of items using a specially designed questionnaire. The relative importance of the criteria can be determined with the help of the AHP by comparing the criteria and, if applicable, the sub-criteria in pairs by experts or decision-makers. On this basis, the best alternative can be found.

Pairwise comparison generally is any process of comparing entities in pairs to judge which of each entity is preferred, or has a greater amount of some quantitative property, or whether or not the two entities are identical. The method of pairwise comparison is used in the scientific study of preferences, attitudes, voting systems, social choice, public choice, requirements engineering and multiagent AI systems. In psychology literature, it is often referred to as paired comparison.

Multi-objective optimization or Pareto optimization is an area of multiple-criteria decision making that is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. Multi-objective is a type of vector optimization that has been applied in many fields of science, including engineering, economics and logistics where optimal decisions need to be taken in the presence of trade-offs between two or more conflicting objectives. Minimizing cost while maximizing comfort while buying a car, and maximizing performance whilst minimizing fuel consumption and emission of pollutants of a vehicle are examples of multi-objective optimization problems involving two and three objectives, respectively. In practical problems, there can be more than three objectives.

ÉLECTRE is a family of multi-criteria decision analysis (MCDA) methods that originated in Europe in the mid-1960s. The acronym ÉLECTRE stands for: ÉLimination Et Choix Traduisant la REalité.

The superiority and inferiority ranking method is a multi-criteria decision making model (MCDA) which can handle real data and provides six different preference structures for the system user. MCDM is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making, both in daily life and in settings such as business, government and medicine.

This is a worked-through example showing the use of the analytic hierarchy process (AHP) in a practical decision situation.

The decision-making paradox is a phenomenon related to decision-making and the quest for determining reliable decision-making methods. It was first described by Triantaphyllou, and has been recognized in the related literature as a fundamental paradox in multi-criteria decision analysis (MCDA), multi-criteria decision making (MCDM) and decision analysis since then.

In decision-making, a rank reversal is a change in the rank ordering of the preferability of alternative possible decisions when, for example, the method of choosing changes or the set of other available alternatives changes. The issue of rank reversals lies at the heart of many debates in decision-making and multi-criteria decision-making, in particular.

Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) is a method for multi-criteria decision making (MCDM) or conjoint analysis, as implemented by decision-making software and conjoint analysis products 1000minds and MeenyMo.

The Preference Ranking Organization METHod for Enrichment of Evaluations and its descriptive complement geometrical analysis for interactive aid are better known as the Promethee and Gaia methods.

<span class="mw-page-title-main">European Working Group on Multiple Criteria Decision Aiding</span>

The European Working Group on Multiple Criteria Decision Aiding is a working group whose objective is to promote original research in the field of multicriteria decision aiding at the European level.

In multiple criteria decision aiding (MCDA), multicriteria classification involves problems where a finite set of alternative actions should be assigned into a predefined set of preferentially ordered categories (classes). For example, credit analysts classify loan applications into risk categories, customers rate products and classify them into attractiveness groups, candidates for a job position are evaluated and their applications are approved or rejected, technical systems are prioritized for inspection on the basis of their failure risk, clinicians classify patients according to the extent to which they have a complex disease or not, etc.

DecideIT is a decision-making software for the Microsoft Windows operating system. It is based on multi-criteria decision making (MCDM) and the multi-attribute value theory (MAVT). It supports both value tree analysis for multi-attribute decision problems as well as decision tree analysis for evaluating decisions under risk and can combine these structures in a common model.

The VIKOR method is a multi-criteria decision making (MCDM) or multi-criteria decision analysis method. It was originally developed by Serafim Opricovic to solve decision problems with conflicting and noncommensurable criteria, assuming that compromise is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. VIKOR ranks alternatives and determines the solution named compromise that is the closest to the ideal.

D-Sight is a company that specializes in decision support software and associated services in the domains of project prioritization, supplier selection and collaborative decision-making. It was founded in 2010 as a spin-off from the Université Libre de Bruxelles (ULB). Their headquarters are located in Brussels, Belgium.

PriEsT is an acronym for 'Priority Estimation Tool' which is an open-source decision-making software that implements the Analytic Hierarchy Process (AHP) method - a comprehensive framework for decision problems. PriEsT can assist decision makers in prioritizing the options available in a given scenario.

DEX is a qualitative multi-criteria decision analysis (MCDA) method for decision making and is implemented in DEX software. This method was developed by a research team led by Bohanec, Bratko, and Rajkovič. The method supports decision makers in making complex decisions based on multiple, possibly conflicting, attributes. In DEX, all attributes are qualitative and can take values represented by words, such as “low” or “excellent”. Attributes are generally organized in a hierarchy. The evaluation of decision alternatives is carried out by utility functions, which are represented in the form of decision rules. All attributes are assumed to be discrete. Additionally, they can be preferentially ordered, so that a higher ordinal value represents a better preference.

Best Worst Method (BWM) is a multi-criteria decision-making (MCDM) method that was proposed by Dr. Jafar Rezaei in 2015. The method is used to evaluate a set of alternatives with respect to a set of decision criteria. The BWM is based on pairwise comparisons of the decision criteria. That is, after identifying the decision criteria by the decision-maker (DM), two criteria are selected by the DM: the best criterion and the worst criterion. The best criterion is the one that has the most important role in making the decision, while the worst criterion has the opposite role. The DM then gives his/her preferences of the best criterion over all the other criteria and also his/her preferences of all the criteria over the worst criterion using a number from a predefined scale. These two sets of pairwise comparisons are used as input for an optimization problem, the optimal results of which are the weights of the criteria. The salient feature of the BWM is that it uses a structured way to generate pairwise comparisons which leads to reliable results.

Ordinal priority approach (OPA) is a multiple-criteria decision analysis method that aids in solving the group decision-making problems based on preference relations.

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 4 5 6 7 8 9 10 11 12 13 14 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. 1 2 3 4 5 6 7 8 9 10 Oleson, S (2016), "Decision analysis software survey", OR/MS Today 43(5).
  6. 1 2 3 4 Amoyal, J (2018), "Decision analysis software survey", OR/MS Today 45(5).
  7. ↑ Ishizaka, A.; Nemery, P. (2013). Multi-Criteria Decision Analysis. doi:10.1002/9781118644898. ISBN   9781118644898.
  8. 1 2 3 4 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. 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.
  11. ↑ "Archived copy" (PDF). Archived from the original (PDF) on 2015-05-26. Retrieved 2015-08-02.{{cite web}}: CS1 maint: archived copy as title (link)
  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. ↑ "www.creativedecisions.org"
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