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MindDecider is lucky to find its own niche among similar decision making tools. The competitors are either too simple to face complex life issues or too math-packed and time-consuming to be intuitive. We hope that MindDecider will make your everyday and business life much easier!
S.Roodchenko, software designer and project director

Decision making process

Decision making process in steps

Commonly, decision making process is based on two main techniques: multi-criteria decision analysis (MCDA) and Analytic Hierarchy Process (AHP). Using these techniques a problem solving process can be structured into the following steps:

  1. Statement of a decision task (or decision problem) which involves several variants or choices. For example, if you have $10000 on your card and do not know what to do with them, the task may sound as "where to invest?"
    Decision making process: state a decision problem or decision task
  2. Entering variants or alternatives. These can be open, i.e. new options and alternatives may be possibly discovered and added by a decision maker, or closed, with the limited number of choices. In our example, we enter 6 variants assuming possible enhance to them: buying shares or stocks, depositing, ForEx trading, real estate purchase, getting education and setting up business.
    Decision making process: generate alternatives or options
    These options may be further decomposed into a hierarchy of elements, each of which is analyzed independently (see mind mapping page on this site). For example, setting up a business may include starting a greenfield project, purchase of a ready business or purchase of a franchise.
    Decision making process: task decomposition - simple hierarchy
  3. Identifying criteria or attributes for the created variants. Such criteria can be either positive (the more the better) or negative (the less the better). Criteria may be set for all the variants at once or for each variant or a tree branch independently. Some criteria are measurable or numeric, but some are non-numeric and relate to specific states (good, average, poor) or subjective perceptions by a decision-maker (look, design, experience, etc). Attributes can also be ranked according to their significances, i.e. the most important ones are in the top, the least in the bottom. In the investment task the following attributes may be applied: return on money, risk degree, money withdrawal possibility, need of special knowledge or experience.
    Alternatives: return on money, risk degree, money withdrawal, special knowledge
  4. Evaluation of variants using concrete data for the elements or personal judgements about the elements' relative meanings and importance. For numeric attributes the estimates can be entered either directly into the input field or via mouse-controlled bar:
    Estimates in Plan mode

    Decision making process: editing estimates directly or via green bar

    Sometimes a decision-maker acts under uncertainty conditions, that is, the exact value of an attribute is unknown but a range or an interval of possible meanings can still be found. In such a case fuzzy calculations are of great help. For example, it is always hard to tell exactly how much money you will earn in future when you finish your education and get a more profitable job:
    Decision making process: fuzzy calculations, entering intervals for attributes

    For non-numeric criteria such as risk degree, for example, a special pairwise comparison (balancing) option is offered. A decision maker is asked to judge between pairs of elements and thus to determine their relative order (ranking):
    Decision making process: pairwise comparison (fast or precision balancing procedures)
  5. Processing of numerical estimates for each of the decision alternatives according to their weights and importance ratios. The result of decision making process is a final rate of an object which is calculated by the following general formula:
    Rate =
     significancei *
    estimatei - min.estimatei

    A root item (main task or another object with children) may process the data from its branches by several methods: choice of the best (worst) variant, summation of estimates, calculation of average meaning, probability, finding max or min possible alternative. In our case we need to find the best choice for investment of money resources:
    Report mode - brief statistics on compared variants, reasoning of the best or worst choice

Why special software should be used to facilitate decision making process?

  • unlimited number of alternatives;
  • cost savings;
  • time savings;
  • unbiased and rational decisions;
  • effective teamwork;
  • effective data management;
  • visual presentation of results.

Generally, the whole decision making process takes up to several minutes in a simplest case and may reach hours in most complex and multivariant tasks. In any case the program saves up to 80% of worktime and enormous amount of money and resources which could be wasted in a case of a wrong choice.

You may find extra information on decision making process and theory on our links and reading page.

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