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Introduction to Multi-Criteria Decision-Making and 1000minds

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About this lesson

Define Multi-Criteria Decision-Making terminology and get an overview of the decision-making process using the 1000minds software.

Exercise files

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Introduction to Multi-Criteria Decision-Making and 1000minds
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Introduction to Multi-Criteria Decision-Making and 1000minds - Solution
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Quick reference

Introduction to Multi-Criteria Decision-Making and 1000minds

Define Multi-Criteria Decision-Making terminology and get an overview of the decision-making process using the 1000minds software.

When to use

When you are new to Multi-Criteria Decision-Making or 1000minds, or just want to brush up on the terminology and the 1000minds decision-making process.

Instructions

Multi-Criteria Decision-Making (MCDM)

  • A method used to prioritize or choose from a variety of different alternatives, or options, based on multiple criteria.
  • Examples: choosing which patient to prioritize for hospital treatment; choosing a new house; selecting which project to invest money in
  • Also known as Multi-Criteria Decision Analysis (MCDA)

Alternatives

  • The options that you are ranking or choosing between
  • Example: In the case of buying a new house, the alternatives would be the different houses you're considering.

Criteria

  • What it is that matters to you when deciding between different alternatives
  • Example: In the case of buying a new house, your criteria could be the design, number of rooms, and view

Levels

  • The different categories in each criterion
  • Example: A view might be "poor", "OK", or "great". Here, "poor", "OK", and "great" are your levels for this criterion.

Trade-offs

  • A series of questions where you have to choose between two hypothetical alternatives, each defined on different levels of two criteria. Each question requires you to make a trade-off.
  • Example: "Do you prefer a house with a great view, but ugly design, or a house with a poor view, but excellent design?"
  • Trade-offs can be done at any time after specifying your criteria. 

Preference values

  • Percentages that represent the relative importances of your criteria (i.e. how much each of your criteria matters to you relative to each other)
  • These values are determined by the trade-offs you make

Ranked alternatives

  • Your alternatives that are scored and ranked according to how they performed on each criterion
  • The scoring and ranking is done using the preference values of your criteria

Costs and other considerations

  • Any factors that are negative or neutral that you want to factor into your decision and weigh against your criteria; or any arbitrary information that you want to store
  • Examples: cost, neighborhood, sector, risk level, product URL, contact information
  • These can be analyzed alongside your alternative score using the value-for-money chart in 1000minds
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  • 00:05 So what is multi-criteria decision-making?
  • 00:09 MCDM as it is often called, or also known as multi-criteria decision analysis
  • 00:14 is a method used to prioritize, rank, or choose from a variety
  • 00:20 of different alternatives or options based on multiple criteria.
  • 00:25 For example, you might think about which patients to prioritize for
  • 00:31 treatment at a hospital or which project to invest money in.
  • 00:36 Or maybe you're thinking about something more personal like buying a new house.
  • 00:41 In MCDM, the options that you're ranking or
  • 00:44 choosing between are referred to as your alternatives.
  • 00:48 In the case of looking at a different house to buy,
  • 00:52 your alternatives would be the houses.
  • 00:54 When buying a house, you have several different things to consider.
  • 00:58 Like how many bedrooms that house has, what the view is like,
  • 01:03 whether or not you like to design, and whatever else you care about.
  • 01:08 These things are referred to as your criteria,
  • 01:11 which is what matters to you when choosing between different alternatives.
  • 01:16 Then for each criterion, you have to specify different levels.
  • 01:21 So for example, a view might be poor, okay, or great.
  • 01:26 Or the design might be ugly, okay, or excellent.
  • 01:31 After you've specified your criteria, 1000minds will ask you a series of
  • 01:36 questions where you have to choose between two hypothetical alternatives.
  • 01:41 The questions will be something like, do you prefer a house with a nice view but
  • 01:46 ugly design or a house with a poor view but excellent design?
  • 01:51 In other words, you always have to make a trade off.
  • 01:54 This step is therefore appropriately referred to as your trade-offs.
  • 02:00 1000minds uses the trade-offs you make to determine how much each
  • 02:04 of your criteria matters to you.
  • 02:07 These weights or relative importances are called preference values.
  • 02:12 Then your alternatives will be scored and ranked according to these preference values
  • 02:17 and the alternatives' performance on each criterion.
  • 02:21 You can add alternatives either before or after making trade-offs.
  • 02:26 But your perfect alternative might not be the one with the highest ranking.
  • 02:31 Maybe you found the ideal house, but the cost is way beyond your budget.
  • 02:36 If you specify the costs under costs and other considerations,
  • 02:41 you can use the value-for-money chart to analyze them alongside the alternative
  • 02:46 score and choose an alternative that is more suitable for you.
  • 02:51 You can use other considerations for any factors that are either negative or
  • 02:56 neutral such as a house price or what neighborhood it's located in.
  • 03:01 Or you can even use other considerations to store arbitrary information,
  • 03:07 such as the address of each house that you're considering.
  • 03:11 1000minds breaks down complex decision-making into these simple steps,
  • 03:16 so that you can enjoy making better decisions.
  • 03:19 And if you need any help, we're always here for you.
  • 03:23 Let 1000minds show you a better way to decide.

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Projects, Decisions, and Surveys
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