Decision matrix
A decision matrix, also known as a "decision-making matrix" or a "evaluation matrix," is a tool used to evaluate and prioritize different options or alternatives. It is a table that is used to compare and evaluate different options based on a set of criteria, and is often used in project management and strategic planning. The matrix typically includes a list of options, a list of criteria, and a scoring system for evaluating each option based on the criteria. The scores are then used to rank or prioritize the options, making it easier for decision-makers to choose the best course of action.
How to create decision matrix?
The procedure is as follows:
- Identify the options: Clearly define the different options or alternatives that you are considering.
- Define the criteria: Determine the factors that are important to the decision. These could include cost, feasibility, impact, and so on.
- Assign weights to the criteria: Prioritize the criteria by assigning a weight to each one, based on its importance to the decision.
- Score each option: For each option, evaluate how well it meets each criterion. This can be done using a scale, such as a 1-10 rating, or a simple pass/fail assessment.
- Multiply the scores by the weight: Multiply the score for each option by the weight assigned to the corresponding criterion.
- Sum the weighted scores: Add up the weighted scores for each option to get a total score.
- Compare and evaluate: Compare the total scores for each option, and use them to evaluate and prioritize the options.
- Choose a course of action: Based on the evaluation, choose the best course of action.
It is important to note that decision matrix are only one of the many tools to make a decision and should be used in conjunction with other tools and methods to make a well-informed decision.
Example of decision matrix
Here is an example of a simple decision matrix that could be used to evaluate different job candidates:
| Criteria | Candidate A | Candidate B | Candidate C |
|---|---|---|---|
| Experience | 5 | 4 | 3 |
| Education | 4 | 3 | 4 |
| Skills | 4 | 5 | 4 |
| Interview | 3 | 4 | 5 |
In this example, the options being considered are three job candidates (A, B, and C). The criteria being used to evaluate the candidates are experience, education, skills, and interview performance.
Each candidate is scored on a scale of 1 to 5 for each criterion, with 5 being the best possible score.
The scores can be multiplied by the weight assigned to each criterion to give the final score. For example, if experience is considered the most important, it could be assigned a weight of 2, education 1.5, skills 1.5 and interview 1.
The final score for each candidate can be calculated by adding up the weighted scores.
- Candidate A: (5 x 2) + (4 x 1.5) + (4 x 1.5) + (3 x 1) = 23
- Candidate B: (4 x 2) + (3 x 1.5) + (5 x 1.5) + (4 x 1) = 22.5
- Candidate C: (3 x 2) + (4 x 1.5) + (4 x 1.5) + (5 x 1) = 22
In this example, Candidate A would have the highest score and therefore be considered the best candidate for the job.
| Decision matrix — recommended articles |
| Analytic hierarchy process — Expected monetary value — Kendall coefficient of concordance — Comparative analysis — Level of complexity — Analytic network process — RAROC — Accounting rate of return — Project evaluation methods |
References
- Salmerona, J. L., & Smarandacheb, F. (2010). Redesigning Decision Matrix Method with an indeterminacy-based inference process. Multispace and Multistructure. Neutrosophic Transdisciplinarity (100 Collected Papers of Sciences), 4, 151.
- Kou, G., Ergu, D., & Shang, J. (2014). Enhancing data consistency in decision matrix: Adapting Hadamard model to mitigate judgment contradiction. European Journal of Operational Research, 236(1), 261-271.
- Ghorbanzadeh, O., Feizizadeh, B., & Blaschke, T. (2018). An interval matrix method used to optimize the decision matrix in AHP technique for land subsidence susceptibility mapping. Environmental Earth Sciences, 77(16), 1-19.
