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Grid Analysis for Time Management

When you have a number of good options to consider and a number of factors that could influence the decision, you may need a prioritization tool that is more complex than the paired comparison grid. In these cases, a grid analysis is a useful tool for making decisions or prioritizing your work.

To begin, you’ll create another grid. This time the options will be the rows and the factors that will affect your prioritization will be the column headings. You will then assign a score and a weight to each pairing in order to get an overall score for each option. Let’s use an example for this grid analysis of prioritizing which firm to use as a marketing consultant. See below Figure for the example grid.
Now that your grid is ready, you need to assign a weight to each factor so that you know which factors are most important and which are less important. Use zero if the factor isn’t important at all and five for the most important factor or factors. You can have more than one factor with the same score. Write the weight in the ‘weight’ row in your grid.

Next you will start with the first column, in this case cost. Go down the column and rate each option on this factor with a number from zero for poor to five for excellent. Then move on to the next column and complete the same rating, repeating this step until the columns are all completed.


To calculate the results, you take the rating that you gave the consulting firm for a category and multiply it by the weight factor. For example, ABC Consulting was rated a ‘3’ on cost, which has a weight factor of ‘5’. Simply multiply 3 by 5 for a score of 15 for this category for ABC Consulting. Once you have all of the scores tabulated, you add the scores across each factor to get a total score for each option.


In this case, the ‘winner’ is XYZ Consulting. When you present your recommendations for a consulting firm, you can now demonstrate a logical reason for the recommendation and even discuss the different factors individually should someone want to remove a factor from consideration.


     


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