Comparing Alternatives

Comparing Alternatives

Definition:

Every project team should consider multiple alternative options prior to making a recommendation. Comparing alternatives is how a team selects between the alternatives.

What it is: Every set of alternatives can be compared by either a quantifiable financial analysis or a subjective qualitative analysis. We will look at both options in this tool. Alternatives can be identified by the team considering many alternative approaches to solving the problem or opportunity presented to the team.
What does it do: The comparative analysis provides an authoritative method to determine which alternative is optimum for meeting the needs of the project sponsor.

Uses:

How is it used: Once a series of alternatives have been identified, the comparative analysis allows for an authoritative approach to making a decision of which alternative to select. Without a defined method, the decision is made from a contest of wills, opinions, and the intensity of the argument. These are never a good approach to make a decision.
Where: Anytime there is a defined desired outcome, then we can make a comparative analysis to see which alternatives best deliver the desired outcome.
Why: Because you have to make a decision, and to avoid arguments, and maximize the impact of the decision, a process will help facilitate the desired outcome.

Limitations:

Where it shouldn't be used: When a decision has already been made, and the decision-maker does not want their decision to be challenged
Any restrictions: You can only use this process when there is a defined preferred outcome to compare the alternatives against.
Warnings: Defining the desired outcome is critical because the comparative analysis will try to optimize the decision to coincide with the desired outcome. But if you have selected the wrong outcome (like selecting revenue instead of profit), you may come out with an answer that will bankrupt you, because you are maximizing the wrong factor.

Demonstrations:

Step-by-step process:

For the Financial Analysis tools, you create a Financial Modeling and measure each alternative with NPV, IRR, Total Profit, or Efficient Frontier. Check the various approaches found under Financial Analysis tools.

For the Decision Matrix use the following steps from MindTools:

Decision Matrix Analysis works by getting you to list your options as rows on a table, and the factors you need to consider as columns. You then score each option/factor combination, weight this score by the relative importance of the factor, and add these scores up to give an overall score for each option.

While this sounds complex, this technique is actually quite easy to use. Here's a step-by-step guide to an example. Start by downloading our free worksheet Then work through these steps.

Step 1: List all of your options as the row labels on the table, and list the factors that you need to consider as the column headings. For example, if you were buying a new laptop, factors to consider might be cost, dimensions, and hard disk size.

Step 2: Next, work your way down the columns of your table, scoring each option for each of the factors in your decision. Score each option from 0 (poor) to 5 (very good). Note that you do not have to have a different score for each option – if none of them are good for a particular factor in your decision, then all options should score 0.

Step 3: The next step is to work out the relative importance of the factors in your decision. Show these as numbers from, say, 0 to 5, where 0 means that the factor is absolutely unimportant in the final decision, and 5 means that it is very important. (It's perfectly acceptable to have factors with the same importance.):

Step 4: Now multiply each of your scores from step 2 by the values for the relative importance of the factor that you calculated in step 3. This will give you weighted scores for each option/factor combination.

Step 5: Finally, add up these weighted scores for each of your options. The option that scores the highest wins!

From Mind Tools: Decision Matrix Analysis