How to Prioritize Projects Using Bubble Chart Pro™

You can also see the video "Project Ranking Using Bubble Chart Pro™ PLUS" by clicking here.

Project prioritization is a critical step in selecting which projects to start, continue, or stop. A value-maximizing and clearly understandable project ranking system is an essential part of a Project Portfolio Management system. It should be based in sound, quantitative, and modern decision-science.

This article will show exactly how to prioritize or rank your projects in a way that meets all these criteria using the built-in SMART (Simple Multi-Attribute Ranking Technique) project prioritization system.

When you’re done the prioritization, you'll see how the prioritization looks using bubble charts that plot the value score versus the project attributes such as the one in Figure 1. Here you can see that the most attractive projects are the low-cost and high-value-score projects in the upper-left quadrant and less-attractive projects are the high-cost and low-value score in the lower-right quadrant.

Figure 1. A prioritized project portfolio bubble chart. The projects are ranked by SMART value scores.

Figure 1. A prioritized project portfolio bubble chart. The projects are ranked by SMART value scores.

The built-in SMART project prioritization system was developed by researchers from MIT, Harvard, and the University of Southern California. This system allows you prioritize your projects in a way that integrates your key project data into a single value score that is clear, understandable and rigorously defensible.

In the SMART prioritization system, each project attribute (such as ROIs, risks, costs, etc.) is transformed onto a curve representing a “0” to “100” scale where “0” is the worst value (for example, lowest ROI or highest risk) and “100” is the best value (for example, highest ROI or lowest risk). These individual attribute scores are then weighted by the analyst and then summed to yield the overall SMART value score for each project in the portfolio.

"Numerous R&D projects within a small company with finite resources can be a real challenge to prioritize. Net Present Value (NPV) can be one method, however with the potentially endless parameters available within Bubble Chart Pro OPTIMAL, visualizing an entire portfolio from several different business perspectives is even more powerful. This unique tool has allowed our company to better allocate resources to projects that meet our management team s objectives and weed-out  those that don t. And, with the flexible parameter weighting, our prioritization methods can evolve as our company grows. The minimal cost of obtaining a license has already been offset just in helping to eliminate the focus from low-value projects."
Rich D., Project Development Manager in R&D, Agrichemicals Industry

You can also view your prioritized portfolio in project portfolio project ranking charts that automatically rank your projects against whatever variable you select for the Y-axis. In the project portfolio project ranking chart in Figure 2, the overall value score is plotted on the Y-axis and the bubble size is proportional to profit.

Figure 2. A prioritized project portfolio ranking chart. The projects are ranked by SMART value scores, and ranking is shown on the X-axis

Figure 2. A prioritized project portfolio ranking chart. The projects are ranked by SMART value scores, and ranking is shown on the X-axis. The bubble size represents project estimated profitability.

All you have to do is decide what project criteria or attributes are most important to your business and then weight each one by assigning values of relative importance to them. Here’s how easy that is to do in Bubble Chart Pro™:

(NOTE: Click here to learn an easy system for weighting your attibutes.)

1) In an un-prioritized portfolio, notice that all the project scores in the “Value Scores” column are “0” (Figure 3).

Figure 3. An un-prioritized project portfolio containing 20 projects.

Figure 3. An un-prioritized project portfolio containing 20 projects.

2) We’ll start by clicking on the top of a selected column to open an Attribute Form. In Figure 4, we have opened the attribute “Profit”. We are going to choose “Profit” as our most important attribute, so we’ll assign it a weight of “1000." The weight of an attributes determines its influence on the overall SMART value score of each project. We're going to move the slider to adjust the value (utility) curve to bias the attribute to higher profit projects. With this curve setting, the value score increases faster as profits get higher (an increasing return rate). Because we have the "Show Projects" check box selected, we can see the projects’ SMART value scores on the curve.

Figure 4. An attribute form for "Profit" with the SMART ranking weight set to 1000.

Figure 4. An attribute form for "Profit" with the SMART ranking weight set to 1000.

3) After we save it, notice how the SMART value score immediately appears in the “Value Score” column (Figure 5). Because we have only assigned a weight to a single attribute, the SMART value score rank order of the projects is identical to the ranking of the projects by "Profits":

Figure 5. A project portfolio with one weighted attribute.

Figure 5. A project portfolio with one weighted attribute.

4) Next we’ll click on the top of column “Cost” to open its Attribute Form. We are going assign “Cost” a weight of 800, meaning that “Cost” has 80% of the influence in the overall SMART score as “Profit” in our model. We’re also going to check the “Lower Values are Better” check box because lower cost projects are better that higher cost projects, and we'll use an "S-Curve" to represent the SMART score curve.

Figure 6. A S-Type (Logisitic) attribute curve. Note that the [Lower Attribute Values Are Better] check box is selected because lower costs and lower resource uses are more desirable and will contribute to higher SMART value scores.

Figure 6. A S-Type (Logistic) attribute curve for “Cost”. Note that the [Lower Attribute Values Are Better] check box is selected because lower costs and lower resource requirements are more desirable and will contribute to higher SMART value scores. This reverses the direction of the curve from low-to-high to high-to-low.

Next, we'll assign a weight of 400 to "Resources" and check the “Lower Values are Better” checkbox because lower resource requirements are better than higher resource requirements. Also, we”ve selected and modified a 5-Step incremental curve for this attribute.

Figure 7. A Step-Type (Incremental) attribute curve.

Figure 7. A Step-Type (Incremental) attribute curve.

5) Notice how the Value Scores have automatically recalculated (Figure 8) based on the addition of the weighted attributes “Cost” and "Resources" and how they are no longer ranked just by profit. Now the value scores reflect the weighted contribution of all three attributes: Profit, Cost, and Resources Required.

A project portfolio with three weighted attribute. Each attribute contributes to the overall SMART value score.

Figure 8. A project portfolio with three weighted attribute. Each attribute contributes to the overall SMART value score. Note that the assigned weights are displayed in the column headers.

Next, We’ll assign a weight of 500 to "Strategic Value" (Figure 9). We're going to use a "Category" attribute type and assign a SMART score value to each category.

Figure 9. Note the attribute "Strategic Value" attribute is of the "Categories" type with SMART value scores assigned to each category

For "Probability of Success" we’ll assign a weight of 750 and use a S-Type curve (Figure 10). By sliding the curve slightly to the right, we are biasing it to an increasing rate of return: projects with higher probabilities of success will have increasingly higher SMART value scores in the project portfolio.

Figure 10. The "Probability of Success" attribute with a modified S-Curve.

Figure 10. The "Probability of Success" attribute with a modified S-Curve.

7) And we’re done! Now we can see the SMART Value Score for each project and we can sort them by value score by clicking at the top of the Value Score column to see them in prioritized order (Figure 11).Now the value scores reflect the weighted contribution from all five attributes:

Figure 11. A project portfolio with 5 weighted attribute. The value scores represent the contribution of all 5 attributes.

Figure 11. A project portfolio with 5 weighted attribute. The SMART value scores represent the contribution of all 5 attributes.

8) By clicking on the [Calc.] button in the button-bar at the top of the form (Figure 11), we can see the contribution that each attribute makes to the total value score (Figure 12) . These numbers are called the “normalized weighted values,” and each project’s value score represents the sum of these individual values. Clicking the [Actual] button returns to the attribute data view (Figure 11).

Figure 12. A project portfolio showing the calculated weighted attributes for the individual projects.

Figure 12. A project portfolio showing the calculated weighted attributes for the individual projects. The project scores in the "Value" column is equal to the sum of the weighted attribute values in the corresponding column rows.

9) Now you can use these SMART Value Scores in your bubble charts! In the chart below, we can see that the most attractive projects are the largest bubbles in the upper left quadrant (higher value score, lower costs, higher profit) while the least attractive projects are the smallest projects in the lower right quadrant (lower value score, higher cost, lower profit):

Figure 13. A prioritized project portfolio bubble chart showing SMART values score versus Cost versus Profit.

Figure 13. A prioritized project portfolio bubble chart showing SMART values score versus Cost versus Profit.

10) You can also look at your portfolios in other dimensions to see how they compare. In the Figure 14, we can see that the most attractive projects are the largest bubbles in the upper left quadrant (higher profit, lower costs, higher probability of success) while the least attractive projects are the smallest projects in the lower right quadrant (higher cost, lower profit, and lower probability of success):

Figure 14. A prioritized project portfolio bubble chart showing Profit versus Cost versus %Probability of Success.

Figure 14. A prioritized project portfolio bubble chart showing Profit versus Cost versus %Probability of Success.

11) Bar charts are another useful way to see this kind of data, and Bubble Chart Pro™ has them built-in so you can make them in a couple of clicks. The different stacked bar charts in Figure 15 let you see the raw project data and compare it to the weighted attribute data.

Figure 15. Prioritized project portfolio bar charts show the relationships between project attribute values and weighted attribute values.

Figure 15. Prioritized project portfolio bar charts show the relationships between project attribute values and weighted attribute values.

12) Another useful high-level tool in project prioritization is sensitivity analysis. Sensitivity analysis allows you to understand what happens if an attribute value changes or if you change the weight of an attribute. Figure 16 displays two sensitivity charts: the foreground chart is an attribute sensitivity test for cost and the background chart is an attribute weight sensitivity chart. The location of the bubbles represent the current locations of the projects relative to the X- and Y-axes. The lines represent potential changes in SMART value scores for each project if their X-axis value changes. These charts are created in just a couple clicks in Bubble Chart Pro™ PLUS and Bubble Chart Pro™ OPTIMAL.

Figure 16. Two prioritized project portfolio sensitivity testing charts.

Figure 16. Two prioritized project portfolio sensitivity testing charts.

13) Attribute Sensitivity Testing: In Figure 17, two projects have been isolated: Project Scorpio and Project Taurus. Note how the slope of the lines Indicates that as the Cost (X-axis) go up, the project SMART value scores go down. In this example, we can see that if the cost of Project Taurus were reduced to below 5,000, it would have a SMART value score higher than Project Scorpio.

Figure 17. Example of attribute sensitivity testing of two projects in a prioritized project portfolio.

Figure 17. Example of attribute sensitivity testing of two projects in a prioritized project portfolio.

14) Weight Sensitivity Testing: In Figure 18, two projects have been isolated: Project Scorpio and Project Taurus. Their current location along the X-axis indicates the current assigned weight for the attribute "Cost" of 800. If the cost weight were changed to less than 500, then Project Taurus would have a higher SMART value score than Project Scorpio.

Figure 18. Example of attribute weight sensitivity testing of two projects in a prioritized project portfolio.

Figure 18. Example of attribute weight sensitivity testing of two projects in a prioritized project portfolio.

So now you can see that the SMART prioritizer in Bubble Chart Pro™ is a fast and powerful way to prioritize your projects and visualize the results. We recommend starting with a small group of projects to try different weighting combinations so you can develop a set that prioritizes the small group close to the way you would do it manually. Then you can have confidence in the ranking when you add more projects.

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