Project ranking is at the heart of project portfolio management (PPM). A good project portfolio ranking system should not only make the job much easier and faster but also yield a superior result over doing it manually or with simple spreadsheets.
Almost every project portfolio management system comes with its own "twist" on project ranking: some are excellent, some are good, and some are poor or just wrong.
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.
Here some key things to consider about project portfolio ranking systems:
Avoid systems that rank based on a financial metrics alone, such as net present value (NPV) or return on investment (ROI). The major limitation of using purely financial metrics is that it can under estimate the true value of projects (e.g., time to market advantages or increased shareholder value). With NPV, higher discount rates selected to account for higher project risk can bias portfolios toward shorter-term projects with faster payoffs because longer-term projects may be overly discounted.
Look for systems that prioritize based on the integration of value-adding criteria into the ranking system. Systems that use multi-criteria decision analysis (MCDA) or multi-attribute utility theory (MAUT) usually do this. However, make sure you have flexibility in the type of data you can use and that you can adjust the utility or attractiveness curves to reflect your preferences.
Avoid systems that use the Analytic Hierarchy Process (AHP) for project ranking. AHP is one of the more popular project ranking techniques and is appealing by its seeming simplicity; however, it is not a quantitatively sound technique for ranking projects.
Look for systems that let you test sensitivity and understand how the portfolio changes under different scenarios.
Sensitivity testing can be important in testing the robustness of your ranking. Most systems only let you rank based on a "most-likely" scenario.
Select a system that can handle uncertainty in the data and the ranking systems parameters. Systems that use Monte-Carlo simulations to simulate multiple portfolio scenarios automatically are ideal for this.
Avoid systems that rank projects based solely on pseudo-quantitative methods like "balance" or "portfolio alignment," or other non-value maximizing approach. While these names may sound intuitive and appealing, most are pure snake-oil when it comes to solid project portfolio ranking. They do not create value-maximizing portfolios.
Look for systems that have clear and understandable graphical presentations of the data, but remember that pretty charts are not a substitute for sound data analysis. If you need too many charts to explain your results then you'll likely confuse your stakeholders.
Choose systems that have mathematically and theoretically sound methods. Be sure that you can understand qualitatively how it works and that you can explain it to others (because you'll surely need to later!).
Avoid vendors that will not or cannot show you the underlying mathematics and explain to you in plain language how it maximizes portfolio value.
Before you buy, try the software you have selected on a small portfolio of 12 - 20 real or fictional projects using metrics that you expect to be using. The application should prioritize the projects in a way that is understandable and makes sense to you. If it does not, then there may be something wrong in the underlying logic. A portfolio ranking system is an aid to good decision-making, and should reflect your values and strategies.
In summary, be sure that the underlying ranking methodology is sound and testable. Be aware of tools that use pseudo-quantitative methods for project ranking or do not offer any methodology for sensitivity testing. Make sure that you can test the tool on a small project portfolio so you can be certain you understand the results.
Almost every project portfolio management system comes with its own "twist" on project ranking: some are excellent, some are good, and some are poor or just wrong.
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.
Here some key things to consider about project portfolio ranking systems:
Avoid systems that rank based on a financial metrics alone, such as net present value (NPV) or return on investment (ROI). The major limitation of using purely financial metrics is that it can under estimate the true value of projects (e.g., time to market advantages or increased shareholder value). With NPV, higher discount rates selected to account for higher project risk can bias portfolios toward shorter-term projects with faster payoffs because longer-term projects may be overly discounted.
Look for systems that prioritize based on the integration of value-adding criteria into the ranking system. Systems that use multi-criteria decision analysis (MCDA) or multi-attribute utility theory (MAUT) usually do this. However, make sure you have flexibility in the type of data you can use and that you can adjust the utility or attractiveness curves to reflect your preferences.
Avoid systems that use the Analytic Hierarchy Process (AHP) for project ranking. AHP is one of the more popular project ranking techniques and is appealing by its seeming simplicity; however, it is not a quantitatively sound technique for ranking projects.
Look for systems that let you test sensitivity and understand how the portfolio changes under different scenarios.
Sensitivity testing can be important in testing the robustness of your ranking. Most systems only let you rank based on a "most-likely" scenario.
Select a system that can handle uncertainty in the data and the ranking systems parameters. Systems that use Monte-Carlo simulations to simulate multiple portfolio scenarios automatically are ideal for this.
Avoid systems that rank projects based solely on pseudo-quantitative methods like "balance" or "portfolio alignment," or other non-value maximizing approach. While these names may sound intuitive and appealing, most are pure snake-oil when it comes to solid project portfolio ranking. They do not create value-maximizing portfolios.
Look for systems that have clear and understandable graphical presentations of the data, but remember that pretty charts are not a substitute for sound data analysis. If you need too many charts to explain your results then you'll likely confuse your stakeholders.
Choose systems that have mathematically and theoretically sound methods. Be sure that you can understand qualitatively how it works and that you can explain it to others (because you'll surely need to later!).
Avoid vendors that will not or cannot show you the underlying mathematics and explain to you in plain language how it maximizes portfolio value.
Before you buy, try the software you have selected on a small portfolio of 12 - 20 real or fictional projects using metrics that you expect to be using. The application should prioritize the projects in a way that is understandable and makes sense to you. If it does not, then there may be something wrong in the underlying logic. A portfolio ranking system is an aid to good decision-making, and should reflect your values and strategies.
In summary, be sure that the underlying ranking methodology is sound and testable. Be aware of tools that use pseudo-quantitative methods for project ranking or do not offer any methodology for sensitivity testing. Make sure that you can test the tool on a small project portfolio so you can be certain you understand the results.
Looking for project management system, contact Alenu Now! at (65) 6884 5030.
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