In the previous screencast “Project Portfolio -- (Focus, you can't do it all -- Part A)” I described the process of project portfolio prioritization using constraints. Specifically, Cost and Risk factors to re-prioritize the portfolio. In this screencast called “Part B” I will show you the third constraint type using Resources. We’ll deal with the same problem statement, “How to prioritize projects based on a limitation of resources.” We need to select the best project mix to maximize benefit in order to meet our objectives.
Here is the same subset of a project portfolio I’ll use to illustrate resource constraints. I have my decision statement, my business objectives I must fulfill through the project portfolio—which I’ve prioritized using pairwise comparisons, and my list of project candidates to fund. Finally I’ve ranked each project as to how well it contributes to each objective. I will need to invest $50M to fund all projects. I'll also consider Risk and my “must-have” projects in this model.
Instead of looking at a lump-sum cost for each project, I’ll estimate costs using resources. In this case two skill types. Design and Test Engineers. I can have up to 10 types or groups of resources including capital equipment and/or material resources in my model.
You can see I need about 150 Designers and 60 Test Engineers. This is based on my per project estimates over the next year. I’ve estimated the number of people I need over an average time frame for each project. This view lacks the time dimension during the year, but I am OK with a rough level of granularity now, since I’m just trying to get a gross overview of my resource needs. Later I’ll refine this using a macro schedule.
Lets assume I only have 125 Design Engineers, not 155. With this limitation, what projects can I fund? In fact, I actually only need 120 Designers because Project F was eliminated, my overall benefit dropped to 96%, and I now only need $40M to do the remaining projects. The resource constraint impacted the projects I could fund.
Further, lets assume only 45 Test Engineers are available. Now I only need 36, my benefit drops further to 83%, my budget is $33M and Project D is gone from the portfolio.
Well, things are getting worse, my budget just got cut even further. It is now down to $25M, half of what I started out with needing. One approach would be to continue to half-fund all the projects and ask fewer resources to more with less. I could explain that this is a, “Growth opportunity” to my remaining cynical employees. We see this all the time, including the “motivational” speech from the executive team. In my model though I am going to make the hard decisions to cut some of these projects, but which ones?
With a $25M budget and my specific resource limitations, I have to kill Projects C and F. With this new mix my benefit is still relatively high at 77%.
But, we have a strategic override in that Projects C and D MUST be funded. The red boxes indicate which constraints are turned on in the model. I have resource limits, a budget constraint, and two projects that MUST be funded.
With these requirements my overall benefit drops below 50%, the budget required is $23M and I’m only using 67 Design and 30 Test Engineers. I now have to make the trade-off decisions between the reality of my constraints and the strategic growth demands of my business. Does this project mix work?
Further complicating the problem, lets introduce Risk to the model. Benefit drops even further. We can also see what the contribution of these projects are to each of my business objectives. This mix contributes less than 40% to Engaging Tier 1 Customers and less than 60% of my Margin requirement.
But if I increase the budget to $35M the picture changes and I jump to over 50% overall benefit based on the new mix and most also of my objectives are achieved as well.
The highlighted projects are the ones I could potentially fund based with my $31M budget, 92 Designers and 38 Test Engineers. Of course this is a macro look at the problem. This model will not provide specific details, I’ll cover how to do this in a later screencast, but it does provide a high-level decision tool to make macro-level decisions.
You cut a diamond by first using a band saw, before using an emery cloth. We’re looking at the “Band-Saw” cut now using this modeling method. When people start with the “Emery Cloth,” they usually get lost in the details and no material is removed.
Finally, this is the Cost-Benefit curve for the reduced portfolio mix where Projects A and F are dropped from this round of funding.