It seems almost a universal truth that resource allocation exercises use prioritization at some point in the process. Nearly every company we’ve spoken to or heard from over the past decade-and-a-half, in Pharma or other industries, relies on it. Project prioritization has several things going for it:
- Mathematical simplicity: It’s very hard to quibble with the math behind project prioritization, and explaining division to executives or any other group of people is far easier than explaining genetic optimization algorithms. The simplicity also means that anyone with Excel can do the math, and since “anyone with Excel” is generally almost everyone, project prioritization is extremely egalitarian.
- Limited data requirement: There are really only two pieces of data required, one each for the numerator and denominator.
- Everybody loves a winner: It’s easy to see which is the “best” project and which is the “worst”, and the rankings in between. In the words of one client: “Everyone wants to know where their project stands.”
Prioritization using a “bang for the buck” metric has its place in the portfolio process
The table on the right is typical of how project prioritization results are presented. The projects are listed from best-to-worst, ordered by descending “Productivity”, which in this example is the ratio of rNPV (risk-adjusted Net Present Value) to the Requesting Funding in the budget year. (All units are in $M except for Productivity, which is dimensionless.) Beginning at the top of the list, projects are funded until the budget is met (in this case, $2,500), and the amount with which each project is funded is recorded in the “Allocated Funding” column. Funded projects receive an “x” in the “Included?” column. A running total of allocated budget is kept in the “Cumulative Funding” column. As the budget runs low and projects are not able to be funded in their entirety, they may be partially funded based on management discretion. In this example, both Mritigen and Zerxil have been granted partial funding.
So when is project prioritization useful, and when is it hindering good decision-making processes?
Project prioritization at its best: Tactics
Prioritization can be extremely useful to provide guidance for project managers scheduling work. In what we term operational R&D portfolio management (often referred to as project portfolio management, or PPM), it’s important to know the relative importance of projects. On any given day, as those responsible for getting projects done face the need to allocate their time and other resources, they should have clear guidance about which projects take priority. This may be expressed by ranking the entire portfolio or by putting projects in buckets by importance.
Project prioritization at its worst: Strategy
Many companies attempt to incorporate prioritization as the foundation of their decision-making processes. Prioritization can be a very useful tool, but at its heart prioritization is about competition, and competitive processes work best when there is only one winner. In the case of R&D portfolios, however, there are many winners in each resource allocation cycle, and the value of each project depends on the others included in the portfolio with it.
Consider this example: A high-tech conglomerate creates a new division to pursue solar panels. If the company allocated resources strictly using project prioritization, it’s likely that the solar panel projects—presumably riskier and longer term than projects in more-established business areas—would land near the bottom of the list. The leadership team may attempt to compensate by assigning a “kicker” to solar panel projects, increasing the scores of all such projects. (We’ve seen many companies in this situation do just this.) However, while the company may be interested in ensuring that 5 or 10 solar panel projects attain funding, they probably aren’t interested in funding 50. The value of the kicker doesn’t diminish as more projects are funded, though, and the utility of the project prioritization process diminishes.
In this example, artificially inflating the scores of solar panel projects is really a proxy for what the company truly cares about: ensuring that x number of solar panel projects are funded. A more strategic process that focuses on the set of projects chosen, rather than on the individual projects themselves, creates a much more direct relationship between the strategic objectives the organization cares about and the methods used for project selection.
Marimekko charts in the Enrich Analytics Platform highlight spending breakdowns across divisions and projects
The chart on the right presents data on a project-by-project basis, but does so in the context of the portfolio. It is immediately apparently how much funding is allocated not only to each project, but to each Therapeutic Area, making it much easier to judge whether or not certain TAs are under- or over-weighted.
Thinking about the portfolio in its entirety, and considering trade-offs among portfolios instead of projects, makes the impact of project selection decisions on corporate performance far more clear. Put another way, looking at the forest instead of the trees makes it much easier to determine the best path forward.
Each year, tens of billions of dollars in R&D investments are shaped, allocated, and refined with the help of Enrich’s EAP. Are you interested in learning how we can help streamline your portfolio reviews, turning months of long nights and frustration into a value-enhancing, confidence-affirming exercise for your R&D organization? Contact us, and learn what our clients already know about the value of the Enrich Analytics Platform.
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