Innovation Crescendo

In our continued pursuit of the perfect R&D portfolio, this post discusses the optimal number of projects for an R&D group to execute at any one time.

Is there an Optimal Number of Projects for a Portfolio? … Remember that every R&D group has a finite capacity for the number of projects it can handle efficiently at any one time and that capacity is limited by the R&D budget, the size of the group, the collective talent of the R&D group and the state of its organizational infrastructure.  Once this capacity has been exceeded, then bottlenecks will occur as projects progress through the new product development (NPD) process.  Without project prioritization, important projects will be held up until the bottleneck is resolved.

This all suggests that for every R&D group there is an optimal number of projects that keeps the R&D group fully engaged without bottlenecks.  However that optimal number varies depending on the average “size” of the projects in the portfolio.

The NPD Effectiveness Metric … In the previous post¹ we showed how the relative performance of R&D groups from different companies can be compared by plotting the average launch size of new products verses R&D productivity (number of launches per year/R&D budget).  Another metric that gives a different view of R&D performance across companies is “new product development (NPD) effectiveness” (average launch size x R&D productivity).  I will use that metric going forward to discuss the optimal number of projects in a portfolio.

Maximize  NPD Effectiveness for the R&D Portfolio … There are two major factors which govern new product development (NPD) effectiveness once the R&D budget has been set: risk and capacity.  If you plot the NPD effectiveness of a fully-utilized R&D group having a fixed budget, as the number of projects increases from a small number of large projects through to a large number of small projects you will find that there will be a maximum that occurs somewhere in the middle.  This NPD effectiveness maximum is called the “sweet spot”.

If a R&D portfolio contains a few large projects then each project by definition carries a relatively large amount of risk.  A large complex project can fail for many reasons as there is so much more that can go wrong with complex project relative to a simple project.  Also, even if a large complex project is successfully launched it may not reach the desired sales expectations in the market place, which is a further risk.  In the situation where the portfolio consists of a few large projects, NPD effectiveness can be reduced greatly if failures occur in even one or two projects.  The failures will dramatically decrease the value of the portfolio and hence reduce R&D productivity (and consequently NPD effectiveness).  This is the “risk constrained” region of the graph to the left of the “sweet spot”.

On the other hand, if there are many small projects, risk is spread over a large number of projects and is reduced because failure of a few projects will not dramatically affect the value of the portfolio.  Also there is less that can go wrong for a small project.  However if there are too many small projects in the R&D budget, resources become constrained and the pipeline becomes congested, limiting the value of the NPD portfolio and NPD effectiveness.  This is the “capacity constrained” region of the graph to the right of the “sweet spot”.

Summary … Looking at the graph, the NPD effectiveness of your R&D group can be optimized by choosing the number of projects that falls within the “sweet spot”.   The “sweet spot” is between the “risk constrained” region which contains a few high risk “big idea” projects and the “capacity constrained” region which contains too many projects (often small incremental line extensions or maintenance type projects).

“Best in class” companies carefully manage the number of active projects within the portfolio by a strong governance body² so that R&D resources are fully utilized but not overburdened (i.e. so bottlenecks don’t occur) and the number of high risk projects is balanced by other types of projects.  Portfolio optimization is another good example of innovation crescendo at work.

1. Previous post:  “Perfecting your R&D Portfolio” discussed the benefits of a balanced R&D portfolio and how to balance risk verses R&D productivity.
2. A future post will examine portfolio governance.

© Dennis Nelson 2013