This is the time of year to check if the annual R&D budgeting process has set up the organization for success. One question kept bugging me from a recent executive portfolio review I attended. The R&D exec asked me: “We have reallocated 10% of R&D budget across business lines. Is this the right move?” In other words, how much budget should we shift across portfolios? Or: what is the right balance between continuity of innovation from a stable R&D pipeline and reallocation of resources for value maximization? The typical answer we would give is something along the lines of “It depends on your strategy and on the proposals which ones to fund”, however I decided to check if we could do better than that.
The extreme scenario for reallocation
A first quick review gives two rather extreme ways to approach the R&D budget allocation process:
- Maximum continuity
In this extreme scenario, each portfolio gets the same budget (in value, or more likely in share of total budget, or in share of the running business’ revenue or margin). This gives the maximum continuity for each portfolio individually, and essentially makes the top-level portfolio management process “easy” (or absent, since there is no reallocation across portfolios). The individual sub portfolios can then optimize and their results can be implemented without interference from other portfolios.
The major downside of this optimization of stable sub portfolios: it is suboptimal at the overall portfolio level. And more so if the value creation potential across portfolios is more differentiated. This could come from different stages in he product and market lifecycles, from different inherent profitability or ROI characteristics, and from different innovation maturity levels as well.
- “Zero-based budgeting”
The other extreme approach would be to start each portfolio round with a clean slate: all proposals (and even all running projects) compete on an equal footing for all the resources. In financial planning, this approach is called zero-based budgeting. The big advantage is the potential to optimize on value creation, and as a side-effect the perceived fairness (level playing field) for all proposals. Major disadvantage is the dramatic shifts that can occur from round to round, with a lack of continuity for R&D resources, compentences, and market consistency. That might be fine if these effects were all included in the analysis. However, the heavy burden it puts on the reliability of the underlying data conflicts with the inherent uncertainty in R&D.
So, if neither of these extremes appear to give the best portfolio, what is the right balance?
What do the experts say?
Looking for academic research, very little guidance comes up. The simulation models for portfolio flow (such as the work of Repenning in A dynamic model of resource allocation… and related) focus more on trade-off between R and D and shifting across projects, than on shifting across portfolios. The most relevant discussion on this topic seems to be from McKinsey in 2014 (Sweet spot for innovation resource), who have surveyed executives at large companies about this theme. Their research indicates that reallocation around 13% of budget across business portfolios year on year correlates with highest success rates. If I look at the data carefully, the differences between best and worst performers do not seem that big, as most companies are reallocating in the 10-20% range anyway.
One helpful side-effect of the McKinsey research is its implication for the inflow of new proposals. Each innovation funnel’s front end should be set up to generate sufficient proposals so that a proper selection process can in fact lead to a 1/7 increase in the budget. In short: make sure that this front-end (or ideation) process generates proposals for at least 30% budget increase (if all would be approved).
With this limited top-down guidance, the best way forward is to have a better look at the running projects and the proposals. The best reallocation decision comes from comparing the impact of a budget shift on each portfolio’s value creation potential. For example, in our FLIGHTMAP software, it is easy to compare the value creation potential (.g. in total portfolio Net Present Value) for compositions with different budget constraints (say 30% reduction, steady, and 30% increase). A proper optimization engine gives the resulting optimal portfolio composition with a single click.
More than just a sort of sensitivity analysis at the portfolio level, this analysis also gives clear guidance of where to reallocate the budget (and not just how much). By linking the reallocation percentages to value creation potential from real underlying project proposals, it drives value creation and makes the reallocation decision much more tangible.
Conclusion: solid analysis is required yet feasible
So summarizing our conclusions so far:
- if you are doing a high level check on a large portfolio, seeing a shift of about 1/7 of the resources across portfolios is in line with best practices
- if you want to look for proper portfolio balance, make sure the front-end process generates at least a 30% overshoot on budget
- for value-driven portfolio management, it is best to compare optimized portfolio compositions with -30%-0%-30% shifts and reallocate accordingly
As with most portfolio balance questions, this one also requires an integral view of the portfolio (including running business, running initiatives and new proposals), and a way to quickly analyse alternatives. With this analysis, we have focused on three of the four portfolio dimensions: value creation, balance, and feasibility (meeting the budget and resource constraints). Adding the strategic alignment dimension and its impact on continuity or shift seems a good topic for a new post.
Let me know if you have suggestions for this topic?