In previous posts, I’ve discussed how to prioritize your portfolio of R&D investments in great detail. Today, I want to focus on prioritization’s flashy sibling, optimization.
Unlike simple prioritization schemes, optimization methods can handle multiple constraints to address competing portfolio objectives. So where a prioritization result may unduly favor later stage, less innovative projects, an optimization will suggest a more nuanced investment plan. In addition, optimization methods easily handle dependencies between lead and follow-on projects and can consider multiple development and go-to-market plans for key initiatives.
This video will take you through the whys and hows of portfolio optimization. We’re using the Enrich Analytics Platform to accomplish the optimization and scenario analysis in a way that lets us easily explore both portfolio-level implications as well as the project-by-project trade-offs suggested by each investment plan.
Optimization won’t give you or your executive team ‘the answer’. Rather, it will suggest bundles of projects that could move you closer to your strategic goals than your current investment plan. It’s up to you to judge (and refine) the suggested portfolio in light of political realities and the less tangible trade-offs facing your organization.
In our experience, the organizations that leverage optimization methods most effectively have the following characteristics:
- They have a significant percentage (30%+) of their funding that is discretionary; if 90% of all funds are committed there isn’t much use in using sophisticated methods to allocate the remaining 10% of funds.
- They see optimization results as a starting point, using them to create and refine prospective investment plans.
- They compare these investment plans against the current/base case plan, a more traditional prioritization of projects, and other executive or division-crafted plans to better understand the trade-offs inherent in their portfolio as well as the strengths and weaknesses of each method.
- Executives actively participate in the discussions of trade-offs between the prospective plans, and are able to judge each plan’s potential to make progress towards short- and long-term goals (thanks to a clearly-articulated set of goals).
Over the years (decades, even) we’ve seen interest in optimization methods wax and wane. The key to their effective usage is a solid understanding of the methods’ value and their proper place in a portfolio management process. When used correctly they can be a quick source of insights regarding the breadth of options available to your team.
At Enrich, we have deep experience helping companies benefit from portfolio management at every level of maturity. From startups with developing patent portfolios to the largest life science companies on the planet, we’ve deployed processes and tools that help them all make better investment decisions. If you’re interested in learning how our tools (Viewport and the Enrich Analytics Platform) can help you level-up on your portfolio management process, drop us a line.
