R&D Prioritization Process
A global biotechnology firm identified the need for an improved system to prioritize its R&D investments. Like most large research-focused companies, they performed an annual review of the R&D pipeline. We designed a system to:
Improve the analytic quality of the results by including uncertainty analysis for key projects
Bring greater consistency and reduce the risk of error by employing standard template models
Reduce the amount of work required to carry out the process, both for the project teams and the portfolio analysis team
The portfolio process made the dialogue between senior management and the project teams more productive. The straightforward expression of uncertainty in the new models reduced the amount of time spent on year-over-year comparisons ("why has this number changed?") and encouraged management to focus on value creation improvements ("what can we do to make the target product profile scenario more than 40% likely to occur?").
A leading biotech firm was about to launch a new-to-market product with limited manufacturing capacity. White Deer Partners employed multivariate analysis to support numerous intangible value drivers for this decision, including Stock Out, KOL Acceptance, Patient Centric, and Product Experience.
After developing and refining 7 strategies, we built scales to quantify the degree to which each strategy performed against these values, assessed weights to understand the relative importance of each value, and then formally combined this to produce a rank ordering of the strategies.
Since the Inventory Build strategy was preferred, the team performed an inventory optimization analysis recognizing the key uncertainties around supply and demand. The output of this analysis included the timing for stockout under any set of assumptions, and the probability of stockout with all uncertainties varying across their range.
White Deer Partners designed an excel-based worldwide patient-based market model and analysis tool. The tool was comprehensive enough to allow for specific regional input, assumptions, and rationale for the required market parameters. In addition to improving data quality, the parametric design of the market model allowed the Marketing Analytics team to perform sensitivity analysis for the key inputs at both a regional and global level.
WDP brought Subject Matter Experts (SMEs) together and through a structured exercise, assessed probabilities of success at each major milestone for a flagship project.