Clinical-Stage Biotech · Life Sciences · San Francisco, CA · 10 weeks
R&D portfolio analytics built across 8 programs
A clinical-stage biotech with eight active programs and $340M in pipeline lacked a consistent way to track R&D performance. Each team used separate spreadsheets, leading to conflicting status reports for the board. We developed a centralized analytics platform that standardized program tracking, delivering one clear view of pipeline value and risk for leadership.
Challenge
Eight program teams each tracked milestones, spending, and success chances in their own spreadsheet format. The CFO’s team spent three weeks manually reconciling data for board reports, which program leads often challenged. This inconsistent reporting left the board unable to answer investor questions reliably.
Approach
We created a single R&D portfolio data model to align milestone definitions, spending categories, and success probabilities across all eight programs. Then, we developed a Power BI dashboard that delivered the board a clear view of pipeline value, milestone progress, actual spend, and risk-adjusted NPV for each program and the entire portfolio.
Outcome
We cut board reporting time from three weeks to two days by standardizing data inputs. After four weeks aligning program leads on the unified data model, they fully adopted it. For the first time, investor presentations used consistent metrics approved by the board. The CFO leveraged portfolio analytics to pinpoint $18M in R&D spend that could be reallocated.
How We Picked the Metrics That Really Showed Success
Alright, here’s what went down. Each team was flying solo, guessing success chances their own way, it was chaos. So, we pulled everyone together, sat in one room, and built a single scoring system from scratch. We focused on clinical stage, how the drug works, and what the competition looked like. Took about a month, but by the end, every program lead was fully on board with this new, unified approach.
How We Used Risk-Adjusted NPV to Help the Board Make Smarter Calls
The board was struggling to compare programs, different sizes, different stages. So we used risk-adjusted NPV to level the playing field. We took standard success rates, added projected peak revenues, and applied discount rates specific to each program. That gave us a clean, apples-to-apples number for every option. The board finally had a clear, unbiased way to decide where to invest.
Results
- 3 weeks to 2 days Board reporting preparation time
- $18M R&D spend reallocation opportunities identified
- 8 programs Unified under single portfolio data model
- Full Program lead acceptance of unified data model
We had 8 programs, each reporting differently, so the board couldn’t really compare them. Investors were getting uneasy. Thinklytics created a unified portfolio view in 10 weeks. Right away, the CFO spotted $18 million we could reallocate.
In the client's terms
The question
Where does this number come from, and can the path be trusted?
The situation
Eight programme teams tracked milestones, spend and probability of success in eight spreadsheet formats. The CFO's team spent three weeks reconciling them for each board pack, and programme leads regularly disputed the result.
What we found
The disputes were legitimate. Milestone and probability definitions differed between teams, so reconciliation was quietly making judgement calls that belonged to the programme leads, and they were finding out in the board pack.
What it produced
Board reporting fell from three weeks to two days. Programme leads accepted the unified model after four weeks of alignment. Investor presentations now use board-approved consistent metrics, and the CFO used the portfolio view to identify $18M of R&D spend available for reallocation.
The roadmap
One portfolio data model aligned milestone definitions, spend categories and probability of success across all eight programmes, agreed with the leads rather than imposed. A Power BI view then gives the board pipeline value, milestone progress, actual spend and risk-adjusted NPV per programme and across the portfolio.
The work behind this result
- Reporting takes too much work, the problem this engagement resolved.
- AI Reporting Automation for Tableau & Power BI
- Business Intelligence & Analytics Consulting
- Agentic BI Implementation Consulting
- Reporting Baseline and Benefits Worksheet, for whoever has to approve the spend.
- The 30 day Corporate Drag and Risk Diagnostic, findings yours either way.
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