5–10%
Increase in innovation pipeline value
Improvement in the assessed value of the prioritized pipeline.
Modeled improvement based on the client's own pipeline valuation method.
Case 02
Improving Innovation Portfolio Value Through Data-Driven Prioritization and Resource Allocation
Portfolio governance and analytical prioritization replaced case-by-case negotiation, increasing the value of the innovation pipeline.
- Client
- A mid-market R&D and innovation company
- Industry
- Consumer & Commercial
- Decision domain
- Innovation portfolio prioritization
- Capabilities
- Strategy · Decision Intelligence · Optimization
Measured outcomes
What changed.
Pipeline value figures are modeled using the client's own valuation method, not audited financial results.
Tens of millions
Financial value measured in tens of millions of dollars
Modeled financial value at the portfolio level.
The situation
Where the work started.
A mid-market R&D and innovation company ran a development pipeline larger than its capacity to deliver.
Programs entered and stayed in the pipeline through advocacy, with limited comparison against alternatives.
Decision at stakeWhich development programs deserve investment, in what order, and what is given up by funding one over another.
What prevented the decision
The constraints that had to be removed.
- No consistent basis for comparing programs of different size, risk and horizon.
- Resource constraints surfaced late, after commitments were already made.
- Prioritization outcomes were not documented, so they were re-litigated every cycle.
What SMPLCTY delivered
The system we built.
- Portfolio governance model
- A documented prioritization method with defined criteria, decision rights and review cadence.
- Prioritization analytics
- Value, cost, risk and capacity data brought into a consistent comparison across the pipeline.
- Resource allocation modeling
- Scenario comparison showing what each funding pattern produces under real capacity constraints.
Implementation
- 01Agreed the prioritization criteria with leadership before any modeling began.
- 02Built the comparison and allocation models against the company's own pipeline data.
- 03Ran the first cycles alongside the leadership team, then handed the method and models over.
Applied here
Services and solutions behind this work.
Services
Data, Analytics & AI StrategyA strategy anchored to the decisions that move performance — what to measure, what to build, in what order, and what it is worth.Decision Intelligence SystemsDecision products, not dashboards: the evidence, thresholds, ownership and workflow that make a recurring decision reliable.
Related work
Comparable decisions.
Case 01How a Global Consumer Health Company Cut Portfolio Time-to-Action by 80%Portfolio data, prioritization logic and recommended actions brought into one governed decision system, cutting the time between question and decision.Case 04Cutting Product Launch Time by 50% Through Portfolio and Resource OptimizationSequencing and resource allocation modeled against real capacity constraints, halving the time from decision to launch.
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