CASE STUDY 1
AI-Enabled
RFP Strategy
Turning a fragmented pursuit process into a governed system for better decisions, faster execution, and stronger pursuit performance.
Industry: National insurance brokerage
Business Context: Multi-line commercial sales
My role: VP, Client Strategy and Cross Sell
Focus: Revenue growth, decision intelligence
The Constraint
RFPs were handled inconsistently across the firm. Qualification varied, important intelligence was difficult to reuse, and teams repeatedly rebuilt research and content from scratch. Leadership had limited visibility into pursuit quality, resource requirements, and the reasons opportunities were won or lost.
The problem wasn’t a lack of effort. It was the absence of a system for making better pursuit decisions and executing them consistently.
The System
I designed a governed RFP operating model that combines qualification standards, structured collaboration, reusable knowledge, AI-assisted analysis, and human review.
Opportunity Qualification
Formal criteria determine where resources should be invested.Win Strategy & Intelligence
Relationship, competitive, and business intelligence shape pursuit strategy.AI-Assisted Research
AI accelerates research, synthesis, requirements analysis, and pursuit preparation.Human Review & Governance
Expert judgment validates information, manages risk, and determines the final strategy.Performance Intelligence
Leadership gains visibility into pipeline, outcomes, capacity, and reasons for loss.
My Role
I designed the capability from concept through regional implementation, including the operating model, governance, workflow, technology, adoption, and performance measurement.
Redesigned the pursuit workflow and governance model
Selected and configured AI and knowledge-management tools
Built the information architecture and reusable content library
Established review standards, quality controls, and human oversight
Trained teams and led adoption
Developed performance reporting and leadership dashboards
Partnered with regional leadership on pursuit qualification and investment decisions
The Result
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Higher Win Performance
A more disciplined qualification and execution model materially improved pursuit outcomes.
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Faster Execution
Major proposal cycles became substantially shorter.
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Greater Capacity
he team could manage multiple complex pursuits simultaneously without proportional headcount growth.
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Better Visibility
Leadership gained insight into pipeline quality, resource allocation, and reasons for loss.
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Stronger Collaboration
Clear ownership, shared intelligence, and review standards improved coordination across pursuit teams.
“We stopped treating every RFP as a writing assignment and
started treating it as a business decison supported by a repeatable system.”
Big ideas, real impact.
AI creates more value when it is designed into a better operating model, not added to a broken process.
Technology accelerated research, synthesis, and preparation. The larger transformation came from qualification, goernance, reusable knowledge, explicit decsion points, and a workflow that made expert judgement easier to apply consistently.
That is the pattern I look for in transformation work: Identify where the business is losing time, judgment, or opportunity, then redesign the system before deciding where technology belongs.