Presans: Building Business Models for Innovation Intermediaries Custom Case Solution & Analysis
1. Evidence Brief: Presans Case Data Extraction
Financial Metrics
Revenue Growth: Since founding in 2008, the firm reached a turnover of approximately 2 million Euros by 2014.
Business Model Mix: Revenue primarily derived from success fees (commission on expert placement) and fixed-fee consulting projects.
Market Position: Operating in the Open Innovation Intermediary (OII) sector, estimated to be worth hundreds of millions globally, though fragmented.
Service Pricing: High-touch concierge services priced significantly higher than automated platform competitors like InnoCentive.
Operational Facts
Expert Database (X-Net): Access to over 6 million experts worldwide via proprietary web-crawling technology (Expert-Search).
Human Capital: Core team of 15 employees supported by a network of Fellows (high-level retired R&D executives).
Process: Three-stage methodology: 1. Problem definition, 2. Expert identification and qualification, 3. Knowledge transfer.
Technology: Proprietary algorithms that map scientific expertise by analyzing publications, patents, and technical documents.
Stakeholder Positions
Albert Meige (Founder and CEO): Advocates for a shift toward a subscription-based model (Presans Insight) to stabilize cash flow and scale operations.
Fellows: Act as the crucial bridge between technology and clients; their role is to translate complex industrial needs into searchable scientific queries.
R&D Directors (Clients): Seeking faster innovation cycles and external expertise to solve specific technical bottlenecks but often constrained by internal procurement and security protocols.
Information Gaps
Customer Acquisition Cost (CAC): The case lacks specific data on the cost to acquire a new industrial client versus the lifetime value (LTV).
Churn Rate: No data provided on the renewal rate for clients who have completed a single concierge project.
Technical Scalability: Missing details on the server costs or maintenance requirements for the 6 million profile database.
2. Strategic Analysis: The Scalability Dilemma
Core Strategic Question
How can Presans transition from a labor-intensive concierge service to a scalable business model without eroding the high-trust, premium value proposition that differentiates it from low-cost automated competitors?
Structural Analysis
Value Chain Analysis: The primary value is not in the 6 million experts (the data) but in the filtering and validation (the insight). Competitors provide the data; Presans provides the solution. Scaling the human-led validation (Fellows) is the bottleneck.
Jobs-to-be-Done: R&D leaders do not want a list of names; they want a solved problem. Presans Insight must move from providing access to providing ongoing strategic foresight.
Porter Five Forces: Threat of substitutes is high from internal R&D and LinkedIn-style networks. Bargaining power of buyers is high as they are large industrial groups (Total, Danone).
Strategic Options
Option
Rationale
Trade-offs
Pure SaaS Pivot
License the Expert-Search tool directly to clients.
High scalability but loses the high-margin Fellow-led validation; risks commoditization.
Hybrid Subscription (Insight)
Retainer model for ongoing access to Fellows and technology.
Stabilizes revenue and maintains premium status; requires high organizational change.
Consulting Expansion
Focus on high-end, one-off innovation strategy projects.
Highest margins; impossible to scale without massive headcount growth.
Preliminary Recommendation
Pursue the Hybrid Subscription model (Presans Insight). This path preserves the unique Fellow-led vetting process while moving the firm away from lumpy, project-based revenue toward a predictable recurring revenue stream. It aligns the cost structure with the value provided—continuous innovation support rather than one-off firefighting.
3. Implementation Roadmap: Transitioning to Presans Insight
Critical Path
Fellow Standardization (Month 1-2): Codify the Fellow methodology into a repeatable playbook to reduce the time required per client engagement.
Insight Dashboard Development (Month 1-4): Build the digital interface for the subscription model, allowing clients to track expert interactions and scientific trends in real-time.
Sales Force Re-training (Month 3): Shift the sales narrative from selling a project to selling a capability and long-term partnership.
Pilot Launch (Month 4-6): Convert three existing concierge clients to the Insight subscription at a discounted early-adopter rate.
Key Constraints
Fellow Availability: The model depends on high-caliber retired R&D heads. Scaling requires an aggressive recruitment and onboarding pipeline for these individuals.
Sales Cycle Friction: Industrial procurement departments are accustomed to buying projects with clear deliverables, not ongoing subscriptions.
Risk-Adjusted Implementation Strategy
To mitigate the risk of revenue loss during the transition, Presans should maintain a dual-track approach for 12 months. Large-scale concierge projects will fund the development of the Insight platform. A dedicated transition team must be formed to ensure that the development of the SaaS tool does not distract from the high-touch service that currently maintains the brand reputation.
4. Executive Review and BLUF
BLUF
Presans must pivot to the Insight subscription model immediately. The current project-based concierge model is an operational trap that prevents scaling and leaves the firm vulnerable to revenue volatility. By productizing the Fellow-led validation process into a recurring service, Presans can capture a higher share of R&D budgets while maintaining its premium differentiation. Success depends on the ability to standardize the human-in-the-loop component without degrading the quality of expert matches. APPROVED FOR LEADERSHIP REVIEW.
Dangerous Assumption
The analysis assumes that the current Fellows can and will adapt to a more standardized, tech-enabled workflow. These are senior executives who may resist the transition from expert advisors to part of a repeatable productized service.
Unaddressed Risks
Data Privacy and Security: Large industrial clients (e.g., aerospace, defense) may refuse to use a cloud-based dashboard for sensitive R&D queries, potentially limiting the Insight model to less sensitive industries.
Algorithm Decay: As competitors improve their AI-driven search capabilities, the technical advantage of the Expert-Search engine will diminish, placing even more pressure on the Fellow network.
Unconsidered Alternative
The team did not fully explore a White-Label Partnership. Presans could license its Expert-Search engine to major strategy consulting firms (e.g., BCG, McKinsey) who already have the client relationships and could use the tool to augment their own innovation practices, providing Presans with high-margin licensing revenue without the sales overhead.
MECE Compliance
The strategic options are mutually exclusive (SaaS vs. Hybrid vs. Consulting) and collectively exhaustive regarding the potential directions for an innovation intermediary at this stage of growth.