| name | new-business-opportunity-filtering |
| description | A rigorous framework for vetting new product lines or startups. Use this when evaluating a potential pivot, selecting between multiple roadmap opportunities, or validating a new business model before committing resources. |
New Business Opportunity Filtering
Derived from Jason Droege’s experience launching Uber Eats and leading Scale AI, this framework applies a high bar to new ventures by prioritizing "independent insights," gross margin stress tests, and incentive alignment. It shifts focus from simply "solving a problem" to identifying sustainable business models with competitive alpha.
The Core Filters
1. The "Independent Insight" Test
Before building, you must articulate why you have an insight that others do not. In a world of a million smart entrepreneurs, your competitive edge must be specific.
- The Question: "Why am I so lucky to have this insight?"
- The Validation: If your research is heavily influenced by the general market consensus or "what everyone is saying on X/Twitter," you lack alpha. Look for truths that people currently believe are false.
2. The Gross Margin Stress Test
Use gross margin as a "coarse instrument" to measure the value you are adding and your degree of differentiation.
- The 60% Rule: Start with the assumption that the business should have a 60% gross margin.
- The Negotiation: If a 60% margin seems impossible, ask exactly why.
- Is it because the customer has an alternative?
- Is it because the underlying costs (labor, ingredients, compute) are too high?
- The Red Flag: If the alternative is a low-margin (e.g., 20%) offshoring or legacy business, your margins will likely compress toward theirs unless you have a massive technological differentiator.
3. Incentive Triangulation
Do not take customer feedback literally. Instead, look at the underlying incentives of every stakeholder in the ecosystem.
- Financial Incentives: Map out the unit economics of your customer better than they do.
- Non-Financial Incentives: Identify the ego, career growth, or regulatory pressures driving the buyer.
- The Ground Truth Method: When customers won't share data, triangulate it. (e.g., If a restaurant won't share costs, buy the food, weigh the ingredients, and look up wholesale prices to build your own model of their margins).
4. The "Survival First" Principle
"Not losing is a precursor to winning." Avoid "going for it" with high-risk gambles that could compromise the enterprise.
- Risk Profile: Seek asymmetrically positive decisions where the downside is capped but the upside is uncapped.
- Timeline: Ensure the business model allows you to survive long enough for the market "timing" to eventually hit. Most businesses fail because they run out of resources before they find the right product-market-fit iteration.
Application Guide
- Select the Market: Choose markets with "good" inherent characteristics (Marketplaces, SaaS, Recurring Revenue, Network Effects).
- Run the Filters:
- Is it Urgent? Is this the top thing the customer thinks about daily, or just an annual "nice-to-have"? (Avoid "long roads to small towns").
- Can it Scale? Does the business become more valuable at a large scale than at a low scale?
- Identify the "Alpha": Write down the one thing you believe about this market that your competitors currently think is bunk.
Examples
Example 1: The Uber Eats Launch
- The Insight: Restaurants have high fixed costs (rent/labor) but low incremental costs for one extra meal.
- The Margin Stress Test: Uber proposed a 30% cut. Restaurants balked, but Uber’s triangulation showed that a 70-80% incremental gross margin on extra orders made the math work for the restaurant even with the high fee.
- The Outcome: A multi-billion dollar business that scaled because it aligned with the restaurant’s need for incremental demand without increasing fixed overhead.
Example 2: AI Healthcare Solution
- The Insight: Doctors at elite hospitals are backlogged not by a lack of knowledge, but by the "300-page document" problem (manual synthesis of rare case data).
- The Urgency: This isn't just "better data"—it's a productivity bottleneck that prevents them from seeing more patients.
- The Value: The "eval" (defining what good looks like) is created by the doctors themselves, creating a specialized moat that generic models can't easily replicate.
Common Pitfalls
- Falling in Love with the Idea: Ignoring the "Gross Margin Stress Test" because you are personally passionate about the solution.
- Solving Non-Urgent Problems: Building a product that provides value but isn't a "top 3" priority for the buyer, leading to infinite sales cycles.
- The Denominator Effect: Mistaking a high number of "Pilot Projects" for product-market fit. In AI especially, POCs (Proofs of Concept) are easy to start but take 6–12 months of "operational chiseling" to make robust enough for production.
- Neglecting Change Management: Assuming that because the technology is better, the customer will automatically adopt it. The "last mile" of adoption is a human and policy issue, not a technical one.
