It's a quarterly review, with twenty projects on the agenda and two hours on the clock. Each innovation team gets six minutes, the board nods, and the next team walks in. At the end, every project still gets funded, and the direction is exactly the same as before.
In a survey of 118 companies, 75% called incubation important to their growth. Only 14% rated themselves effective at it, and 6% efficient. That gap between ambition and execution is why incubation is called the messy middle of innovation.
Innovation leaders are frustrated, as they are asked to build massive business cases they know they can't defend, then held to assumptions they were forced to guess at. A pivot gets treated as a failure, while the budget keeps flowing back to the safe work.
The fix is to redesign the system itself. Doug Williams and David Matheson of SmartOrg spend their time inside companies rewiring incubation, replacing the stage-gate machinery with the 6Vs framework — a process built around de-risking: testing the riskiest assumption first, cheaply, and letting what the team learns decide where the next dollar goes. The team stops defending guesses and starts producing answers.
Running the system takes three steps: find where governance breaks down, score the team against the 6Vs, and fix whichever practice scores weakest this quarter. Leaders who run the system this way ended up with a faster path to killing weak bets, more resources reaching the projects that earned them, and a finance team that finally trusted what the innovation budget was doing.
Why Stage Gates Break Down in Incubation
Some kinds of uncertainty companies handle well. A pharmaceutical company, for example, spends hundreds of millions on a clinical trial without knowing whether the drug will work. The organization does so with confidence, because everyone in the room knows what the risks are, how to test them, and how long the answers will take. The risks are large, and the team has experience managing them. That's why stage gates work here.
In incubation, the uncertainty looks different. A team builds a business case with a revenue number resting on three assumptions: customers will pay this much, the market is this big, the channel will carry the product.
The innovation leader putting the case together knows those numbers are soft. They came from a market report, an internal estimate, a conversation with one customer. They go into the plan as inputs anyway, because the business case template asks for a number. The team moves on to the work they know how to do, and nobody looks at the assumptions again.
Six months later, a CFO flips to the revenue slide and asks, "Why do we believe any of this?" Nobody has an answer, because nobody tested the assumptions. The engineering team never examined the channel, the product team never pressure-tested the market sizing, and the quarterly review never raised the question because those assumptions went into the plan as fixed numbers.
The stage gate checks whether the team is on plan, and according to the plan, everything looks fine. So the team passes every gate, hits every milestone, and the assumption that could change the project's direction never gets tested, until it is too expensive to fix. And anyone who has watched a promising project collapse in its third year over something the team could have tested in week two, knows exactly what this costs.
De-risking in incubation means catching that assumption early: find the one most likely to change the project's direction and test it first, while the test is still cheap.
Testing it early might cost a few weeks of work. Discovering the same assumption at a stage gate, after months of spending, can cost the whole program.
Nevertheless, in most organizations, leaders who try to de-risk often run into their own company's existing governance system. That system asks for a business case and a plan, before the team is even allowed to test anything.
How Governance Blocks Incubation
Running incubation well is hard. Running incubation inside a company that already has its own governance, incentives, and review culture is harder. Most of the frustration innovation leaders feel comes from the way their own organization manages incubation, which in most companies means defaulting to the same governance that runs the core business, because no alternative exists.
Five patterns show up when that happens.
The promise trap. Traditional governance asks for a promise the team can keep. So teams promise something small and safe, and a small promise produces a small result.
Most innovation leaders have watched a team with a genuinely large opportunity walk into a review and pitch the smallest possible version of the idea, because that was the version they could commit to delivering.The comfort-zone blind spot. Vetting drifts toward the issues the team already knows how to handle: technical teams raise technical issues, consumer brands raise consumer issues, and the surprises that decide the outcome sit outside the team's expertise, in the areas nobody owns.
And when vetting turns political, the list gets shaped by whatever the senior person in the room already cares about. The issues that would actually change the plan never make the list, because raising them feels like inviting trouble.The business-case standoff. Innovation leaders resist building business cases because a case feels like a commitment they will be held to. If they get it wrong, they risk their entire career. Finance, from their side, cannot tell whether the money is being spent in a sensible order or simply being spent. The two sides avoid each other until a big investment finally needs justifying. As a result, they only meet for the first time over a funding decision neither side is prepared for.
"There's a bit of a battle between the financial function and the innovation function," David mentions. "If an innovator makes a business case, they might get held accountable to assumptions they're asked to make that they can't really defend. So it's extremely dysfunctional — those two groups rarely see eye to eye until late in the process, when they have to justify a big investment, and that's a difficult hurdle to get through."The HIPPO problem (highest-paid person's opinion). Teams prioritize by what they already know how to do, or by whatever the most senior person in the room wants. Both habits mean the team spends its time on work that feels productive while the question that would actually change the project's direction stays untouched.
Governance that punishes learning. The framework warns against what it calls "terminal niceness": governance so focused on keeping everyone comfortable that it stops nothing and redirects nothing. That niceness can become incredibly costly over time.
Small promises, comfort-zone vetting, business-case avoidance, HIPPO prioritization, and governance that punishes learning all happen because of the same thing: a system built for the core business, applied to work it wasn't designed for. The 6Vs replace that system with one built for incubation.
The 6Vs: A System for Running the Middle
A team needs a repeatable process for testing the biggest risks first. SmartOrg's framework for incubation has six practices, called the 6Vs, which form a loop designed to replace stage-gate governance with a system built for learning under non-routine uncertainty. These are:
Vision: set a target for the project that is big enough to matter, for the customer and for the business. The vision is the destination, separate from the near-term promise the team makes to its funder.
Vet: list the issues that could influence – positively or negatively – the organization’s ability to achieve the Vision, and find the few most likely to change the plan. These are the project's real risks.
Value: build a lightweight business case using assumption ranges to identify which factors drive the project's value. The assumptions that swing the value most are the ones to test first. The business case is where de-risking materializes: it tells the team where to aim its learning using objective data rather than guesses.
Velocity: govern the rate of learning by working on the question that would most change a decision, and run the cheap, decisive tests before the expensive ones. Velocity measures learning, not activity.
Venture: run focused, lightweight experiments that resolve the priority issues.
Verdict: hold regular pivot meetings where the team presents what it learned, how the learning changes the plan, and what to fund next. The verdict replaces the status review with a decision.
The six practices connect as a cycle. The team sets a vision, vets the issues, builds a value case to find where the risk sits, prioritizes by velocity, runs ventures to resolve the top risks, and brings the results to a verdict meeting that updates the plan and starts the loop again.
When moving the framework from theory to practice, reality surfaces: most companies are strong on some of these and weak on others. When SmartOrg asked participants across three recent workshops to assess their own organizations against the 6Vs, the pattern was clear.
Teams rated themselves strongest on the early stages, with 50% scoring well on vision and vetting, the stages that feel like strategy work and play to existing strengths. The two stages that determine what to work on next and when to change direction scored worst: velocity at 6%, verdict at 22%.
Score the six practices
For each of the six practices below, rate your team strong or weak, using the temptation listed as the test: if the team recognizes the temptation as something it does regularly, mark that practice weak.
☐ Vision — strong / weak. Temptation: promising small instead of aiming at the full prize.
☐ Vet — strong / weak. Temptation: raising only the issues inside the team's comfort zone.
☐ Value — strong / weak. Temptation: avoiding the business case, or treating the business case as a promise.
☐ Velocity — strong / weak. Temptation: doing the work that confirms instead of the work that decides.
☐ Venture — strong / weak. Temptation: managing experiments like execution projects.
☐ Verdict — strong / weak. Temptation: running meetings that check schedule instead of checking learning.
Then, take the practice marked weakest, and find one project already running through it. How can you improve?
The three examples below are organizations piloting the 6Vs framework. Each one prioritized the practice that would actually change their plan, then acted on what they learned.
How a materials test became a market-adoption project
The following example shows what happens when a team recognizes the promise trap and the comfort-zone blind spot, and applies the first three Vs (vision, vet, and value) to reframe the project and de-risk the real issue.
A defense contractor was working on frequency-hopping military radios. The real prize was large: shrink the antenna so command vehicles stop being easy targets on the battlefield. The company had the technology, a real strategic problem, and a field test lined up.
The project got scoped as a materials-science effort: qualify a new material for the antenna circuitry. That was the promise, small and deliverable. When finance modeled the returns, the numbers came out weak. Orders would trickle in one vehicle at a time, one design cycle at a time. On paper, the project was one of the smallest in the portfolio.
The core issue was the scope. The dream (shrink the antenna, change the market) was trapped inside the small project (qualify the material).
The team of materials scientists worked the part they knew and left the issue that actually decided the outcome untouched: getting radio and vehicle manufacturers to adopt the new material as a standard. No plan, no staff, no activity of any kind pointed at manufacturer adoption. The team had never raised the issue because it sat outside their expertise, and nobody in the room owned it.
Once the team reframed the project around the full vision, the work changed shape. They added a business-development effort aimed at the manufacturers, the effort that could actually open the market.
The business case, rebuilt around the dream, showed a fundamentally different return profile. A project that looked marginal as a materials qualification became a serious portfolio bet once the scope matched the opportunity.
What happens when the business case keeps running
The radio story shows what a single reframe can do: separate the vision from the promise, vet the real issues, and rebuild the business case around the full opportunity. The next example shows what happens when a team keeps running the loop, using the business case as a living document that points at the next assumption worth testing, cycle after cycle.
An agricultural-chemical company had a project with a modest initial valuation. Rather than locking in that number and executing against it, the team treated the business case as a working tool, updating it each time they learned something new about the market, the product, or the economics.
Over several years, each round of learning reshaped the project. The team opened a new market segment it had not originally considered. It reworked the pricing model based on customer willingness-to-pay data it gathered during incubation. It found ways to capture more of the value chain than the original scope assumed.
Each change fed back into the business case, which pointed at the next assumption worth testing.
Eventually, the project's value rose roughly 5X over that stretch. A promise-based system would have locked in the first valuation and called that a success. The iterative approach kept resizing the prize as the team learned, and the learning kept pointing the team toward higher-value work.
How Eli Lilly is re-imagining drug discovery
Eli Lilly, an American multinational pharmaceutical company with billions in annual revenue, applies the framework in early-stage drug discovery, the research arm where new medicines begin.
In pharma, the process splits into two stages with very different risk profiles. Clinical trials carry enormous uncertainty, but the company runs them with discipline because the questions, methods, and timelines are well understood. Early-stage discovery, the stage before trials begin, is where incubation happens. The uncertainty there is non-routine: the assumptions are untested, the blind spots are invisible, and the standard process doesn't surface them.
The problem Eli Lilly has is that scientists, understandably, follow the science. Left alone, they miss the issues outside the lab (the patient need, the patient experience, the commercial viability) that could redirect a project toward a stronger outcome for both the patient and the company. Science is the comfort zone, and the issues that would change a project's direction sit in business, regulatory, and patient-experience territory that scientists are not trained to examine.
To close that gap, Eli Lilly is rolling out the 6Vs framework across its discovery teams, training scientists to frame a project's vision in business terms as well as scientific ones, and to vet the issues a scientist would usually skip.
The rollout requires adapting the framework to pharma's reality. Eli Lilly already has decision-science specialists supporting the hundred-million-dollar bets of clinical development, but those methods are too heavy for an individual scientist facing many small, ambiguous calls early in discovery.
So they stripped the framework down. Skip the detailed financial modeling, because a successful drug is so valuable that precise early sizing adds nothing. Focus on the vision and vetting steps, where the blind spots actually sit. Give scientists a lightweight, repeatable way to make better decisions without turning every early-stage project into a full business case.
The Eli Lilly effort is a multi-year change program, closer to an HR-led shift in how people work than a tool rollout. The effort is still underway, but the payoff so far is better decision-making in the stage where the biggest bets originate.
Getting Finance to Trust the Incubation Process
Every example in this piece, the radio reframe, the agricultural-chemical 5X, the Eli Lilly rollout, depends on finance keeping the budget flowing long enough for the learning to pay off. In most companies, that trust doesn't exist.
"It's very ambiguous from the CFO's perspective," says Doug. "How is this money being spent, are we doing things in the right order, are we learning? How can we ensure we're being a good steward of those resources, and getting to failure points as fast as possible?"
Innovation teams avoid building business cases because the numbers feel like promises they'll be held to, and finance can't tell whether the spending is producing learning or just producing activity. The two sides stay apart until a big funding decision forces them together, and by then neither side is prepared. Any innovation leader who has walked into a CFO's office with a slide deck full of assumptions and no data to back them up knows how that meeting ends.
The agricultural-chemical company's approach works here: a lightweight business case, built in ranges and refreshed as the team learns, that gives finance something concrete to evaluate.
When the innovation team shares the business case with finance, the CFO can see the project's upside, the assumptions it depends on, and what the team is spending money to learn. Each update shows what changed since the last one. Finance stops asking "what am I getting for this money?" because the business case already shows the answer, updated every cycle.
The pitch to a CFO sounds like this: "I'm not promising a good outcome. I'm telling you I'm going to fund work that either eliminates the bad outcome or gives us a path to the good one. And if the learning shows the good outcome is out of reach, I'm going to recommend we stop."
A CFO who hears that pitch is looking at a team that manages innovation spending the way the rest of the company manages capital: with discipline, with evidence, and with a willingness to stop when the numbers say stop.
What You Can Do This Quarter
Adopting a full incubation framework takes time. For leaders who can't overhaul a new framework this quarter, two starting points make the biggest difference.
The first is to take a harder look at how the incubation process actually runs. Most leaders accept their stage-gate process and make surface changes, rewording the review template or asking people to be more evidence-based.
David's test is simple: if the decision meeting reviews 20 projects in two hours, no surface change will fix what happens in that room. As he puts it, "you can't get there from here." That realization, that the problem stems from the meeting structure and not the team, is the starting point. What must follow is a commitment to real change management.
The second is to get out of the comfort zone faster. Whatever a company is best at is probably not where its middle is failing. A technical organization is most likely tripping on the customer. A consumer brand, confident that the right consumer insight would solve everything, is most likely tripping on channel or technology. The company's strength is rarely where the middle is failing. The weakness almost always sits in the area the team would rather not touch.
Both moves lead to the same place: a specific project, a specific assumption, and a decision about who is going to test it.
Testing The Riskiest Assumption First
The messy middle stays messy because incubation still runs on governance built for the core business. That governance was never designed for it. The stage gates, the quarterly reviews, the demand for firm promises: these structures work well in the core business. Applied to incubation, they bury the assumptions that matter and reward the work that feels safe.
Running incubation a different way means testing the riskiest assumption first, using the 6Vs, and letting what the team learns decide where the next dollar goes. Governance stays out of the test itself, and steps in only at the verdict, when there's a decision to make.
The quarterly review that opened this piece had twenty projects, two hours, and no hard questions. Run that same meeting around de-risking instead, and each team reports which assumption it tested, what the result was, and what decision followed. Some projects advance. Others get killed early, freeing the budget for the bets that earned it.
But the outcome is the same: the CFO sees exactly where the money is going, and why.
