“What is this actually worth?"

It's the five-word question every CFO eventually asks in the innovation budget meeting, and the one nobody on the team has a clean answer to.

Simon Hill, founder of Wazoku and author of Expected Value, has spent more than a decade watching this scene repeat: "We see big, thick lines being drawn through our innovation budgets, because we've struggled to show the value we've been creating," he says.

One popular sport solved its version of this problem a decade ago: football. For most of the game's history, arguments started and ended with the scoreline. A team could outplay an opponent for ninety minutes, lose 1-0 to a deflection, and the coach was gone by Monday. The result was the only number that counted, and it often had little to do with the performance underneath it.

The fix was a metric called xG, or expected goals. xG looks at every shot a team takes and asks how often a chance like this ends up in the net. Added up across a match, it gave football a leading indicator that held up when the scoreline didn't, and it now sits on screen during every broadcast.

Innovation boardrooms did not have a model like this. What Simon eventually built, after years of research, is the innovation equivalent of xG, called xV, or Expected Value. xV is a single number, denominated in currency, that a CFO will accept, and that innovation teams can use to decide which projects to back, which to kill, and which to wait on.

The framework, a formula with four variables and one ratio, sets out to finally establish one shared language between innovation and finance. It also sets the foundation for what comes after: tracking whether the value forecasted by xV actually materializes in the business, what Simon calls Realized Value, or rV.

This piece walks through the whole framework in detail, so that next time your innovation team encounters the value question in a meeting, the answer is already written on the page.

In his book “Expected Value: The System to Measure, Prove and Scale Value” Simon tells the xV story through a single character who represents the many innovation managers he has worked with over the past decade.

She is the Head of Innovation at a mid-sized company. On paper, she has everything an innovation leader could want: a board-level sponsor, a team, a budget that has survived three years of scrutiny. Her team has had a good year by the usual measures: two hackathons, hundreds of ideas, four pilots shipped, engagement up 40%.

The pilots have produced outputs she cannot describe and outcomes she cannot quantify. One has been quietly shelved. Another sits in the murky zone between "still learning" and "probably dead." Her scorecard measures what innovation teams have always measured — idea volume, engagement, pilot count, buzz — and none of it answers the question on the table.

Within eighteen months after that review, the team's budget is cut in half. Two of the four pilots have been killed without any structured learning captured. One of her best people has left for a competitor. The Head of Innovation herself is reviewing whether the role is still worth staying in.

She goes looking for the answer she should have had in that meeting. Most of the frameworks she finds measure what Simon calls velocity: time-to-market, throughput, idea counts, participation rates, engagement statistics, occasional success stories. Simon's argument is that none of these measures the thing innovation teams are supposed to produce in the first place, which, in his definition, is new value created.

Motion is not value and activity is not impact, he continues. What innovation should really be measured on is the currency it produces.

That was the system the innovation leader was looking for, but it did not yet exist in innovation. It already existed, as it turned out, in sport.

The breakthrough came from outside innovation entirely. In the book, the innovation leader's brother is a data scientist who spent his career in sports analytics, working with xG every day.

Innovation, he points out, has exactly the same problem football did before xG. The "scoreline", whether a pilot got shipped or a platform launched on time, is a lagging indicator, and often a misleading one. What innovation leaders need is a leading indicator of value, calculated from the evidence available now, that updates as new evidence comes in. They call this xV, or Expected Value.

The formula they end up with does for innovation what xG did for football: it turns a fuzzy, debatable, politically contested conversation into a number that can be tracked, compared, and defended.

The complete xV formula looks like this:

xV = Confidence × Predicted Value × Time Sensitivity × Strategic Fit

Four variables, multiplied together, produce a single monetary figure. The first three answer the question: is this a good idea? The fourth answers: is this a good idea for us?

Before going component by component, two properties of the formula are worth sitting with.

With these properties defined, it’s time to see how the four variables unfold within the formula.

Most innovation teams lose the conversation with finance on this variable alone, because they've been trained to conflate two different things.

Felt confidence is the conviction of the project champion, the person pitching the idea. It's built on months of thinking, customer conversations, competitive scanning, and instinct. It's what makes a founder pitch on stage with absolute certainty the idea will change the world. Simon, who has been that founder many times, knows it well.

Evidenced confidence is what's left when the enthusiasm is stripped away and the question becomes: what has actually been validated, with data, that a disinterested third party would accept as proof?

For most early-stage ideas, honestly assessed, the answer is: very little.

The Confidence variable in xV is scored from 0.1 to 1.0, based entirely on evidenced confidence, across six dimensions. A project gets a full Confidence score only when each dimension has real, documented evidence attached:

Each dimension is scored independently against documented evidence, including prototypes tested, willingness-to-pay signals from real customers, pilot data, capability assessments, and regulatory reviews.

A large healthcare company applied the framework to a live project. The team was six months into an AI-powered diagnostic assistant, with significant internal excitement, senior-level backing, and roughly $400,000 already committed. Simon walked them through their plans and asked them to run the Confidence matrix honestly, dimension by dimension.

The results were stark.

Technical feasibility scored 0.6, because the prototype worked in controlled conditions. User desirability scored 0.2, because clinician enthusiasm from a few conversations was not the same as evidenced willingness to pay from the hospitals that would actually buy the product. Market viability scored 0.2, because no pricing model had been tested. Operational delivery, implementation readiness, and regulatory compliance each scored somewhere between 0.2 and 0.4.

Aggregated, the Confidence score came in at 0.3.

That single number did more to refocus the project than the previous twelve months of steering-committee reviews. It pointed the team at the one thing that needed to happen next: stop investing in technical development, and go generate willingness-to-pay evidence from the hospitals, or stop investing entirely. Six weeks later, signal from two hospital pilots had lifted Confidence to 0.5, and the project had earned the right to continue.

The lesson for innovation leaders sits inside this story: low Confidence is not a reason to stop. It's a reason to know where to focus. xV turns the usual anxiety about an early-stage idea into a specific, fundable learning activity.

Confidence tells the team how much of the idea has been validated. Predicted Value tells them what the idea is worth, if that validation holds up.

One without the other is useless.

Confidence of 0.9 on something worth $100,000 is a rounding error. Confidence of 0.3 on something worth $50 million is a genuine opportunity, if the innovation leader knows how to invest behind building the evidence.

Predicted Value is the monetary upside if the idea succeeds, typically measured over a three-year horizon. Simon takes the three-year frame from the vitality index, a measure popularized by 3M and now used widely across R&D-heavy companies, which tracks how much of a company's current revenue comes from products launched in the last three years. Three years is long enough for a new product to compound, but short enough to still be recognizable as new.

And this is the variable where teams most often lose discipline; they confuse the size of the opportunity with the size of their claim on it.

Here's how it usually plays out. The Total Addressable Market deck says the opportunity is $50 billion. The project champion, the person whose job depends on getting the pilot funded, sincerely believes the company can capture $500 million of it. The skeptic at the back of the room, usually someone from finance, mumbles that $5 million is more realistic.

A familiar pattern illustrates exactly this dynamic going wrong: Project Phoenix, a celebrated AI prototype one organization loved, consumed $800,000 of investment without delivering a single cent of evidenced value. Meanwhile, an internal customer service tool that nobody had branded as "breakthrough" was quietly generating $260,000 in annual productivity savings. The buzz was on the wrong project.

The xV discipline cuts through the noise. The right number at the early stage is almost always what the team can see right now, not what they can imagine.

Simon's test for Predicted Value has three questions the team needs to answer, with evidence:

When the team can answer all three, the calculation is straightforward. Sum the cost savings, the new revenue, and any quantified risk or strategic value across the three-year horizon. That total, in currency, is the Predicted Value that goes into the xV formula.

When the team cannot answer all three, Simon presents a fallback: a t-shirt framework with pre-defined dollar bands for the organization. A typical set: Small under $1M, Medium $1M to $10M, Large above $10M. Each band is tied to a profile. Small affects a single department, Medium affects multiple departments or a significant customer segment, and Large is transformative at the organizational level.

The t-shirt approach is deliberately imprecise since precision at the early stage is, most of the time, a false signal.

Who does what in this process matters as much as the method. There is a clean division of responsibility between roles here, that's worth making explicit:

Ambition belongs to the team that has to build the thing. Predicted Value belongs to the system that has to decide whether to fund them.

Predicted Value tells the team what the idea is worth. Time Sensitivity tells them whether the moment matters.

This is the variable many innovation teams get wrong. They carry a default bias toward acceleration: every project has an "urgent" stamp on it somewhere, every sponsor wants their thing moving faster. xV flips the question: why are we not going slower?

Inside an innovation team, the mechanic runs like this:

Note that before any idea earns a Time Sensitivity above 1.0, two tests apply:

If neither test is met, the score stands at 1.0. If both are met, the score is probably somewhere above 1.2. And if the team cannot quantify the cost of going slower, the default stance is that slower is fine.

There is a deeper logic to this caution. Every innovation follows an S-curve: emergence, acceleration, maturity, decline. Urgency behaves differently at each stage. An emerging project almost never needs speed, because the market and the capability are still being built. An accelerating one almost always does. A mature one is often better served by deliberately slowing investment as the curve flattens.

Simon names the trap at both ends of the scale, calling it “The Icarus paradox”: fly too high and the wings melt, because of over-ambition. Fly too low, and you get what Simon calls "ambition deficit disorder," and the project never catches the curve at all.

Good innovation leaders navigate both.

The first three variables answer: is this a good idea? Strategic Fit answers a completely separate question: is this a good idea for us?

Simon has seen more than one project killed that was genuinely good, with a real market, a validated customer need, and a workable business model. Despite the positive signs, these were not good ideas for the companies that were building them.

Without capability, without a place in the strategy, without a right to win, a good idea becomes a sunk cost. Strategic Fit is the gate that “stops intruders” and “catches” projects like these.

It's the most composite of the four variables, because it packs four distinct checks into one multiplier. Each check is scored from 0.1 (weak) to 0.3 (strong), and the four scores are summed. The total Strategic Fit multiplier runs from 0.4 (weak fit) to 1.2 (exceptional fit).

This score isn’t just an extra note for the writing board: it produces a clear next move.

In the early 2000s, digital photography was climbing exponentially, and Fujifilm's core business, photographic film, was heading into terminal decline. Kodak, their great rival, was already on the path to the bankruptcy it would file in 2012. Fujifilm's leadership had to decide whether to defend a dying business or leap to an adjacent one. A conventional strategic-fit check on "move into cosmetics" would have raised the obvious objection: we don't sell cosmetics, we sell film.

Run Strategic Fit on that decision and it scores almost perfectly. The collapse of film made diversification existentially urgent. Film emulsions rely on collagen and nanoparticle chemistry, the same science that underpins modern skincare, so the company's technical advantage transferred directly. Global cosmetics was a large, accessible, growing market. And the anti-aging category was accelerating on demographic tailwinds. Four out of four, with or without hindsight.

Fujifilm launched its Astalift skincare brand in 2007. By the mid-2010s, the division that grew out of the move was a meaningful share of corporate profit.

Fujifilm survived the collapse of film. Kodak did not.

That is what Strategic Fit is built to surface: moves that look absurd from the outside and obvious once the right questions are asked.

With all four variables scored, calculating xV requires multiplying the scores:

xV = Confidence × Predicted Value × Time Sensitivity × Strategic Fit

A project with Confidence of 0.5, Predicted Value of $3M, Time Sensitivity of 0.7, and Strategic Fit of 0.9 has an xV of $945,000 today.

A month later, three enterprise customers signal willingness to pay. Confidence moves from 0.5 to 0.65. xV updates to $1.23M. The number moved because the evidence moved.

That trajectory, not the static snapshot, is where the real insight lives.

But even a moving xV is not enough on its own, and there is a reason why. xV tells the team what a project is expected to be worth. It does not tell the team what the project cost to reach that point. Two projects can carry an identical xV of $500,000 and still be fundamentally unequal. One might have spent $50,000 to get there. The other, $500,000. The first is a good investment. The second has spent almost as much as it is expected to produce.

A CFO comparing those two projects does not see equivalent bets. They see one worth backing and one close to breaking even, and the xV number alone does not show the difference.

That gap is what the next lens closes.

Back to the brainstorming session, the innovation leader and her data-scientist collaborator have the four-variable formula working by midnight. Over the next hour, as they start testing it on real projects from her portfolio, she notices a problem, and the problem is the same one every innovation leader has to wrestle with eventually.

What they need is a metric that would make a CFO lean forward in their chair. Not just a measure of what the idea is worth, but a measure of how efficiently the innovation team is converting invested capital into expected value. At roughly 3am they write it on the whiteboard:

Cost per xV point = Total Investment ÷ xV

Or inverted: xV Efficiency = xV ÷ Total Investment.

This is the ratio that closes the gap between innovation and finance, because it maps directly onto the logic every CFO already uses: how much capital am I putting in, and how much expected value am I getting out? It gives finance a unit they can benchmark, and it gives the innovation leader a way to defend the portfolio that doesn't depend on activity, velocity, or storytelling.

To see what this looks like in practice, here is the portfolio the innovation leader in the book ran through the system. Four real projects, pulled from a live portfolio, scored in the same week.

Project Alpha, AI customer service assistant. Internal R&D build. Big headline opportunity, but early-stage and expensive.

Project Beta, internal process automation. Aligned with an imminent system migration. Already has a pilot.

Project Gamma, blockchain verification. External partnership. Speculative, weak strategic alignment.

Project Delta, customer-facing mobile app enhancement. Delivered through an open innovation challenge rather than internal R&D.

Delta costs less than one-tenth of Alpha, has nearly double the xV, and is being built through an open innovation model rather than internal R&D.

That is not a coincidence. It is the broader point about how innovation efficiency compounds.

Open innovation challenges, when run well, access external talent for a fraction of the internal cost and generate higher-quality solutions by widening the pool of people working the problem. Delta is an extreme case, but the pattern is consistent across Simon's dataset: open-innovation approaches routinely produce cost per xV points between $0.50 and $5, while internal R&D builds sit closer to $10 to $50 per xV point. A ten-to-twenty-fold efficiency gap.

Then comes the allocation question.

Imagine a $500,000 quarterly budget. The traditional approach, back the biggest headline xV, puts the whole $500,000 into Project Alpha. Total xV generated: $480,000. The portfolio has spent $500,000 to create $480,000 of expected value. It's losing money before a single pilot ships.

Note here: the efficiency-based allocation produces more than four times the expected value of the traditional approach from the same budget.

This is the analysis that reframes the innovation conversation inside a board meeting. Not "look how much we did." But "here is the expected value per dollar we spent, benchmarked against open-innovation efficiency, and here is what we're doing next quarter based on the numbers."

Cost per xV point decides what gets funded. It does not decide whether the forecasted value actually arrives: that’s what rV does.

xV is a forecast. It tells the team what an innovation is expected to be worth. But predictions and outcomes are two different things, and an innovation function that consistently produces strong xV numbers without ever showing up in realized business outcomes ends up with the same credibility problem it started with.

Simon is direct about this: "We've gotten much better at predicting what innovations could be worth. Now we need to get equally good at ensuring they actually deliver that value."

This is where Realized Value, or rV, comes in.

rV is the measurable contribution an innovation makes to business outcomes after implementation. It is scored against predetermined metrics, across strategic, financial, operational, and risk dimensions, within defined timeframes.

Most organizations measure only the financial dimension. Simon's Value Typology expands that view into six categories, each with its own metrics and timeline:

In a traditional review, a project delivering new compliance capability, a reduction in regulatory risk, or a better customer-facing talent pool looks like "no ROI." But the Typology shows exactly where that value lives: Risk Value, People Value, Operational Value.

The data is derived from systems most organizations already operate:

The Typology tells the team what to measure. It does not, on its own, tell them how. That is the job of the Value Realization System, a six-step process that turns the Typology from a categorization into an operational discipline:

The innovation team's job is not to build new measurement infrastructure. It is to wire the project into the systems that already exist, on the terms Value Specification has already named.

This whole feedback loop is the real insight. Paired with rV, xV is no longer just a metric. It becomes a forecast discipline, constantly calibrated by rV. When the two align closely, the team's scoring is validated. When the gap is large, the team investigates why.

This is what finally makes innovation investment look like every other investment the business makes.

The CFO asking what is this actually worth? was never the problem. The problem was that nobody on the innovation side of the table had a number to answer with.

That is the shift xV makes.

What xV offers is not a better pitch, or a louder defence of the budget. It is a shared number, denominated in the currency the rest of the business has been using for a hundred years.

Once that number is on the table, the question in the room changes with it. And paired with rV, xV gets tested against reality. xV forecasts the value; rV proves it landed. That is the pairing every other function in the business already runs on, and the one innovation has been missing.

This is why the goal should not always be a bigger budget. Instead, it should be about sharper decisions, inside the budget, already approved. And that starts on Monday: with five projects, four variables, and one ratio.

Six months after that first cycle, the same innovation leader walks into a CFO review with the answer to what is this actually worth? already on the page.

Frameworks die in the gap between reading and doing. The four variables make sense on the page, the ratio is clean, the logic holds. But when implementation time arrives, nothing changes: the portfolio review runs the way it always has.

xV avoids that trap by being small enough to start now.

The minimum viable version fits inside a single working week, and it produces enough signal to change the next portfolio review.

The cadence that follows, running the same cycle every six weeks, is what builds the trajectory finance actually responds to.

Here's how your innovation team can implement it.

Pick a variety, not a test set. The temptation is to start with the easy ones, the projects where the answer is already obvious. Don't. The framework only earns credibility if it holds up against the messy middle of the portfolio.

A good five-project mix:

The goal is to stress-test xV against the full range of what sits in the portfolio, not to confirm what the team already believes.

Score honestly, in this order:

Every score carries a named sponsor. No anonymous numbers, no committee scoring. The point is to put accountability behind each variable from day one.

Run the formula for each project, then divide investment-to-date by xV to get cost per xV point. Rank the portfolio by efficiency, not headline xV.

That ranking is the one a CFO would produce if they had the team's data. It's almost certainly different from the one the team would produce on instinct, and that gap is the most useful output of the whole week.

Don't try to lift everything. Pick the single weakest variable on each of the top three projects, and build the next two-to-six-week sprint around it:

One variable, one sprint, one named owner.

Run this cycle every six weeks and document the results. A flat confidence score across two cycles says something. A falling trajectory flags a project for review before it becomes a zombie. A rising trajectory shows which projects deserve more capital next quarter.

By the third cycle, six months in, an innovation leader running xV walks into a portfolio review with something few others in their company will have: a confidence-weighted, time-adjusted, strategically-filtered, efficiency-ranked portfolio, with a sponsor's name on every score and an evidence trail behind every number.

That’s it for today.

If you made it to this point, I’m sure you took out your Excel and started drafting ways to work with xV. Hoping this edition will prove useful in changing your conversation and relationship with finance. Next time, we’ll explore why breakthrough innovation requires a different, "atomic" structure focused on learning over established corporate efficiency.

Hans Balmaekers
Founder, the Compass and Chief @ Innov8rs

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