Bets on the future
The future bit is the hardest
This is a post about using “Minimum Viable Business Cases”
Are you any good at predicting the future?
Probably, you’re not. Most people aren’t.
The most celebrated study was by Philip Tetlock, who asked 284 experts to make a total of 28,000 predictions - all in areas of their own expertise. Tetlock then did something very unusual. He waited for time to pass and then checked the accuracy of their forecasts once sufficient time had passed for it to be possible to know whether they were right. He found that, once they were being asked to forecast a range of about 3-5 years forward, their forecasts were generally no more accurate than a chimp throwing a dart.
(As he points out in his book Superforecasting, he actually found that “the average expert did about as well as random guessing. Except that’s not the punch line because ‘random guessing’ isn’t funny. The punch line is about a dart-throwing chimpanzee. Because chimpanzees are funny.”)
Now, that’s a bit of an issue, given that most investment decisions are predicated on at least a 3-5 year time horizon. If even the most expert of experts can’t predict that far out, how on earth can investment decisions be made?
The answer isn’t to predict better, it’s to stop pretending we can predict at all. Instead of rigid business cases built on fictional forecasts, we should be using Minimum Viable Business Cases (MVBCs); an approach that starts small, embraces uncertainty and scales only when we learn what actually works.
Traditional Business Cases Are Built on Fiction
Most corporate investment decisions rely on a rigid, multi-year business case that assumes the future is predictable. But in reality, every project has a range of uncertainty: a spread between the minimum and maximum possible outcomes.
Venture capitalists don’t pretend to predict the future. They accept uncertainty and back multiple bets. If they get it wrong (which they will, many times), they cut their losses. But corporates pretend they can predict the future with precision, which creates the incentive to double down when wrong, instead of adjusting.
I’ve been able to see first-hand how VCs work when I founded and led a VC-backed startup, and it’s instructive just how different it is from corporate business cases. But should it be, given that they’re both exercises in making uncertain investments in the future?
Every year a typical VC firm will receive many thousands of business plans to review. Of these, several hundred founders will be invited to pitch. Of these, around 40 will receive investment. Of these, typically, 20 will fail entirely. Of the remainder, one will generate returns that exceed all the others combined.
Obviously, it would be much better only to invest in that one and skip the other 39.
But VCs don’t do that, and the reason is that it’s absolutely impossible to predict which one is the one.
The ratios described above are true not just for a London-based VC like Kindred Capital (the first VC to place a bet on Snap) but the most successful and valuable VCs in the world. Even firms like Benchmark in Silicon Valley (who backed eBay, Uber, Instagram, Snapchat and Twitter) back more firms that fail than firms that go on to win big.
So if the best investors in the world don’t expect to predict the future with certainty, why do corporates pretend they can?
The Case for “Minimum Viable Business Cases”
The reality is that some projects will crash and burn, and others will make it big. And no-one can possibly predict which. Traditional business cases assume a single forecasted outcome, but in reality, every project has a range of uncertainty - a spread between the minimum and maximum possible outcomes. The problem with corporate forecasting is that it locks onto one specific number and ignores this range.
So instead of focusing on a detailed financial forecast (which is actually just one scenario, but consumes most of the time spent preparing an internal pitch, time that could be spent not on honing the spreadsheet but on honing the actual proposal), corporates should adopt a different approach: the Minimum Viable Business Case.
But what is a Minimum Viable Business Case (MVBC)?
A Minimum Viable Business Case focuses on the best-case upside, allows for agile course correction, and avoids rigid long-term forecasts. It treats early-stage investment as an exercise in reducing uncertainty, rather than proving a pre-determined outcome. It prioritises small, testable bets over impossible-to-get-right projections.
Let me give you an example of why it’s needed.
When TfL first came up with the idea of contactless payments back in the 2000s, the business case was predicated on time savings through the gates. As predicted peak demand increased, the pace of throughput would require central London stations to expand to take wider gatelines. Real estate and construction in London is expensive, so it was worth a tech investment to avoid this cost.
What happened in reality was that contactless throughput turned out to be slower than Oyster, not faster. But then Covid came along and - in all probability - permanently suppressed high peak demand.
So the problem that Contactless was created to solve no longer exists and, even if it did, the solution doesn’t work to solve it.
So Contactless failed as a project?
Hell no, it’s been a triumph. It came into its own during the pandemic for obvious reasons, but it was wildly popular before that. For a while, TfL was the largest single contactless merchant in Europe. No-one will be able to prove it, but I suspect it probably delayed the decline in bus ridership by two years.
But on the basis of a traditional business case, Contactless failed. The range of uncertainty on this project was enormous: TfL’s business case focused on one specific benefit (gate throughput), but the real-world impact turned out to be something entirely different (popularity, ease of use, and resilience during COVID).
Contactless was a project with a huge range of potential benefits and upsides. Some of them came true, some of them didn’t. Some were included in the final business case; some weren’t. But it was a decent bet on the future that snuck through a business case method that should have rejected it.
ITSO, the Government’s smartcard standard, was another decent bet on the future. Back in the 1990s, smartcards were the future and setting a national standard was a sensible approach. Unfortunately, ITSO was a bad bet. The standard was too inflexible, the security requirements too onerous and the capabilities overtaken by alternative technologies.
When it becomes clear that a VC has made a bad bet, they stop investing. Immediately. And they don’t feel embarrassed doing so, nor do they feel a failure, because they knew that a proportion of their bets would be wrong.
But tied to a business case that is interpreted as making promises not predictions, a corporate will keep investing long past the moment when they should have drawn stumps. DfT has spent over £1 billion on ITSO, and most of it was after the moment when a VC would have given up.
The business case process
I’m sure lots of corporates do it differently, but everywhere I’ve worked, the capital investment process looks much the same:
1) A capital budget is allocated
2) Business cases are invited from managers
3) Each business case includes a multi-year financial forecast that must demonstrate a high return on investment.
4) Those with the highest return on investment are allocated cash
Corporate business cases therefore become an exercise in trying to engineer a high ROI based on a single forecast of the future. Often the version of the future is constrained by the corporate assumptions as to what the future will look like. If you’ve got a great project for a scenario that is perfectly plausible but different to the corporate central case scenario, you’re not going to get funded. If you can find a way to create an Excel spreadsheet that creates high ROI based on the template assumptions, you’ll win the jackpot for your project.
The forecasts you’ve made will now be baked into a budget and you’ll be held accountable to deliver precisely what you forecast. Managers that sponsor projects which fail will be lambasted while those that luck out will be heroes. Those lacking the self-confidence to make a five-year prediction with absolute certainty will stay quiet all the way through, and their ideas will never be heard.
Now, a VC doesn’t look at things like that.
What a VC will ask is: what is the maximum possible upside of this project? If everything goes best in all possible worlds, how good could this be? And they will look at the transformative potential of a project. They will review the numbers but they will exercise judgement.
Once the’ve made their bets, they won’t then hold each individual investment responsible for delivering precisely what they forecast in their central case. (Though they will support, encourage and motivate them to achieve they most they can). Internally, they will not make budget returns against their individual investments until it becomes clear how they perform in the real world. Instead, they will invest their fund and seek an aggregate return. If they undercut their aggregate forecasts, it means their judgement is wrong - and they’ll focus on how they can improve their judgement so as to make better bets in future.
I remember asking Leila Zegna (a partner at Kindred Capital and the best VC I had the privilege of working with) why they backed FiveAI (an autonomous car startup seeking to create a fleet of robotaxis to compete with Uber on the streets of London) given the extraordinary amounts of capital that FiveAI would need to burn before it became apparent whether or not they were going to make it. Her answer was that the upside was massive so it was worth a bet and even if their precise vision didn’t come off, they would be creating something that was valuable somehow.
Well, the vision didn’t come off. FiveAI have not and are not going to be running robotaxis around London. But, equally, they have built something of value: as they are using their technology as an assurance product for other autonomous vehicle products. Who knows if FiveAI is going to be The One for Kindred Capital, but that’s fine. FiveAI are to Kindred Capital what Contactless turned out to be for TfL: a thoroughly good thing, just not for the reasons they thought it would be.
So if a corporate finance department wanted to adopt the approach of accepting that the future is unpredictable, here’s what they might do:
Allocate a capital budget. That part doesn’t change.
Set an aggregate return target, rather than requiring each individual project to hit its own financial forecast.
Invite pitches from managers. Instead of requiring long-term forecasts, ask managers to present the maximum possible (not certain, just possible) upside of their project. The gap between the minimum possible upside (which is probably zero but might even be negative) and the maximum possible upside (which is very high) is the ‘range of uncertainty’. Traditional business case approaches pretend the range of uncertainty doesn’t exist: in reality, when we’re still at the Excel stage, it is very high.
Finance teams use their judgment to back a mix of high-risk, high-reward bets and lower-risk, smaller-impact bets. There is no attempt to quantify the total cost for each project yet, as no-one can possibly know.
The projects are each given the minimum funding necessary to reduce the range of uncertainty. That will normally be a pretty small real-world experiment to prove something that is currently assumed. In a project that might end up costing £10 million, the range of uncertainty can be considerably narrowed for £10k.
Finance closely monitors projects; not to hold them accountable to a rigid business case but to see which are performing well and deserve more funding as the range of uncertainty narrows for each.
The Shift in Accountability
Some in Finance may not like this approach because it shifts accountability from managers delivering against unrealistic forecasts to finance teams making better investment decisions.
But that’s where accountability should sit.
In this world, finance isn’t just approving business cases, they’re actively managing a portfolio of bets. Instead of acting as gatekeepers for unrealistic ROI projections, they focus on funding, monitoring, and expanding the right investments as uncertainty narrows. Projects don’t succeed or fail based on whether they deliver an arbitrary forecast; they succeed if they systematically reduce uncertainty and prove their potential.
And if, at an aggregate level, the company doesn’t achieve its forecast returns, that means finance needs to improve its decision-making.
This acknowledges the truth that none of us know what’s going to happen in the future, so we need to make multiple bets.
It’s weird how hard humans find it to accept the future is uncertain. But, if a manager in a transport corporate submitting a business case really was so talented at forecasting that (unlike Benchmark capital or Tetlock’s 284 world experts) they could predict financial results five years hence - well, they wouldn’t be a manager in a transport corporate, would they?
Take Action: How to Apply This in Your Organisation
The traditional business case approach is broken because it assumes we can predict the future with certainty when we all know we can’t. The best investors in the world acknowledge this by making bets based on potential upside rather than rigid forecasts. Corporates can do the same by embracing Minimum Viable Business Cases (MVBCs), an approach that starts small, reduces the range of uncertainty and scales up only when real-world results justify it.
If You Work in Finance or Investment Approval:
✅ Change the way you assess business cases. Stop asking for five-year ROI projections based on a single scenario. Instead, require managers to articulate the range of uncertainty: the gap between possible failure and possible breakthrough success.
✅ Fund to reduce uncertainty, not to execute a fixed plan. Approve projects in small increments, with just enough funding to test key assumptions. Require teams to prove something real before getting the next tranche of investment.
✅ Shift accountability from managers to finance. Instead of making managers responsible for delivering against fictional forecasts, finance should take responsibility for improving the quality of investment decisions over time. If aggregate returns are below expectations, the issue isn’t that individual projects failed, it’s that better bets need to be made.
(And, by the way, there’s an obvious point here that managers are still accountable for doing all the right things to run the experiments. I’m not saying that a manager that spaffed the budget allocation in Wetherspoons would be in the clear. Just that we regard the early stages of the project as a learning opportunity not a “prove-the-business-case-at-all-costs-and-hide-when-it’s-not-coming-true” opportunity)
If You’re a Manager Trying to Get Projects Funded:
✅ Reframe your pitch. Instead of forcing your idea into a rigid forecast, present it as a bet with a wide range of possible outcomes. Be explicit about the uncertainties and the potential upside.
✅ Ask for a small, staged investment. Instead of seeking full project funding upfront, propose a low-cost test to reduce uncertainty. Show how a small initial investment (e.g., £10k) can provide critical real-world data before committing millions.
✅ Make it easy for finance to back you. Finance teams are used to seeing traditional ROI calculations. Help them by explaining how their success should be measured differently, not by whether every project succeeds, but by whether they back the right mix of bets.
Conclusion:
Success in corporate investment isn’t about predicting the future, it’s about learning from it in real-time. The best organisations don’t just approve projects; they create systems that let the best projects emerge through iteration, learning and smart risk-taking.
The next time you’re involved in approving or pitching a business case, don’t ask “What will this return in five years?” Instead, ask “What’s the range of uncertainty, and what’s the cheapest step we can take to reduce it?”
Here’s an example of when this didn’t happen…
This post was published in May 2021 and updated in March 2025
