How to identify your riskiest assumption

Richard Branson, the billionaire adventurer, has a complicated relationship with risk. On the one hand, he loves trying outdoorsy stunts and attempts to break world records.

Richard Branson getting punched in the face

Branson as an expert at managing the risk of getting punched in the face professionally

For example, he managed to cross the Atlantic, Pacific, and then circumnavigated the globe in a balloon. He even succeeds at doing so, despite the occasional crash:

On the other hand, he’s brilliant at managing his risk professionally, when starting new ventures. For example, thirty five years ago, he was stuck for hours on Peurto Rico. He wanted to fly to the British Virgin Isles to join his girlfriend, and came up with the following scheme:

Branson walked to the back of the plane and asked for a chalkboard and a writing implement. He figured out how much it would cost to charter a plane to BVI — and how much it would cost each passenger if the expense were pooled. And then he went for it, walking up and down the aisles of the grounded airplane selling tickets. On the chalkboard he wrote, “$39 one way to BVI.”

In one move, he confirmed that there was demand for an alternative. So he charted it. That got his appetite wet. Piggy-backing on his record store chain, Branson went on to sell plane tickets. He entered into a conditional lease of a plane from Boeing, where he insisted on having a one year break clause, to be able to return the plane if necessary. He aimed to fly it between the UK and the Falkland Iles. So Virgin Atlantic was born.

Your riskiest assumptions are probably related to your prospects and customers. Establish empathy quickly with your target prospect, figure out what's valuable, and get your innovation into the market.

In short, he made a couple of moves which significantly limited his downside while giving him the possibility of evaluating whether it was worth soldiering on.

With new products, your primary goal is to manage your risks

Denying the existence of risks only makes you more susceptible to them. Particularly when you are faced with a high risk of failure. Like 50-90%, depending on the study you look at. No joke.

“Jed’s dead. Dead dead.”

It’s really important to note that this is not about being pessimistic. Or questioning your vision. This is about figuring out your vision’s fastest possible path from your head and into reality.

The “magic pixie dust” resides in prioritizing what you test. By testing your riskiest assumptions first, you reduce the chance you go belly up. Regardless of where you are in your new product’s journey, you will always face unexplored or unmitigated risks.

Yet, identifying this riskiest assumption is hard. The key factor to consider when managing your resources (including your time) is risk. All of that requires you to have a solid grasp on what your biggest risk actually is at that moment. Which isn’t always easy, particularly if you are doing something new.

What makes this particularly hard: it’s likely there are some “unknown unknowns”. So even if you do deliberately try to identify problem areas, you’re likely to miss something.

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Essentially, the idea is that you want to generate a large number of ideas about what’s risky. And then prioritize to identify what is riskiest (and were you need to start).

Ways to get inputs on what’s riskiest:

Create an explainer video for your complicated new product. Make sure your audience understands it, without being overwhelmed by technical details.

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1. Intuition

This is hard to describe. Sometimes you just have a gut feel. Pay attention to it. And run with it. Essentially, you’re looking for what feels like it could have really big & bad implications. And it is likely to be a problem.

Personally, I feel this with tension in my gut. So it’s just a question of tuning into that sufficiently, especially before making bigger decisions. And that’s often good enough. But it has taken some effort to be aware of this. Moreover, in a larger company, you may still need to convince others and create alignment, and “I feel it in my gut” is not a strong enough argument. Even if it’s true.

2. Who is the customer and does the customer actually have problem you think?

This is a great insight I got from Lean Startup Machine specifically. Running around London like a headless chicken with some friends, trying to interview young parents. (admittedly before I was one myself). We had a product idea which we though would be attractive for this group. We made some guesses about their biggest challenges. And then we hit the streets and looked for anyone pushing a buggy/pram.

This was the net result:

hitting a low point somewhere during 67 customer interviews in one weekend


After a few failed hypotheses, we had to acknowledge that we actually had no idea what parents of kids 0-2 years old struggled with. And while there were some patterns in what we were hearing, it was clear that it was still too wide of a market to have clear patterns. The tool on the wall helped us systematize testing:

  • who is the customer?
  • what is their biggest problem or challenge?
  • would the solution be an appropriate solution to that problem?

In the end, we had to acknowledge that we the pie chart we were drawing had too many possible answers.

survey of product managers


So we weren’t going small enough to have a clear pie chart, with a significant share of answers being the same:

 looking for well ordered market segments like this


In other words, we needed a consistent easily identifiable & reachable group of people who share a particular challenge. That is a good market segment on which you can build a business.

This is almost always true. And often overlooked up front. Without it, you’ll have a hard time building something that will be relevant for enough people to make a dent. At least in a B2C business, where you need a lot of sales to get started.

In a B2B business, that breadth is less important, as much as depth. You need to be certain that whatever you do build and launch fully addresses the customer’s problem. And has positive and measureable side effects around:

  • increasing revenues
  • reducing costs
  • lowering risks
  • improving their customers’ experience.

At a high level, most businesses will only pay for those outcomes. But each industry and business is a bit different, so you will need to dig into the details of how to achieve it. But the starting point is really deeply understanding the problem from your prospects’ eyes.

3. Analogs

In short, ask people having similar success in different areas or industries doing things similar to what you want to achieve. This was an insight from Getting to Plan B by Komisar and Mullins.

For example, let’s say you discover a really powerful yeast which helps give red wine a unique and attractive flavor. Then you buy wine in bulk, add your magic dust, and then try to resell it to large supermarket chains.

Coming up with the yeast was the hard part. To figure out how to sell the supermarkets, you can probably speak to any salespeople who also sell to supermarkets in your country. It doesn’t have to be other wine merchants or wholesalers. You will learn a lot from a few conversations with people like that, enough to get your head around how this sales cycle works. So even though you don’t have in depth experience doing it yet, you’ll have a clear picture of how to proceed. In this case, you are using an analog to discover any hidden assumptions that could derail the use of direct sales as a distribution channel.

Channel testing example: selling superior wine into supermarkets


This is a good technique to turn “unknown unknowns” to “known unknowns”. Possibly even “known knowns”. Even though it’s less likely to have a company killer impact, it is still possible that you are making assumptions about that initial sales process which could derail you.

4. Antilogs (or Picnic in the Graveyard)

Some industries, especially software and internet, have a lot of public information about startups that have tried something. And failed. There are lots of writeups by previous founders of why they think their startup failed, such as:

If you are thinking of building something similar, you are just at the beginning. Those founders had been through years of trying to get a similar idea off the ground. So it’s quite likely you will learn something from them, if you can read about their failed attempts. Or even better, call them up and speak with them directly.

The idea here is to formulate a good reason why you think you will be successful this time around. It might be a different feature or market. It might be market timing. It might be any number of reasons. Because if you can’t articulate it, it questions whether it’s an idea worth pursuing. Not to mention, it will be hard to convince investors, too.

5. Risk Scorecard

This is kind of the left-brained alternative to #1 above. Basically, you can create a spreadsheet scorecard, where you:

  1. list all of the risks
  2. assign each a weighting from 1 to 5 for both likelihood and impact
  3. multiply the weights together
  4. reverse sort by the highest number going down

The outcome is that you have 1 specific risk you need to address and start focusing your experimentation on.

Here is a more detailed writeup of how to do this. Or here.

6. Pre-Mortem

Imagine your business failed 4 years into the future. You meet with your cofounders over beers or tea. As your tears flow, and drip on your Business Model Canvas (BMC), you discuss what you wish you would have known up front.

Which is the likeliest to have caused the failure?

  1. Write down all possible additional reasons you come up with onto post-its.
  2. After a general session, you can also think through any assumptions in each box of the BMC which might be relevant for this particular business.
  3. Prioritize them using dot-voting
  4. Create an initial risk backlog based on this discussion, sorting from the most dots down to the least

The best source for this is Dave Gray’s excellent Gamestorming book, if you need any more detail. But that should get you started.

7. My “ace in the sleeve” questions

Based on my own mis-adventures in startup land discussed in Launch Tomorrow, I have a few following additional questions which I use to “stress test” any idea:

  • Am I going after the right customer–for me or my company? Is it a strategic fit?
  • Can I reach my customer cost-effectively?
  • Is this customer type willing to do anything about the problem? Because if they aren’t, they aren’t likely to spend any money.

So for example, it’s a good idea to build a business around a group of people you can easily relate to and who you like. I tried building a business in the weight loss industry despite not having a medical background or being a middle-aged woman. So while I did have a signature success story in this context, my marketing would always be less effective than if either of those requirements were fulfilled. And I wasn’t keen on going back to school to become a doctor first.

All of these do matter in certain contexts. And they’re probably good “spot check” questions anyway, before you proceed with a specific idea.

8. Talk to industry experts

Once I get outside of the internet and software worlds, there is a lot I don’t know. Lately, I’ve been working with AgriTech and MedTech startups, for example. And while I know the concepts behind innovation, I honestly don’t know have that much experience in how they apply to those sectors.

For example, agriculture has a “crossing the chasm” like curve. However, it’s heavily skewed to the right. So basically, there are many more people in the late majority or even the laggards. In other words it takes a lot longer for a technology to diffuse. But when it does, it’s everywhere.

negatively skewed tech adoption curve


Anything related to medicine has to go through regulatory approval. In this case, you can’t just pooh pooh the regulators like various marketplace startups did (Uber, AirBnB). People’s lives and health are potentially at stake. In practice, for founder this means it takes a decade before you can go to market. Which means two things:

  1. you need a lot more money up front
  2. you have less attempts at building a business during a founder’s lifetime

In short, these industry specific details significantly change how you’d look to innovate in these areas. And I learned both of these points from experts with decades of expertise in the industries (thanks Huw and Anthony).

From a risk management perspective, expert’s ideas are simply ideas that require testing. You don’t want to ask experts for their opinions and treat it as gospel either. As that would mean you replicate their biases. Gather your own data and proof. But at least you know what to pay attention to.

9. Red team, Blue team

Finally, to stress test your business model, you can use this approach that the British military came up with. This is a strategic exercise, to try to identify any holes or oversights in a plan. The red team tries to penetrate a well designed defense plan.

  1. Essentially nominate a few well-meaning friends.
  2. As them to “red team” your current business model.
  3. Looking together at the current BMC together with your “blue team” consisting of the co-founders or delivery team, ask the “red team” to identify any major assumptions you might have missed. Holes that need to be covered. Things which could easily go wrong and derail your product launch.

There was a good example of this in the HBO serial Newsroom. The news team was working on a high stakes story. Certain people were intentionally kept in the dark about the big scoop. When the team producing the story was ready to go live, they assembled the people who had been intentionally left out to form a Red Team. The Red Team’s job was to poke holes in the story, as the paper was risking its reputation by going live with this story. People kept in the dark are more objective. They aren’t invested in the story, so they see it from a different perspective.

What you are after

Basically the goal is to uncover as many assumptions as possible. And to prioritize them. So you have 1 specific assumption to start testing. This focuses your experimentation on company killers and existential risk, the most meaningful place to start managing risk. This is, in fact, what successful founders like Branson excel at–like when he put up a cardboard sign and started confirming there was enough of a market to create a challenger airline.

If you can take smart risks while being better at managing them, then you are much more likely to do better over the long run. Any particular risk might still go sour. But this ability to manage risk will ultimately define your career as a startup founder and business builder.


4 approaches to track your assumptions, when starting to work on a new business idea
In The Origin and Evolution of New Businesses, Amar Bhide reported that 2/3 of the Inc 500 company founders

Why your riskiest assumption is a great place to start with any new product or idea

Proving the supply side (as they were ridiculed)

For the supply side, the team needed to confirm that they could acquire landlords. But also that landlords would be interested in following the model the founders pioneered. An extra income on the side might not entice enough landlords to make it all work. AirBnb found conferences to be a clear case of insufficient supply. So they continued down that route. When they launched the company “officially” at SXSW in 2008, they made 2 bookings. But then when they managed to get blogger coverage around the Democratic National Convention in 2008, they made 80 bookings. (official company history). That was enough to confirm that–under the right conditions–people were happy to rent out extra space. Yet the marketing was still a struggle:

And we don’t blow up. No one wants to use the site after the DNC. Most people think we’re crazy. My mom thinks I’m out of my mind. All of our friends later tell us they thought we were crazy.

So with risky assumptions on both sides of the market validated, it made sense for the team to shift gears. To start investing time and effort into the product.

Now imagine if either the demand or supply side of those assumptions had turned out false. For example that homeowners didn’t want to do short term lets. And to be fair, most people in 2001 would probably have felt awkward about it. The team could have built the product, yet they would have found it next to impossible to grow it. Because they wouldn’t be able to offer tourists anything. And vice-versa.

Building something nobody wants is one of the most common reasons for product failure. If not the single biggest reason (depending on which survey result you look at). At the time, it would have been somewhat hard to believe. Part of commercializing the product is convincing everyone that counter-intuitive beliefs are true.

Then when estimating market size while raising funding, they were ridiculed some more…

For example, this comes up when raising funding. Initially, the founders thought the breakfasts were the draw. But breakfasts were a smaller market than beds.

How to you get serious investors to believe that the market size for “people willing to sleep on air mattresses” is a multi-billion dollar market? Or that it will be in 10 years, even if it isn’t that big now. Chesky quips, “Suddenly, the market size was huge, except we were still selling air beds. Like, “We’re going to make $30 billion with these air beds. Everyone’s going to live on air beds.” This is a classic conundrum for these wonky startups which navigate a social change cycle as they grow. How do you estimate the future market size of a market that doesn’t exist yet, but may end up being huge.

Then AirBnB were attacked as they drew attention scaling up

For a long time, hotels claimed they were serving a different segment than AirBnb. They didn’t need to acknowledge the presence of the rapidly scaling startup. AirBnB maintained close to 100% growth annually for 10 years. This growth came from having proven the risky assumptions before everyone else. Then built a product and a platform to capitalize on that insight. This ensured they were relatively unique.

6 traps when choosing operational metrics for software or digital teams

Because it’s highly conceptual, software development is notoriously difficult to manage with data:

In an effort to get a bit more quantitative, I started peering into our source code control system. For each person on the team, I noted down the number of commits, or changes to the code, they made over a monthly period.

Focusing on efficient output while losing sight of outcome

This is a really common one in the context of waterfall project management. The three underlying variables that are optimized there are:

  1. % utilization: how much time each person spends working
  2. % completion: a (usually highly subjective) estimate of how much of the work is done
  3. how this relates to predetermined dates that were agreed at the beginning of the project

While in theory all of this sounds like a great idea, these metrics are devoid of a measure of output and more importantly outcomes. Don Reinertsen ( @DReinertsen) has a concise summary of why this is madness: “In product development, our problem is virtually never motionless engineers. It is almost always motionless work products.” All of the above metrics focus on what the people are doing or not doing. Not on whether the product is getting built.