Five Fail-Safe Venture Heuristics

Leveraging a standard framework when evaluating a proposal — or new venture — can be helpful in determining potential opportunities and risks

By: Matthew Sinclair, Partner and Vice President of Engineering at BCGDV

I regularly get asked to judge hackathons — most recently the London Business School Hack in February — and, interestingly, judging a hackathon is not all that different from evaluating a very early-stage proposition of the kind that we see week in and week out at BCG Digital Ventures.

Something that I find useful — both when judging a hackathon, and when evaluating a new venture proposition in my day job — is a set of heuristics that I can check the idea against. I’ve collected, developed and refined them over the 26 years I’ve been building software.

As heuristics, they fall outside of any specific framework so they do not necessarily rule out the proposition entirely on their own, but what they do is raise a red flag for me that the proposition might not be quite strong enough to go through for further consideration. I’ve found them to be a fast and accurate ‘rule-of-thumb’ way to narrow down the scope of a proposition without being overloaded with information.

Here are my five favorite heuristics for evaluating proposals:

1. The “Feature Not a Product” Problem.

This is probably the most common thing that I see when evaluating propositions.

Regardless of the passion of the founders, sometimes the idea they are pursuing is not a full-blown product or service in its own right, but rather, a feature or subset of something else that already exists.

The danger here is that incumbents see the new idea and then just go on to add it as a feature to their existing product or service, squashing you in the process.

In recent times, this kind of thing has become standard operating procedure with incumbent social media networks as a way to kill competition from upstart startups.

2. The “Does Anyone Really Care” Problem.

This is a simple test to see if the proposition has any potential at all to capture users who really care about the idea.

  • Does the proposition have any early adopters?
  • Has the team been able to get anyone to pay to use the product or service in its earliest incarnations?
  • Is anyone shouting loudly or banging the table about the product and how it will change the world, even in its very early, very rough 0.1-alpha state?

If the answer is “no”, then there is a risk that they may never be able to get anyone to care about it.

3. The “You are Not the Product” Problem.

Far too often, founders confuse themselves for their users.

Rather than honestly exposing the product or service to real users with a rigorous attention to how it fares in real-world conditions, they mistake their own preferences and biases for genuine user feedback.

No matter what the founders might think, there is no substitute for putting the product or service in front of real users, seeing what they do with it, and then incorporating those learnings into subsequent iterations.

This problem is particularly apparent for me in my work because we sometimes come across “passion projects” driven from senior executives in the client.

Unfortunately, they can sometimes be quite removed from what their real users are doing and thinking and so end up anchoring on their own ideas rather than constantly testing and learning with their actual users.

4. The “Solution Looking for a Problem” Problem.

This is probably the saddest of these heuristics because you can have a situation where a team has spent an enormous amount of time and effort building something, but what they have built is a solution to a problem no-one actually has.

This is also known as the “build it and they will come” fallacy.

Engineers are particularly susceptible to this mistake (I know because I have made it myself, and more than once!) which is why it’s always good for a team to have a mix of engineering, design, product, and business skills working on the solution to balance out this bias.

If they don’t, the team may end up veering towards “solutioneering” rather than genuine innovation.

5. The “Multiple Miracle” Problem.

The idea here is that if I am evaluating a proposition, then I’m prepared to concede that the team can still succeed even if they have to create one miracle.

In fact, if a team is going for something really ambitious and they don’t require at least one miracle to pay off, then perhaps they’re not being ambitious enough!

However, if I look at a proposition and I see that the team needs miracle after miracle to come true for them to succeed, then I start to wonder if they may be too ambitious.

If the miracles start to pile up across design, business, engineering, and go-to-market, then I really start to get worried.

On their own, each heuristic can act as a useful test when evaluating a proposition. Taken together, they can work powerfully to help separate ideas worth pursuing from those that might be better off getting less attention. However, keep in mind that these are just heuristics and the best validation for any idea is to put real software in front of real users and ask them what they think.

This piece was originally published by Matthew on Medium.

Want to find out more? Start the conversation with BCGDV.

Find us on Twitter @BCGDV, LinkedIn, and Instagram.




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