A lot of my work involves working with large, established enterprises to find new ways to reach customers. Sometimes, that’s “just” marketing, sometimes it’s product development, and sometimes it’s business model design.
Enterprise innovation is challenging. Most established models for innovation in software build on the concept of “lean” and “iterative/incremental”. The most common point of view is that you get better results by experimenting and integrating feedback than by planning and designing in the absence of customer interaction. For a 3-person start-up, a “minimum viable product” can be very minimal, but for a company with billions of dollars in revenue, and a reputation to protect, “minimum viable product” might be a huge commitment.
The best model I’ve seen is with a client known for their innovation (no names, of course); I’ve called their approach “escalating bets”.
Escalating bets as a portfolio strategy
Our client creates a portfolio of innovation “bets”. Anyone who has an idea they believe in and can meet a fairly low initial investment decision bar can get a limited amount of time (typically 6 – 12 months) and money to prove their idea is a winner. It’s a small bet from an enterprise point of view – many companies spend that much on discussing why an idea shouldn’t go ahead.
Each idea has to have an agreed proof point for the first bet, usually related to whether the idea can attract customers. “We can get 1000 people to sign up”. “We can get at least 10% of our users to spend more than an hour a day on this”. “Our first users will recommend us to at least 1 other person”.
If the bet pays off – if the team hit their goals – the company places a second, larger bet. 9 – 18 months, roughly double the original budget. They have to agree another proof point – typically involving customer acceptance and some kind of business case. And so on, and so forth. I’m pretty sure you’ve used products delivered in this way.
Why do escalating bets work?
Innovation involves risk. Companies focus on risk to reputation, risk to brand, risk to strategic priorities, risk to margin – but the bigger risks in innovation are finding a market, and – very simply – execution. The way most companies approach innovation is to place a small number of large bets – large R&D projects, consulting engagements with specialist companies, large product development teams. As each bet is large, and involves the careers and reputations of several senior people, the bets tend to be fairly conservative – incremental innovations, close to the defendable core of the business.
And if one of those large bets fails, it tends to make the business more conservative. I know of a large IoT innovation project that ran out of steam after 2 or 3 years, and a significant investment. The project was large, with a lot of management attention, and – from my point of view – imploded under its own weight. Different departments wanted to impress their own priorities on the innovation. Decision making was consensus-driven and slow. The large number of internal and external stakeholders and participants made the communication overhead almost unmanageable.
The basic concepts were great, it was the sheer size of the bet that brought the project to its knees. This doesn’t mean “IoT” was a bad bet – as a competitor proved just a few months later.
Escalating bets have two benefits.
The large number of bets means you have a better chance of success – VC companies expect only a small number of their start-up investments to pay off. Running a portfolio of small-ish innovation projects gives you a better chance of finding a winner.
More importantly, though, a small project with a clear goal has a better chance of success in most companies than a large project with a high-level goal. “Take 3 people and find 1000 customers” is clear, not threatening to the other departments in the company, and focuses attention.