There’s never any guarantee that your startup is going to scale to a massive valuation, or for that matter even get to the growth stage. But one surefire way to invite failure is to rest on the ingenuity of the solution and assume that growth will take care of itself.
You can’t just stop at a great solution. You have to turn that solution into an effective machine.
Now, I’ve never run a billion-dollar company, but that hasn’t stopped me from swinging for the fences. Here are the basic steps I’ve learned to get from viable solution to high-growth company, based on over 20 years building high-growth startups.
Step 1: Perfect the scalable solution
To begin mapping the path from solution to valuation, I’m going to use two high-growth startup examples from my recent past, plus a third example you’ll be more familiar with.
Ten years ago, Automated Insights started life as a college basketball data analytics website. Within five years we had turned it into a 75-person pioneer in Natural Language Generation technology that produced billions of reports across multiple industries. We sold to a private equity firm back in 2015, and that story continues today.
Three years after we sold Automated, I joined up with Scot Wingo, who had previously taken eCommerce giant ChannelAdvisor from startup to public company. I wanted to learn from him as well as help him scale his new company, Spiffy, beyond its beginnings as a mobile car wash.
Oh, and back in 1995, Amazon started selling books online. That’s the third example, and we all know how that ended up.
Amazon and Spiffy came into existence to solve a big problem, and roughly the same problem, a lack of strategic consistency in mobile product delivery and mobile service delivery, respectively.
Automated Insights, on the other hand, was a solution in search of its big problem. We had developed the science to automate the creation of insightful written stories from data, but the question always hung over us — “Exactly who needs this tech?” I admit the backwards approach to drive home the point that solving a big problem isn’t the only ingredient for success, or even the first ingredient in some cases.
At each of those three startups, a perfect solution was developed and waiting for traction. Amazon got a foothold in eCommerce by perfecting the delivery of books and CDs, much like Automated Insights cracked NLG by perfecting the generation of insights from college basketball data, and Spiffy is revolutionizing mobile service delivery by perfecting a few use cases in auto care and maintenance.
Step 2: Carve out a new market
All three companies started with an opportunity to take what they’d learned at a low level and solve a much larger problem.
Back to Automated Insights and our search for a big problem — it turns out that problem sort of developed around us: The overload of new data from various new sources — including IoT, mobile devices, and wearables — was creating a massive new need for data science. Data scientists were expensive, and we automated a lot of what they did with our tech.
So we started addressing a new market. We were no longer automated writers on demand, we were automated data scientists on demand. This was Natural Language Generation before we knew what NLG was. This was a much bigger challenge with a much bigger addressable market, but we had already been inadvertently addressing that market for a while, vertically, within sports.
We pivoted, and made a horizontal move to other industries, providing automated data science in finance, marketing, insurance, and on and on. Now when we asked the question, “Exactly who needs this tech?”, the answer wasn’t a single industry, it was a market segment in every industry: Anyone who had to analyze a lot of data quickly. In the mid-2010s, that turned out to be everyone.
Amazon and Spiffy approached their new markets in a much more proactive fashion. That approach included a vertical expansion into their current lines of business — fulfillment, technology, and logistics for Amazon and auto maintenance for Spiffy — as well as a horizontal expansion into other lines of business.
Amazon decided to sell anything and everything over the Internet, including bringing in third-party vendors to their platform. Spiffy began developing its own spinout software platform that could make mobile service delivery available to any service in any industry.