Decision Intelligence has “Left the Lab”: Lessons Learned from 10 Years of Evangelism

When Mark Zangari and I started Quantellia, we began with a market research study to ask “if technology should do one thing that it is not doing today, what would that be?” Fulfilling the answers to this question was an audacious model for starting a business, and the journey has been anything but a straight line. But today, about ten years later, DI has gone viral. Check out the above google image search on “Decision intelligence”! I recognize some of the images, but many I don’t. And that’s a good thing.

We took a tough path: trying to create a discipline while selling into it at the same time. Along the way, I’ve kept up a steady push of thought leadership, starting with white papers and videos, and continuing through keynotes, a blog, and most recently, my upcoming book Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World.

I tried to interview everyone I knew who was doing DI in Link, but my apologies that I missed a few. Like this awesome guy. I googled him, and I think that’s Pranav from Busigence (which I did mention in the book a couple of times).

Their website looks like this. Its so aligned with how we think. How awesome is that? And I’ve never met them. This is the look of a left lab.

And a few years years ago, Cassie Kozyrkov from Google started amplifying this messaging massively. She’s brilliant, and awesome, and I love that she sees things a bit differently from me Lots of her thoughts are reflected in how I approached the writing to Link.

So, a few lessons learned if you want to evangelize your own new discipline 🙂

1. Write, write, write. Nothing beats content.
2. Look to the market for guidance ahead of academics. In my world, at least, the needs of potential end users were massively different than the incentive structure in universities. At best, academics might give you an idea or two. At worst, it can manifest a fatal distraction. This one was a hard lesson for me, after a PhD, which was all about giants and their shoulders. But keeping myself blind to current research for a number of years gave me “fresh eyes” with which to see the unsolved problems.
3. Don’t be afraid to pivot in the early days. We initially called the field “Decision Engineering”, yet learned along the way that this name just wouldn’t sell. So we changed all of our collateral and positioning. There were only a handful of folks out there, so the shift stuck.
4. DO NOT, by any means, trademark the name of a discipline. “Prescriptive Analytics” had an opportunity to be viral. But the name fell flat, despite its value. I suspect this is because nobody could use the name without a trademark violation.
5. More generally, realize you’re going to have to give a lot away. Know that a rising tide floats all boats. A discipline is, in an important sense, a commons, and evangelism is the act of creating a space for all to thrive.
6. If you’re trying to sell into the same discipline you’re created, then sell into verticals, to solve business-specific problems. Nobody buys a bare-bones platform, even for the most exciting new discipline.
7. Be persistent, be patient, and know that if your innovation has value, it will, ultimately, survive if you keep showing up. Peter Denning writes about Robert Metcalf in The Innovators Way. Metcalf spent 10 years selling Ethernet. It’s a slog: “…it is the dead of winter and I am in the dark in a Ramada Inn in Schenectady, New York, and the telephone is ringing with my wakeup call at 6am, which is 3am in California, where I flew in from last night. Within the hour I’ll be in front of hostile strangers selling them on me, my company, and its products, which they have no idea they need … If I persist like this for 10 years, and I do it better and better each time, and I build a team to do everything else better and better each time, then I get my new townhouse”. That’s about how the last 10 years have felt for me, too.
8. Be a good person. Be kind and generous with your time and content.
9. Understand that the time frame for starting a new discipline is considerably longer than to sell into an existing one (Rob Adams says seven years). This is probably going to take longer than most VCs will want to wait, so you’ll need to get creative with cross-subsidizing organic growth (we did it with ML consulting, strategic advisory, and writing projects).

And some challenges I haven’t yet conquered:

1. How to create an ecosystem, a community? We’re working on this a bit with the Responsible AI/DI Summit, but that’s not a commercial venture for us, rather a way to pay it forward. And there are at least a thousand fans in various discussion groups like this one. The question is how to activate this resource? Maybe it’s time to start a commercial conference? (Anybody want to partner on this?) Maybe we need an Impresario: someone to put on “the show” (whichi is broader than just a conference). Any takers?
2. How to combat entropy? “Decision Intelligence” means different things to different people. That’s not unusual, nor is it a serious problem. We need a crisper framework that unifies it all. The Wikipedia page is a start, but it falls short.
3. How to work effectively with other evangelists? The limitation here is more about hours in the day than anything else.
4. And, underneath it all, how can we leverage lessons learned from other disciplines’ formative periods to ensure that DI thrives, provides positive social value, and is, in a few years, ubiquitously helping us all to solve problems better than we ever have before?

Or, in particular, this:

From the video above: “Leadership is overglorified … there is no movement without the first follower…the best way to make a movement, if you really care, is to courageously follow, and show others how to follow…have the guts to be the first person to stand up, and join in.”

In other words, it’s not about me. It’s about you. Write to me, if you like. Or, better yet, just go do it.

PS breaking news: I just heard that Gartner’s written a DI report, saying that “Data and analytics leaders should use decision intelligence as a practical discipline framing a wide range of decision-making techniques.” See, I didn’t even know about it. Awesome.