ESPN’s innovation dilemma

One pant leg on is a local maximum. One problem is solved but the larger set is not.

Clayton Christensen’s series on disruption and innovation is about local maximums.

Money machine go brrr is a strong incentive to keep printing. Maximizing a profitable business makes sense, which is the dilemma! Organizations find themselves looking good in one pant leg.

The solution to local maximums is exploration. But this is costly – money, status (uh oh), time, reputation. Plus the stakeholder’s opinions.

The solution, Clayton Christensen writes, is separation. Different groups with different strategies, finances, and when possible physical locations.

Solutions via exploration are important because customer and consumer preferences – their JTBD – change.

“We are all under the Disney umbrella,” Brian Burke said, “ is a huge enterprise with an army of people and is a revenue generator in so many ways. It’s difficult to change course. FiveThirtyEight is agile, nimble, and experimental so (publishing there) was a great opportunity”. go brrr.

Which is the dilemma, and Disney/ESPN uses FiveThirtyEight as the exploration solution. Who knows if Burke’s writing approach is better, but the publishing strategy is a solution to the innovator’s dilemma.

“The next” will be different. Whatever is next will have a different business model than the current Great Firms (Christensen’s subtitle). Whatever is next will have a different maximum. It will be a short vertical video or the degradation of the sport monoculture or something we can’t predict today.

Or even an analytic forward analysis from Brian Burke.

Creativity through randomness

“There’s a great point in your book,” host Adi Wyner says, “where your coach tells you you’re coming in too high in the tournaments.”

“This realization happens pretty early on. It’s six months into my poker playing and I’m very happy I’ve been cashing in poker tournaments. Say you buy in for $100, but the prize money is very heavy up top. Maybe only ten people cash and the person in tenth gets $110. You make a little money on your entry fee, but first place might be $10,000. That’s the disparity. If you consistently cash, but bust out soon after it means you are losing money because it’s not just entry fees, but hotels, travel, non-cashing tournaments.” Maria Konnikova, Wharton Moneyball, June 2020

Konnikova had “settled” on a strategy that seemed okay, but was not. Her coach nudged her off it, framing the true costs of winning poker.

Sometimes a coach knows what to do. Sometimes we are just figuring things out.

“One thing that this pandemic has made us realize is a collective failure of imagination. I’ve been modeling pandemics for twenty years. I’ve been modeling for local agencies, for federal agencies, and all of our models up until 2019 pretty much assumed that our next pandemic was going to be an influenza pandemic. A lot of our planing had been around making sure we had medical counter measures for influenza, playbooks, and game plans. The assumption was that there would be a six-month timeline for vaccines and we would use non-pharmaceutical measures in the interim time period. Covid19 really took us by surprise.” – Lauren Ancel Meyers, University of Texas College of Natural Sciences, March 2021

Covid took us by surprise, in part, because we lacked a coach. In these cases we need creative solutions. Lacking that, random ones work too.

“Each evening during their hunting season, the Naskapi Indians of the Labrador peninsula determined where they would look for game on the next day’s hunt by holding a caribou shoulder bone over the fire. Examining the smoke deposits on the caribou bone, a shaman would read out, for the hunting party, the points of orientation of the next day’s search.” – David Stark, The Sense of Dissonance, August 2011

Stark makes the point that this randomization element meant the tribe would not necessarily return to the last place they succeeded. But it also wasn’t totally random. The hunters still used their very particular set of skills on the hunt.

Lots of life is a balance of “do what I know works” and “find what works next.” The specific mix is contextual, but if we find ourselves in need of a change, and lack a coach, maybe a shaman can point us in the right direction.

Thanks Thomas for the shoulder bone source. Konnikova’s book, The Biggest Bluff chronicles her journey from starter to ‘casher’. We’ve touched on this idea here too: Local maxima of bees, marketers, and NASA engineers.

Local maxima

When stuck-at-home in 2020 my kids (12, 10 then) and I enrolled in the Marc Rober Creative Engineering course on Monthly. It was mostly above my engineering (and their in-depth interest) level but it was still great. We got to see Rober’s structure for brainstorming, more of the build process, and his thinking along the way. The hours of course video were like a documentary, a ‘Making of’ video.

One thing we saw was how Rober prototypes his builds. In the case of a making a candy launching device Rober made one using springs, one using compressed air, and one using hydraulics. The reason to prototype, Rober said, it to not get stuck at a local maxima.

Rober's sketches

We all have an idea for solving a problem and a lot of times we just do that. However in the situation we get more information. Rober suggests imagining a series of wooded hills. From the ground we don’t know which is highest (the best solution). So we need to hike up our best guess and look around from there. The hike up to, and the view from the top give us information on how best to act.

Rober’s process has come, in-part, from his years at Apple and NASA and making things like squirrel obstacle courses and glitter bombs. He’s a YouTuber with a very small staff, (no groupthink) so how might an organization avoid local maxima?

Rory Sutherland suggests following the bees. What’s great about Rory’s recounting is the structure. Organization direction is based on culture and incentives. Sutherland’s structure is one way to change the incentives.

“I think having two budgets, two sets of metrics, and two sets of incentives for exploit and explore. It would be utterly insane to learn something in a test and fail to exploit it by doing more of it. Make the most of what you know, but always invest twenty percent in what you don’t know yet. Bees do this where roughly twenty percent of bees ignore the waggle dance that tells you where to find nectar. The bees understand that if you don’t have these rogue bees the hive gets trapped at a local maxima and eventually starves to death.”

Part-of-the-question with a local maxima is the cadence of change: is a business more like Netflix or a pool construction company? Rober prototypes. Sutherland et al. ‘test counterintuitive things’. Some bees explore, some exploit. Each found a balance and designed a loose solution so not get stuck at the local maxima.