The Trust ROI: Why Orthopedic Automation Fails (and How to Fix It)
Uncertainty, Overwhelm, and the Wisdom of Bull Durham
We survived the first quarter of the year. Congratulations everyone, job well done.
Did we hope for more than just survival? Of course we did! But hey, sometimes just living to fight another day is a victory and we still have nine more months to hit our KPIs, deliver our OKRs, and nail this fiscal’s BHAG.
So, let’s take a moment to focus on what really matters: Baseball is back!
Along with the hope of the new season, and the warm weather that comes with it, comes an excuse to revisit the wisdom of classic baseball moves. In 2021, I wrote about Moneyball’s lessons in innovation and it continues to be one of the top read posts on my blog.
If you feel overwhelmed by Q1, fear not! There’s no greater source of advice on finding simplicity, solving problems, and leading people than Bull Durham.
When you’re overwhelmed, go back to the basics.
Skip: This… is a simple game. You throw the ball. You hit the ball. You catch the ball.
The Durham Bulls are 8-16 and Skip (the manager) has had enough. He’s tried every tool in his coaching toolkit and the team continues to perform poorly, display a poor attitude, and deliver a halfhearted performance. Overwhelmed and frustrated, he turns to veteran player Crash Davis for advice. “Scare ‘em,” Crash offers and what comes next is one of the greatest tirades on film.
But the greatest lesson here is what comes towards the end of the tirade: a description of the utter simplicity of baseball. There’s no strategy, no competitor analysis, no number-crunching, just a simple explanation of the most basic elements of the job. Throw. Hit. Catch.
It’s easy to get overwhelmed by news, technology, corporate politics, the list goes on. That overwhelm causes us to worry, lollygag, and obsess about what could happen. But when we cut through all that to find the essence of what we do and why we do it, things become remarkably clear and the next steps feel obvious.
Fall in love with the problem. Not the solution.
Zeke: We need a night off just to stop our losing streak. We need a rainout.
Crash: I can get us a rainout.
The Bulls are on another losing streak but this time on the road. As the team bus pulls into another motel and the players gather their bags, they complain about their problem (losing streak), propose an approach (night off) and propose a specific solution (rainout).
When Crash promises a rainout, it’s not because he knows something about the forecast the others don’t. It’s because he understands that there’s more than one way to get a night off. Like breaking into the ballpark, turning on the sprinklers, and flooding the field.
When we fall in love with a solution (rainout) we get stuck. We focus on making one thing happen, when critical dependencies are beyond our control. But when we fall in love with the problem (need a night off to stop a losing streak), we’re able to see less obvious but more likely and effective solutions.
People first. Problem solving second
Larry: [Jogs out to the mound to break up a players’ conference] Excuse me, but what the hell’s going on out here?
Crash Davis: Well, Nuke’s scared because his eyelids are jammed and his old man’s here. We need a live rooster to take the curse off Jose’s glove and nobody seems to know what to get Millie or Jimmy for their wedding present. We’re dealing with a lot of sh*t.
Larry: Okay, well, uh… candlesticks always make a nice gift, and uh, maybe you could find out where she’s registered and maybe a place-setting or maybe a silverware pattern. Okay, let’s get two! Go get ’em.
The Bulls are finally on a winning streak, but off-the-field issue are affecting on-the-filed play and things aren’t looking good. As the players gather on the mound, the team’s Assistant Manager trots out to figure out what’s going on and get the game going again.
After Crash sums up the personal issues, instead of telling the players to be professional, leave their problems at home, and get on with things, Larry focuses on solving the single issue affecting the most people first. It’s only when the players start nodding that he shifts everyone back into work-mode.
Only on Severance can we separate ourselves into work and life modes. Pretending that isn’t the case is counterproductive and toxic. But we can’t let one consume the other because it will ultimately degrade both our professional and personal lives.
As leaders, we need to find the balance between helping the humans grapple with real and personal issues and getting the team (back) on track and doing great work.
Ready to keep playing?
Baseball is a game of survival. A foul tip keeps the at bat alive. A walk keeps the inning alive. A bloop single to score a runner send the game into extra innings.
Winning takes patience and perseverance because the game is rarely won or lost in a single at-bat or inning. Just like you don’t win or lose your KPIs, OKRs, or BHAGs in a quarter.
As we start a new quarter, let’s keep it simple, focus on solving problems, and put people first.
Go get ‘em.
You’re Addicted to AI. That’s by Design.
“AI is the new cigarette.”
When a colleague said this in the waning days of 2022, days after ChatGPT burst on the scene, she took my breath away. The idea that this miracle would kill us seemed confined to hysterical handwringing foretelling the birth of Skynet.
She was right.
But neither of us knew it was designed to be that way.
Designed for addiction
My friend predicted that ChatGPT would stay free and helpful until usage reached “critical mass,” and then we’d have to pay. Less than three months after its November launch, OpenAI introduced its $20 per month service.
But it’s not the “first one’s free, the next one will cost you” aspect of drugs that makes AI addictive. It’s the design decisions at its core that keeps you coming back:
- Purchase Decoupling in which you convert real money into tokens, creating psychological distance between you and your actual spending
- Difficulty Curve where skills and benefits accumulate quickly giving you the sense that you’re becoming more capable over time and therefore more committed after progress slows.
- Skill Atrophy where every skill you stop practicing because the machine does it for you, quietly disappears.
Even casual AI users have experienced one or more of these:
- You get a message mid-chat telling you you’ve used all your tokens and need to come back in three hours even though you’ve paid your monthly $20 fee
- You’re prompting in all caps because it’s the only way you can think of to get the LLM to stop hallucinating, while reminiscing about the days when it was a brilliant thought-partner
- You’ve relied on AI to outline articles for the last several months, but you need to write in a different style and have no idea how to get started.
And yet, we keep going back.
But it’s not just individuals who are addicted. It’s entire organizations.
Signs that your organization is addicted to AI
Your CFO asks for the total AI spend across the organization. Three weeks and four departments later, the number is three times what anyone expected because the licenses are buried in IT infrastructure budgets, the pilots are expensed as innovation projects, and half the tools were purchased by business units on corporate cards.
The board approved the AI transformation initiative based on the pilot results. Eighteen months later, the pilot case study slide hasn’t changed, headcount has been reduced in anticipation of productivity gains that haven’t materialized, and the team running the pilot has quietly moved on to other work.
You eliminated the analyst pool two years ago because AI could do in minutes what they did in days. Now you need to evaluate whether the AI’s output is actually correct, and you’ve just realized there’s nobody left in the organization to check it because everyone who’s done it is gone.
Sound familiar? Your organization is an addict.
Recovery is possible
Addiction can’t be cured, only managed. The same is true for AI.
The road to recovery starts in a similar place: Visibility
- Centralize AI spending the way you centralize other business processes AND allow some flexibility by setting strict spending limits and clear decision-making criteria and ownership.
- Start pilots with the end in mind by establishing success metrics and scaling plans at the start of the pilot, not when it’s already in process.
- Treat certain human capabilities as strategic reserves the same way you’d treat any critical operational dependency. Before automating a function, explicitly document what judgment and expertise currently lives there, who holds it, and what it would cost to rebuild it if needed.
Unlike cigarettes or gambling, we’ve reached a point where we can’t quit AI.
But we can be aware of our addiction and we must manage it.
The first step is admitting that it’s real. And by design.
