Ep 296 – James A. Seechurn (Author and Advisor)

1. Most companies are “cutting the cape” instead of solving the real problem

One of the best ideas from the conversation came from James’s story about a child wanting to cut Batman’s cape off. The first instinct is to react to the request literally. But the real issue is usually underneath it.

In companies, that same pattern shows up all the time: leaders say performance management is broken, top performers are leaving, or people want more differentiation — so the organization jumps straight to redesigning merit cycles, bonus plans, or ratings systems.

But that often means changing the most visible mechanism instead of diagnosing the actual issue. Pay is easy to tinker with because it’s concrete, measurable, and highly visible. That doesn’t mean it’s the right lever. James’s point was that too many HR and reward projects start with a solution before anyone has really defined the problem.

“The instinct is to tinker with something. And it’s usually pay… because it’s the most visible thing.”

That’s a useful gut check for people leaders: before you redesign the process, ask whether you’re fixing the root cause or just making the spreadsheet prettier.

2. Pay for performance sounds fair — but breaks down fast in knowledge work

A big part of the episode centered on the gap between what people assume is fair and what actually works. Most employees say they want their pay tied to their own performance. On the surface, that sounds obvious. But James pointed out that the research is much messier than our intuition.

In knowledge work, it’s incredibly hard to isolate where one person’s contribution starts and another person’s ends. Most work is collaborative, interdependent, and shaped by context that a manager can’t fully see. Even in functions like sales and marketing — where leaders often assume attribution is cleaner — the reality is still fuzzy, because results are shared across teams, handoffs, systems, and timing.

“We are mostly knowledge workers… solving complex, abstract, basically impossible-to-define problems in a collaborative way.”

That makes annual attempts to assign precise individual reward outcomes feel more objective than they really are. The takeaway is not that contribution doesn’t matter. It’s that many organizations are pretending to measure something they can’t actually measure well.

3. The real question isn’t “How do we drive more output?” It’s “What does performance actually mean?”

One of the strongest reframes in the episode was James’s definition of performance. In a lot of companies, performance gets reduced to output volume: more tasks completed, more content shipped, more pipeline generated, more activity logged.

But James argued that this is far too narrow — especially in a market where products, competitors, and customer expectations are changing constantly.

For him, performance is really about survival and relevance. Are you still creating ideas, products, and solutions that keep the company competitive? Are you adapting quickly enough to changes in the market?

That shift matters because it changes what leaders should optimize for. If performance means innovation and adaptability, then systems built around narrow individual output metrics can actually make the company weaker.

“Performance is survival. Performance is relevance.”

That is a much more useful definition for people leaders. It pushes the conversation away from “How do we pressure people into doing more?” and toward “How do we create the conditions for better thinking, better collaboration, and better ideas?”​

4. If you want better performance, build for autonomy, competence, and relatedness

But the real unlock is creating the right conditions.

The three that matter most:
Autonomy — control over how work gets done
Competence — the chance to improve and master something
Relatedness — connection to a team and shared purpose

When those are present, people naturally do better work.

When they’re not, performance systems start to backfire.

“You don’t have to drive anything. People aren’t lazy.”

The problem is most systems do the opposite: Over-specifying goals, micromanaging execution, measuring narrow outputs

That leads to compliance — not innovation.

5. The companies that innovate don’t squeeze harder — they create space

James gave a few great examples of what this looks like in practice. He pointed to 3M’s famous 15% time, which helped create the Post-it Note, and Google’s 20% time, which led to products like Gmail. He also mentioned Semco’s voluntary innovation groups, where people came together without rigid hierarchy or titles to build new ideas.

The common thread is that these companies didn’t create innovation by attaching tighter pay mechanics to individual outputs.

They created it by giving smart people time, space, and trust. That doesn’t mean structure disappears. It means leaders stop assuming that every important contribution can be forecasted, measured, and rewarded in advance. Some of the most valuable work in a company begins as exploration — not as a KPI.

“We don’t hire intelligent people to tell them what to do. We hire intelligent people so they can tell us what to do.”

That’s a powerful design principle for people teams. If you want more innovation, ask where employees actually have room to think, experiment, and contribute beyond the narrowest version of their job.

6. AI will automate more work — which makes human trust and judgment even more important

AI will replace parts of jobs — especially repetitive, back-office work. That’s already happening.

But AI isn’t the differentiator. Everyone has access to the same tools.

What actually sets companies apart:
Better ideas
Better judgment
Better use of AI

“The boats that are really going to excel are the ones that still embrace the human-driven innovation.”

So the real shift isn’t just automation.

It’s redesigning work around what humans do best.