The Aha! Moment

Where Should the Capacity Go?
In the first article in this series, I suggested that business owners stop asking only how many jobs AI might replace and start asking a different question: What capacity will AI create? That question matters because AI can reduce the time required for routine work dramatically. A task that once

AI Creates Capacity
When most people talk about artificial intelligence, the conversation usually starts with fear. Those are understandable questions. But I think they’re the wrong place to start. Instead of asking, “What jobs will AI replace?” I think business owners should be asking a different question: “What capacity will AI create?” That

Your Employees Aren’t Slow. They May Just Not Have Your System.
Most people know I’m not the biggest morning person. If I have to be somewhere—especially early—I want to get out of bed at the very last possible moment and still arrive on time. And I’m definitely not one of those people who rolls out of bed instantly awake and ready

Stop Copying Compensation Plans. Start Designing Them.
In the first article in this series, we looked at where today’s compensation systems came from. They weren’t created because someone discovered the perfect way to pay employees. They were designed to solve specific business problems. In the second article, we looked at compensation systems as measurement systems. Hourly pay

What Are You Really Measuring?
Last week, we looked at how today’s compensation systems evolved. Hourly pay wasn’t invented because it was the perfect way to compensate employees. It was created because factories needed people in the building at specific times. That raises an important question. If different compensation systems were designed to solve different

Why Are We Still Paying People Like It’s 1926?
If you ask ten business owners how employees should be paid, you’ll usually hear one of two answers. “They should be hourly.” “They should be salary.” It’s often presented as though one of those options is the “right” way to pay people. But here’s the problem: Neither one was designed