Wednesday morning, October 1st. Watching Q4 planning meetings where everyone optimizes their existing systems while nobody questions whether those systems should exist at all, and realizing that our obsession with optimization might be the thing preventing actual progress.

The Efficiency Trap

Optimization is the highest status activity in modern work culture. We optimize processes, automate workflows, streamline communications, refine our systems. Every improvement is celebrated. Every efficiency gain is a win. And yet, most organizations are more efficient than ever at producing outcomes that don't matter.

The fundamental problem with optimization is that it assumes you've already identified the right thing to do. It's a second-order activity that depends entirely on first-order correctness. Optimizing the wrong strategy doesn't produce better results—it produces worse ones, faster and more efficiently.

When you optimize a bad system, you don't get a good system. You get a highly efficient way of doing something that shouldn't be done at all.

The Local Maximum Problem

Optimization is hill-climbing. You look at your current position, identify which direction is upward, and move incrementally in that direction. This works perfectly for finding the peak of whatever hill you're currently on.

The problem is that you might be on the wrong hill entirely.

Organizations spend enormous resources optimizing their existing products, processes, and strategies. Every quarter brings new efficiency initiatives, new automation projects, new ways to do what you're already doing but faster and cheaper. And all of this optimization locks you more firmly into your current local maximum, making it harder to see—much less move toward—the global maximum that might exist on a completely different hill.

The company that optimizes its DVD-by-mail service can become extraordinarily efficient at shipping discs. But streaming isn't an optimized version of DVD shipping—it's a different hill entirely. All that optimization expertise becomes irrelevant, and the ability to recognize when you need to abandon your current hill becomes the only thing that matters.

Most strategic failures aren't about executing poorly. They're about optimizing the execution of the wrong strategy.

The Measurement Trap

Optimization requires metrics. You can't improve what you can't measure. This sounds like wisdom, but it's actually a constraint that shapes what you can optimize in dangerous ways.

The things that are easy to measure—cycle time, defect rates, response time, costs—become the focus of optimization. The things that are hard to measure—strategic positioning, customer delight, creative breakthrough, cultural health—get ignored. Not because they're less important, but because optimization demands clear metrics.

Over time, organizations become extraordinarily good at optimizing the measurable while the unmeasurable aspects that actually determine success slowly degrade. You hit all your optimization targets while your strategic position erodes, your culture deteriorates, and your customers lose interest.

The question "what should we be doing?" is always more important than "how efficiently can we do this?" But only one of those questions can be answered with dashboards and metrics, so we optimize instead of strategize.

The Opportunity Cost

Every hour spent optimizing existing systems is an hour not spent questioning whether those systems should exist. Every resource allocated to making the current approach more efficient is a resource not available for exploring fundamentally different approaches.

This creates a subtle but powerful form of strategic lock-in. The more you invest in optimization, the more you have at stake in your current approach. Abandoning an optimized system feels expensive—all that work, all those refinements, all that institutional knowledge about how to make it work well.

Sunk costs shouldn't matter logically, but psychologically they matter enormously. Organizations that have spent years optimizing their approach are much less likely to abandon it even when evidence suggests they should. The optimization itself becomes the trap.

Meanwhile, competitors who haven't yet optimized anything have nothing to defend. They can move faster, experiment more freely, and pursue completely different strategies without feeling like they're wasting previous investments.

The Innovation Paradox

Optimization and innovation are fundamentally incompatible activities. Optimization assumes you know what you're trying to achieve and need to get better at achieving it. Innovation assumes you don't yet know what you should be trying to achieve and need to discover it.

The skills, processes, and mindsets that make you good at optimization make you terrible at innovation. Optimization rewards consistency, standardization, incremental improvement. Innovation requires variation, experimentation, tolerance for failure.

Organizations typically try to do both—optimize existing products while innovating new ones. But what happens in practice is that optimization drives out innovation. The resources, attention, and status flow toward optimization because it produces measurable, predictable results. Innovation, which requires tolerance for ambiguity and frequent failure, gets starved of resources and relegated to "innovation theater."

The companies that successfully innovate usually do it by protecting innovation from the optimization culture, creating separate spaces where different rules apply. But this requires recognizing that optimization is not always good, that efficiency can be a trap, and that sometimes the best thing to optimize is your ability to recognize when to stop optimizing.

The Strategy Tax

Here's the uncomfortable truth: most optimization isn't strategic—it's defensive. Organizations optimize because it's easier than questioning their fundamental approach, because optimization projects have clear success criteria and manageable timelines, because optimization doesn't require the uncomfortable conversations about whether we're on the right hill in the first place.

Optimization becomes a substitute for strategy. Instead of making hard choices about what to do differently, we make easier choices about how to do current things better. Instead of confronting the possibility that our core approach is wrong, we incrementally refine it and call that progress.

This is what makes optimization so insidious. It feels productive. It generates measurable results. It keeps everyone busy and feeling successful. And it's completely compatible with strategic failure, with slowly becoming more efficient at activities that matter less and less.

The question is never "can we optimize this?" The answer is almost always yes—you can optimize anything. The question is "what happens if we optimize this?" And very often, the answer is "we become more committed to an approach that should be abandoned."

The Effectiveness Alternative

The alternative to optimization isn't chaos or laziness. It's effectiveness—the practice of ensuring you're solving the right problem before you worry about solving it efficiently.

Effectiveness asks different questions than optimization:

  • Are we working on the right things?
  • What would change if we abandoned this entirely?
  • What would we do if we were starting from scratch today?
  • Which constraints are we accepting that we could actually change?
  • What are we optimizing toward, and is that still the right target?

These questions are uncomfortable because they might reveal that much of your current activity is waste. But they're necessary because efficiency multiplies the impact of your direction—and if your direction is wrong, efficiency makes things worse, not better.

The most valuable skill isn't getting better at what you're already doing. It's the ability to recognize when to stop doing it entirely and start doing something else.

The October 1st Question

Today, Q4 starts for many organizations. Planning meetings focus on how to optimize the final quarter, how to hit year-end targets, how to do what you've been doing but better.

But the more important question is: what are you optimizing toward, and why?

Before you refine your process, ask if it's the right process. Before you automate your workflow, ask if you're working on the right things. Before you make your team more efficient, ask if they're solving problems that actually matter.

The most strategic thing you can do this quarter isn't to optimize what you're already doing. It's to question whether you should be doing it at all.

Effectiveness first. Optimization second. Or not at all.

The optimization delusion isn't that efficiency is bad—it's that we treat optimization as if it's strategy-neutral, as if making something faster and cheaper is always good regardless of whether it should exist. Real strategic thinking requires the courage to abandon optimized systems when they're solving the wrong problems. The best organizations aren't the most efficient at what they do. They're the ones that most quickly recognize when to stop doing it and start doing something else instead. In a changing world, the ability to abandon optimization might be more valuable than the ability to perform it.