Why "Better Leadership" Isn't Always Enough
One Takeaway: Every growing company hits cross-functional coordination problems. The standard default advice is to fix this through better leadership. Get the right people in the room, align on priorities, and communicate the vision. But this treats every coordination failure the same way. What leaders need is a diagnosis of why coordination is failing in their organization. The Design, Connect, Protect framework we’ve used throughout the series of articles offers that. This framework, based in economic logic, leads to different solutions depending on the actual problem.
Cross-functional alignment isn’t a new idea. Matrix organizations, cross-functional teams, dotted-line reporting, alignment meetings, shared OKRs. Organization and management experts have been working on these problems for decades. Every management book tells you to break down silos. Every leadership seminar teaches you to align teams around shared goals.
And yet problems tend to persist. Not because leaders are bad at alignment. Because bad alignment is a symptom for many types coordination failures. Bad alignment is a symptom, it is not a sufficient diagnosis.
The Same Problem, Three Different Causes
A mid-market SaaS company noticed that their enterprise product launches kept failing. Product, sales, and customer success were supposed to work together on every launch. They had cross-functional meetings. They had shared timelines. They had executive sponsorship. Leadership kept saying “we need better alignment.” They tried everything the leadership playbook recommends.
Nothing worked. Launches kept missing the mark. Leadership concluded they had a culture problem.
They didn’t. They had three different problems that looked identical from the outside but required completely different solutions.
Problem one was a design problem. Product was measured on time to get new features out. Sales was measured on deals closed. Customer success was measured on ticket resolution time. Each team was individually incentivized to optimize for their own metrics. When a launch required product to slow down feature work, sales to delay pipeline activity, and customer success to invest in pre-launch preparation, each team faced a reasonable reason not to cooperate. The shared timeline existed on paper. The incentives each team was evaluated on pointed in three different directions.
Better leadership wouldn’t fix this. Better meetings wouldn’t fix this. The system was designed so that cooperation was a sacrifice. The fix was redesigning the economics. It was creating shared launch metrics that all three teams were evaluated on jointly. This made cooperation the rational choice rather than the self-sacrificing one.
Problem two was a connection problem. Customer success had detailed knowledge from support conversations about which features customers actually used and which they ignored. This knowledge would have been invaluable for product prioritization and sales positioning. But it lived in support tickets and team conversations. It never reached product planning or sales in a usable form. Product built features based on their roadmap. Sales pitched based on their assumptions. Customer success watched customers struggle with launches that didn’t reflect how they actually used the product.
Better leadership wouldn’t fix this either. The knowledge existed. It just didn’t flow. The fix was transfering that knowledge. Ensuring that customer success insights reached product planning before the roadmap was set and reached sales enablement before the pitch was built. Not through another reporting template that would strip out context. Through someone who understood all three functions well enough to translate between them.
Problem three was a protection problem. The company had a small team exploring a new approach to customer onboarding. The work was promising but early. It didn’t fit the standard launch process. It couldn’t show revenue impact yet. Every quarter, the team had to justify their existence. They had to compete in reviews against existing departments showing clear metrics. After two quarters of “no measurable results,” leadership cut the cord. They reassigned their resources to proven optimization work.
Better leadership wouldn’t fix this. The measurement system was doing exactly what it was designed to do. It allocated resources toward measurable returns. The fix was protecting the new innovative work. They needed different evaluation criteria for experimental initiatives. They needed someone to translate what the team had learned into language leadership could evaluate. They needed time and space for the work to mature before being judged by metrics designed for a different type of activity.
From the outside, all three problems looked like “silos” and “lack of alignment.” The standard leadership response—more meetings, more communication, more vision speeches—addressed none of the actual causes. Each problem had a different economic factor underneath it and required a different fix.
Why Economic Thinking Changes the Diagnosis
This is the counterintuitive conclusion that runs through this entire series. Economics makes you a better leader because it gives you specific, diagnosable explanations for problems that leadership intuition often treats as generic.
Consider what each economic insight actually provides.
Transaction cost economics (Coase, Williamson) explains that cooperation has real costs. Things like information costs, negotiation costs, enforcement costs. These costs often increase as organizations grow. When a leader sees departments failing to collaborate, the intuitive response is “we need to communicate better.” The economist instead asks: what are the actual friction costs preventing this collaboration? Can we redesign the system to reduce them? The leadership response leads to more meetings. The second leads to structural changes like shared budgets, joint metrics, different authority structures. Solutions that make collaboration rational rather than relying on goodwill.
The knowledge problem (Hayek) explains that the information needed for good decisions is spread throughout the organization. Often it’s found in forms that resist centralization. When a leader sees bad decisions being made, the intuitive response is “we need better data” or “we need more reporting.” The economist instead might ask: is the relevant knowledge even able to be quantified? Is the reporting process itself destroying the context that makes it valuable? The leadership response leads to more dashboards. The second leads to ensuring decisions get made where the knowledge lives or investing in people who can translate between local knowledge and central decision-making without flattening it.
Measurement economics (Goodhart, Muller, McCloskey) explains that measurement systems create systematic bias toward the quantifiable over the valuable. When a leader sees innovation dying, the intuitive response is “we need to prioritize innovation” or “we need an innovation budget.” The economist might ask: is the measurement system making innovation invisible and punishing the people who pursue it? The leadership response leads to a speech. The second leads to fundamentally different evaluation frameworks for different types of work. It leads to portfolio evaluation for exploration, different time horizons for different functions, or space for work that can’t justify itself on a quarterly dashboard.
In each case, the economic thinking doesn’t replace leadership judgment. It sharpens it. It takes a vague sense that “something isn’t working” and gives you a specific mechanism to investigate and a specific intervention to try.
The Diagnosis Determines the Intervention
This is what separates the design, connect, protect framework from generic leadership advice. Each diagnosis leads to a different action.
If you diagnose a design problem and try to solve it with better knowledge flow, nothing changes. The incentives are still misaligned. People now have better information about an opportunity they’re still punished for pursuing.
If you diagnose a connection problem and try to solve it with new metrics, nothing changes. The knowledge still doesn’t reach the right people. You’ve redesigned the incentives around outcomes that teams don’t have the information to achieve.
If you diagnose a protection problem and try to solve it with better knowledge transfer, nothing changes. The measurement system still kills the work. Everyone now understands the opportunity and still watches it die on the dashboard.
The interventions aren’t interchangeable because the underlying economics forces are different. Misaligned incentives, knowledge that doesn’t flow, and measurement bias are three distinct problems that share the same symptom: coordination failure. Treating them all as “alignment issues” is like treating every fever with the same medicine.
Sometimes a fever means you have the flu. Other times a fever means you have heat stroke. You don’t treat them the same way.
Why the Wrong Fix Makes Things Worse
This isn’t just about wasted effort. Applying the wrong intervention to a coordination problem can actively make things worse.
I learned this firsthand at Lyft. Our vehicle service centers offered maintenance and repair for drivers’ vehicles. Most maintenance and repair operations run on a traditional model: one technician per car, start to finish. Leadership wanted to improve throughput and hit profitability targets, so they tried to redesign this. They decided to shift to an assembly line model. In this case multiple technicians worked on vehicles simultaneously, each handling their specialty.
The workflow change made operational sense. But it broke the compensation system. Under the old model (that every competing repair garage used), individual technicians were evaluated on their own output. They were compensated for cars completed, quality of work, and speed. Performance bonuses were straightforward. Under the assembly line model, no single technician owned a vehicle’s outcome. Individual performance metrics stopped making sense. So compensation shifted to team-based bonuses.
Now leadership had a new problem. Some technicians felt they were carrying others. High performers who had thrived under individual incentives felt punished by team-based compensation. Their contribution (and compensation) was averaged with less productive teammates. The workflow improvement that was supposed to increase throughput actually decreased morale. It created retention risk among the best technicians. It made recruitment efforts difficult. All this together threatened both the quality and profitability the design intended to improve.
Fixing the workflow without simultaneously redesigning the incentive structure didn’t move us closer to the goal. It moved us sideways into a different set of problems. The two systems were interconnected in ways that meant optimizing one in isolation created new distortions in the other.
Sometimes Second Best is Totally Fine
This is a pattern economists have studied extensively. In a complex system with many less than ideal situations, removing one doesn’t automatically move you closer to the best outcome. Sometimes it moves you further away. This can happen because the remaining issues interact with the change in ways you didn’t anticipate.
If your main problem is misaligned incentives and you invest in better knowledge flow without fixing the incentives, you may make things worse. People now have better information about an opportunity they’re still punished for pursuing. The frustration increases. The coordination doesn’t.
If your main problem is measurement bias and you redesign incentives without addressing the measurement system, people are now incentivized to pursue work that the evaluation system will still destroy. They’ll try, fail to show results on the dashboard, and learn not to try again.
This is why diagnosis has to come before intervention. This is why the Design, Connect, Protect distinction matters practically, not just conceptually. The three failure modes interact. Getting one right while the other two remain broken can produce outcomes worse than leaving them all broken. You can end up creating new problems between the fixed and unfixed parts of the system.
It’s also why harmonizer thinking requires economic reasoning rather than leadership instinct. Instinct says “fix what you can see.” Economic reasoning says “understand the system well enough to know which limit is actually the problem. Then know what happens downstream when you change it.”
That difference in approach is often the difference between a leader who makes things better and a leader who makes things different but no less broken.
What This Means for How Leaders Develop
Most leadership development focuses on communication, vision, empathy, and decision-making under pressure. These matter. But they’re general capabilities applied to every situation the same way.
Economic thinking acks as an important diagnostic. A leader who understands transaction costs sees coordination failures differently than one who doesn’t. They ask different questions. They investigate different mechanisms. They design different solutions. Not because they’re smarter, but because they have a framework that distinguishes between problems that look identical on the surface.
This is what we mean by harmonizer thinking. It’s not a specific role to hire for. It’s a way of seeing organizational problems that most leaders haven’t been trained to see. Business education teaches optimization and motivation. They often don’t teach the economics of coordination, knowledge, and measurement. These are central to understanding and explaining why organizations can break down as they grow.
The leads us to a counterintuitive implication. The subject most likely to help you become a better organizational leader isn’t always leadership studies.
It’s often times economics.
Not the economics of GDP and interest rates. The economics of how people coordinate. Why that coordination breaks down. And what specific mechanisms cause specific failures.
Every growing company faces transaction cost problems, knowledge distribution problems, and measurement bias problems. Having names for these, and the ability to tell them apart, gives you an advantage that no amount of general leadership advice provides.
The Bottom Line
Cross-functional coordination isn’t new. Every organization has been trying to break down silos and align teams for decades. What’s been missing isn’t “alignment.” It’s better diagnosis of the causes of the breakdown.
The Design, Connect, Protect framework provides that diagnosis.
Design problems need structural solutions. New rules, new metrics, new incentive systems.
Connection problems need knowledge transfer. Ensuring the right information reaches the right decisions in forms that preserve context.
Protection problems need advocacy. Different evaluation frameworks for different types of work, with space for the unmeasurable.
These aren’t leadership platitudes.
They’re diagnostic categories grounded in specific economic realities. They’re built on transaction costs, knowledge distribution, and measurement bias. Each leads to a different intervention because each addresses a different cause of the same symptom.
Economics gives leaders something that leadership advice alone cannot. It gives leaders the ability to see why coordination is failing, not just that it’s failing. That alone can be the difference between a leader who keeps calling meetings and one who actually fixes the system.