Every organization has that one problem. The recurring issue that consumes endless meetings, spawns task forces, and generates reports that gather dust. You've thrown resources at it. You've assigned your best people. Yet somehow, six months later, you're having the same conversation.

The frustrating truth is that most problem-solving efforts fail not because solutions are wrong, but because they require perpetual energy to maintain. You're essentially pushing a boulder uphill and calling it solved—as long as you never stop pushing. The moment attention shifts, the boulder rolls back down.

There's a different approach. Instead of designing solutions that fight against system dynamics, you can restructure the problem itself so that desired outcomes emerge naturally. The goal isn't to manage problems better—it's to engineer conditions where problems dissolve through normal operation. This shift from ongoing intervention to structural elimination represents the highest form of problem-solving craft.

Traditional problem-solving asks: How do we fix this? Structural problem-solving asks: Why does this keep happening, and how do we change the forces that create it? The difference seems subtle but leads to radically different interventions.

Consider the classic problem of employees not washing dishes in the office kitchen. The conventional approach cycles through solutions: reminder signs, cleaning schedules, passive-aggressive emails. Each works briefly before compliance erodes. The structural approach asks what dynamics create dirty dishes. People are busy. Washing takes time. Dirty dishes don't affect the person who left them. The system's incentives and feedback loops actively produce the unwanted behavior.

Self-solving dynamics emerge when you realign these forces. A company might eliminate shared dishes entirely—everyone brings their own. Suddenly, dirty dishes affect only their owner. No monitoring required. No willpower needed. The problem structure itself now produces cleanliness. This principle scales to complex organizational challenges: instead of adding oversight to ensure compliance, redesign workflows so the compliant path is also the easiest path.

The key insight is that every persistent problem is a stable equilibrium. Something in the current system maintains that equilibrium. Your job isn't to fight the equilibrium through heroic effort—it's to identify the maintaining forces and redirect them. When you succeed, the new desired state becomes the natural resting point, maintained automatically by the same dynamics that previously maintained the problem.

Takeaway

Persistent problems are stable because something maintains them. Instead of fighting that stability, identify the forces creating equilibrium and redirect them so the desired state becomes the new natural resting point.

Not all problems are created equal. Some genuinely require ongoing attention—they're inherent to your operation and can only be managed, not eliminated. Others seem permanent but are actually artifacts of poor design that can be structurally removed. Confusing these categories leads to either wasted effort on fundamentally unsolvable issues or permanent accommodation of fixable ones.

Management problems have root causes that are external or genuinely unchangeable. A restaurant will always need to manage food freshness—ingredients inevitably age. A customer service team will always manage difficult conversations—human emotions are inherent to the work. These problems deserve good processes, training, and resources. But expecting them to disappear is unrealistic.

Elimination candidates are problems that exist because of internal design choices, often made unconsciously or inherited from the past. The key diagnostic question is: Does this problem exist because of how we've structured things, or because of forces genuinely outside our control? A team experiencing constant priority conflicts might be suffering from a management problem (too much work, too few people) or an elimination candidate (unclear decision rights that force everything to become a negotiation).

The elimination test is straightforward: if you can imagine a reasonable alternative structure where this problem wouldn't exist, it's likely an elimination candidate. Many organizations spend years managing problems that a single structural change could dissolve. The courage required isn't in the execution—it's in questioning arrangements that everyone has long accepted as given.

Takeaway

Before investing in better management of a recurring problem, ask whether it exists because of forces outside your control or because of structural choices you could change. Many 'permanent' problems are actually elimination candidates hiding in plain sight.

A forcing function is a constraint that makes undesired behavior difficult or impossible while making desired behavior the natural default. Good forcing functions don't require willpower, monitoring, or reminders—they work by reshaping the choice architecture itself.

The classic example is automobile engineering. Early cars required constant driver attention to avoid damage—you had to manually adjust the choke, carefully warm the engine, and remember specific shutdown procedures. Modern cars have forcing functions everywhere: automatic transmissions that won't shift to drive unless you press the brake, fuel systems that can't overfill, engines that simply turn off with a button. The desired behavior (safe operation) is now the path of least resistance.

Designing effective forcing functions requires understanding the current path of least resistance and why people follow it. A hospital wanted nurses to verify patient identity before medication administration. Training and protocols achieved inconsistent results. The forcing function solution: medication scanners that won't release drugs until both the patient's wristband and the medication barcode are scanned. Verification became easier than non-verification because it was integrated into the required dispensing action.

The art lies in finding leverage points where small structural changes create large behavioral shifts. Effective forcing functions feel invisible when working correctly—they don't create friction, they redirect flow. The goal is making the right thing the easy thing, not making the wrong thing punishable. When you find yourself designing monitoring systems or incentive schemes, pause and ask whether a well-placed forcing function could make the entire apparatus unnecessary.

Takeaway

The most elegant solutions don't motivate or monitor—they restructure choices so the desired behavior becomes the path of least resistance. Design for automatic compliance, not enforced compliance.

The highest compliment to a problem-solver isn't that they managed a difficult situation well. It's that after their intervention, the situation required no further management at all. The problem simply stopped being a problem.

This requires a shift in how we measure success. Quick fixes that require ongoing attention might feel productive but often represent deferred costs. True solutions disappear into the background—they're invisible precisely because they work.

Start examining your persistent challenges through this lens. Which are genuinely intractable and which are structurally manufactured? Where could a forcing function replace a monitoring system? What equilibrium are you fighting that you could redirect instead? The answers may reveal that your hardest problems are actually your most solvable ones.