I Spent a Decade Trying to Fix Problems Before I Realized I Was Looking at Them Wrong

I used to think I was pretty good at solving problems.

I'd identify an issue, break it down into manageable pieces, tackle each piece systematically, and move on to the next challenge. Linear. Logical. Efficient.

Then I watched an organization I helped to generate over 2,000 leads in 3 months not close a single one. They realized (too late) that they didn’t actually have a sales process in place for converting those leads. I watched helplessly as they spun their wheels, not knowing how to fix the problem. I wanted to help, but didn’t even know where to begin.

That's when I realized something uncomfortable: I didn't actually understand how problems work.

The Problem With How We Think About Problems

We still try to tackle modern problems with linear thinking approaches that isolate issues and reduce complexity. But more often than usual, they fall short of providing a viable solution.

I see it everywhere. A company experiences stagnant sales, so they hire more salespeople. The sales team grows, but revenue stays flat. Why? Because the real issue wasn't the number of salespeople—it was a pricing structure that created perverse incentives, which demotivated the existing team, which made onboarding new hires nearly impossible.

Everything connects to everything else.

In business, systems thinking helps managers gain perspective on organizational challenges and identify root causes of problems like low morale or stagnant sales. But most of us never learned to see these connections.

We learned to break things apart, not to see how they fit together.

The Two Loops That Run Your World

Here's what changed my thinking: understanding that every system operates through feedback loops.

There are two types, and once you see them, you can't unsee them.

Reinforcing loops amplify changes within a system, leading to exponential growth or decline. Think of them as the "more leads to more" mechanism. A successful product attracts more customers, which generates more revenue, which funds better marketing, which attracts even more customers.

Or the inverse: Poor customer service leads to negative reviews, which reduces new customer acquisition, which decreases revenue, which forces staff cuts, which makes customer service even worse.

Balancing loops counteract changes and promote stability. They work to bring the system back to a desired state or set point, acting as a self-correcting mechanism. Your body temperature, a thermostat, or a company's hiring process when they reach capacity—all balancing loops.

The real world runs on both types simultaneously.

And here's the part that kept me up at night when I first learned it: Feedback mechanisms have been described as a threshold concept for understanding complex systems—difficult to learn but transformative once mastered.

I felt like I'd been trying to understand movies by looking at individual frames.

Why Smart People Make Terrible Predictions

I used to get frustrated when my careful plans didn't work out.

I'd analyze the situation, create a detailed strategy, execute it precisely, and watch as reality produced completely unexpected results. I assumed I wasn't smart enough or didn't have enough information.

Turns out, that wasn't the problem.

The core challenge is understanding the complex and increasingly unpredictable outcomes when a series of positive and negative feedback loops operate in concert—how difficult it is for anyone, however sophisticated their models are, to predict the future.

The system is smarter than you are.

I watched this play out during the COVID-19 pandemic. Public health officials who understood systems thinking approached outbreak response differently than those who didn't. A systems science approach proved useful for broadening strategic thinking to consider critical factors driving the short and long-term consequences of crisis response measures, including how such decisions would impact health disparities.

The officials who thought linearly said: "Close everything to stop transmission."

The officials who thought systemically asked: "What happens to mental health, domestic violence, education gaps, economic stability, and healthcare access when we close everything? How do those factors then feed back into public health outcomes?"

Both groups wanted to save lives. Only one group understood they were working with a system.

The Questions That Change Everything

I've started asking different questions when I look at problems now.

Instead of "What's broken?" I ask "What patterns keep repeating?"

Instead of "How do I fix this?" I ask "What happens if I change this variable? What else changes as a result? What changes after that?"

Instead of "Who's responsible?" I ask "What incentives are creating this behavior?"

These questions feel slower at first. They are slower. But they're also more honest about what we're actually dealing with.

Recent research from Harvard Business Review emphasizes understanding interdependencies, redefining problems iteratively, and engaging diverse stakeholders to co-create solutions. This positions systems thinking as critical for modern business challenges.

You can't understand a system by looking at its parts in isolation.

Healthcare systems demonstrate this perfectly. They're characterized by interactions among diverse stakeholders—patients, providers, policymakers, and researchers—across various sectors like health, government, community, and education. These systems show properties like non-linearity, emergence, adaptation, and feedback loops.

Try to "fix healthcare" by only looking at insurance, and you'll miss how medical education, pharmaceutical pricing, hospital administration, and patient behavior all interconnect.

What I Do Differently Now

I map before I act.

When I encounter a problem, I spend time drawing out the relationships. What affects what? Where are the delays between cause and effect? Where might a small change create a big impact? Where might a big change accomplish nothing?

I look for the loops. Where is growth reinforcing itself? Where are natural limits showing up? What's trying to maintain equilibrium?

I ask people with different perspectives what they see. Someone in marketing sees different connections than someone in operations. Someone who joined last month sees different patterns than someone who's been here ten years.

I accept that I won't get it completely right.

Systems thinking doesn't give you certainty. It gives you humility and better questions.

Take the case of Alia Whitney-Johnson, who transformed a childhood hobby into an enterprise advocating for exploited youth in Sri Lanka. What started as a simple jewelry business became a case study in using systems thinking to launch and grow an impactful organization through understanding positive feedback loops in social enterprise.

She didn't just create jobs. She understood how employment affects family stability, which affects education access, which affects community development, which creates more opportunities for employment.

One intervention. Multiple reinforcing loops.

The Uncomfortable Truth

Most of the problems you're trying to solve are symptoms.

The actual problem is usually somewhere else in the system, often in a place you haven't looked because it seems unrelated to the symptom you're experiencing.

Understanding the behavior of difficult complex social system problems well enough to even begin to hypothesize a realistic solution, with a high probability of working the first time, is impossible without understanding the key feedback loops involved.

This explains why so many well-intentioned interventions fail. We treat symptoms while the system continues generating the same problems through its underlying structure.

I've learned to look for what's not obvious. The delays. The feedback loops operating on different timescales. The incentives that contradict the stated goals. The unintended consequences waiting three steps down the chain.

Systems thinking won't make you popular.

When everyone wants a quick fix, you're the person saying "It's more complicated than that." When everyone wants to blame someone, you're pointing at structures and incentives. When everyone wants certainty, you're offering probability and interdependence.

But it will make you more effective.

Research on systems thinking in science education has increased in recent years, mainly from the United States and Germany. The academic interest is growing because the approach works.

Where This Leaves You

You don't need to become a systems dynamics expert to think more systemically.

Start by noticing patterns instead of events. Look for what repeats rather than what happened once.

Ask "What else is connected to this?" more often than you ask "How do I fix this?"

Draw simple diagrams showing what affects what. Arrows and boxes. Nothing fancy.

Look for the delays between action and result. Most feedback loops take time to complete their cycle.

Question your first answer. It's usually addressing a symptom.

I still catch myself reverting to linear thinking. It's faster. It's easier. It feels more decisive.

But when I slow down and look at the system, I make better decisions. I see opportunities others miss. I avoid unintended consequences that would have blindsided me.

The world is complex. Our thinking should match that reality.

Not because complexity is beautiful or interesting, but because it's honest about what we're actually working with.

And honest thinking leads to better results than comfortable thinking ever will.