Beyond Band-Aids: How to Solve Problems Once Instead of Forever
- Russ Powell
- Jul 23
- 5 min read
Updated: Jul 28
A CTO once told me that a single senior engineer was saving his 150-employee startup hundreds of thousands of dollars—not with brilliant code, but by teaching his team to slow down. Instead of jumping to solutions, they started with better data collection and root cause analysis.
This engineer had learned what many business leaders struggle with: resisting the reflex to fix things immediately. You see a problem, you want to fix it. Of course. But if you fix the wrong thing, all that speed just slingshots you faster in the wrong direction.
You can't fix what you don't understand.
The Danger of Symptom-Fixing
Let's start with two scenes you might recognize.
A CEO notices that support tickets have doubled in a month. She hires two more customer support reps. Problem solved—until the tickets keep climbing. Later, they discover the real cause: a bug in the latest software release. Hiring staff only poured more water into a leaky bucket.
A factory foreman spots a puddle of oil and tells a worker to mop it up. Problem solved—until the leak returns. Digging deeper, they find a defective gasket, which turned out to be caused by a purchasing policy that prioritized the lowest cost over quality. A simple cleanup task revealed a systemic issue that's been quietly creating bigger costs and risks.
I see this all the time—teams lose time, money, and credibility treating symptoms (low sales, high turnover, oil on the floor) while the real root causes stay hidden: broken processes, unclear priorities, or cultures where people don't feel safe raising concerns.
Step One: Collect the Right Data
Before diving into analysis, gather the facts first. Too many teams skip this step or rely on hunches. Ask yourself: What do we really know?
Are we tracking when and why customers cancel?
Do we know how often projects get delayed?
Have we asked frontline staff what they see happening every day?
For more on collecting meaningful data, see Evidence Before Action: Why Smart Problem Solvers Begin With Data.
Step Two: Analyze for Root Causes
Once you have data, dig for the deeper drivers so you can solve it once, not repeatedly.
Here are two powerful tools that make it easier:
The Five Whys: Cut Through Layers of Symptoms
The five whys digs beneath symptoms by asking "why" repeatedly—about five times—until the root cause surfaces.
Here’s an example:
Support tickets are piling up. The quick fix? Hire another rep. But using the five whys, a team discovered:
Customers couldn't complete checkout because the page crashed
The page crashed because certain browsers weren't tested
They weren't tested because the QA checklist was outdated
No one updated the checklist after the product framework changed
Without the five whys, they would have hired more reps and watched tickets keep climbing. With it, they uncovered a broken QA process and fixed it.
Fishbone Diagram: Map Multiple Causes
Some problems aren't linear—they're tangled. Like a difficult knot. A fishbone diagram helps map possible causes under categories like People, Process, Tools, and Environment.
Here’s an example: A company's new features kept failing to launch on time. Leadership's first thought? Hire a project manager. But the fishbone revealed six interconnected factors:
People: (1) Engineers weren't clear on ownership, and (2) a key person was split across three projects
Process: (3) The release checklist was incomplete
Tools: (4) A slow staging server delayed testing
Environment: (5) No buffers for last-minute design changes, plus (6) key meetings during peak support hours meant engineers were distracted
Without this tool, they would have added headcount and still missed deadlines anyway. With it, they fixed the real blockers and shipped on time.
Learn more about fishbone diagrams here.
Look Deeper: The It-We-I Lenses
Even after using these tools, some causes stay hidden because they live in the system itself. When problems keep recurring, look through these three lenses:
Systems and Structures (the It): Are priorities shifting constantly or processes broken?
Relationships (the We): Is trust or alignment missing between or among teams?
Individuals (It I): Do people have the skills, knowledge, mental models, and clarity they need?
When Systems "Break" Good People
I once worked with a leadership team baffled by why their engineers kept leaving. Their first reaction? “We just can't find good people.”
But the real problem wasn't the engineers—it was the system:
Priorities changed weekly, with no clear roadmap
Engineers had stopped trusting leadership to provide stability
Talented people were feeling burned out from constant chaos
The fix wasn't "better hires." It was reducing chaos through weekly planning sessions, a shared roadmap, and transparent communication. Turnover dropped almost overnight.
The Mindset Shift
Root cause analysis doesn’t have to be overly complicated. In my experience, the best problem-solvers approach issues with these mindsets:
Slow down to go faster. Time spent understanding the problem pays for itself.
Engage your team. Those closest to the work often see causes leaders miss.
Look at the whole system. Data matters, but so do trust, skills, and supportive structure.
What’s Our Target?
Once you understand the real problem, ask: What does success look like if this is solved?
Then design solutions that address root causes, not just symptoms. The oil leak needs a new gasket and a purchasing policy that values quality. The checkout crashes need both updated QA processes and a culture where testing matters.
Next Steps
Root cause analysis is just one part of collaborative problem-solving. The next time you see a recurring issue, ask: Have we taken enough time to understand what's really driving this? Or are we just mopping up oil without finding the leak?
Start with better data, use these tools to dig deeper, and involve your team. You'll save time, money, and frustration—by solving the right problems the first time.
If you’d like a more comprehensive way to help your team or organization internalize these practices, come join us for our foundational workshop, Leadership and the Middle Path, or our full curriculum.
Contact Russ for details.
For More
Data-collection – Evidence Before Action: Why Smart Problem Solvers Begin With Data
The It-We-I model – Systems Thinking and the Juggling Girls of Berlin
The Pareto Principle – If Ya Gotta Eat a Frog, Why Sit Around and Look at It All Day?
Solve the Right Problems, Faster
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