Learning Speed as a Career Advantage
Three ways to learn faster when the world keeps changing around you.
I was in a London hotel room after my first week at Zero100 when I turned on BBC and realized how narrow my news consumption had become. Almost everything I followed was centered on the United States.
I grew up working class in the Pacific Northwest. My worldview was shaped by what I could see directly in front of me: the warehouse floor, the factory line, the distribution center. Sitting in that hotel room, I understood something uncomfortable. The world I advise global executives about is far larger than my information diet suggested. My perspective needed to expand faster than it currently was.
That realization connected to something that has carried me across four industries and fifteen years of operations leadership. Learning speed determines career trajectory.
But here is the deeper truth. Learning fast and learning deep are not the same thing. You need both. Learning fast helps you navigate change. Learning deep builds expertise that lasts.
This distinction shapes how I approach every new domain, every career pivot, and every client engagement. Here is the system I rely on.
1. Build a Deliberately Diverse Information Diet
Most professionals optimize for speed over diversity. They follow the same sources, consume the same narratives, and develop the same blind spots. Then they are surprised when market shifts catch them off guard.
The executives I advise face this at organizational scale. The professionals I mentor face it individually. The pattern is identical. Similar inputs create predictable thinking.
After that night in London, I rebuilt my information architecture around a simple idea. Choose sources that disagree with each other and cover different parts of the world.
Here is what I follow now:
For markets and demographics: The Prof G Pod with Scott Galloway and Ed Elson. Broad, data driven, willing to challenge assumptions.
For international perspective: BBC News. When I travel, I watch local news to understand what matters to people in that region, not just to the U.S. market.
For technology and capital formation: The All In Podcast. Four investors with different worldviews debating the same topics. The disagreement is the point.
For depth: I rotate between The Economist, Wall Street Journal, and New York Times. Each one provides a different lens on global context, business mechanics, and cultural dynamics.
What I removed: Anything optimized for engagement over insight. That eliminated most social media and the majority of newsletters that simply repackage other people’s thinking.
Better inputs sharpen judgment. Global inputs extend your horizon.
But consumption alone does not create learning. You need a mechanism to synthesize.
To build this capability:
Select three sources from different worldviews
Choose two publications you will read consistently
Add one international or regional source
Schedule time to consume them
Remove sources that make you feel informed without changing how you think
2. Create a Weekly Learning Loop
The fastest learners are not the ones who consume the most content. They are the ones who synthesize consistently.
I use the same learning loop across every industry shift and role transition. It works because it forces application, not just accumulation.
Sense: Scan widely for early signals. I capture anything surprising, contradictory, or repeating across sources.
Filter: Decide what might matter. My test is simple. Does this affect my industry. Does it surprise me. Does it repeat across unrelated sources.
Connect: Link patterns across technology, behavior, and incentives. This is where insight emerges.
Rerank: At week’s end, review what repeated and what shifted your understanding.
Act: Apply one insight the following week. This step matters most. Learning without application is just expensive entertainment.
Here is what this looked like last month.
I captured twelve insights on AI implementation across enterprises. Two survived the filter. First, companies struggle more with change management than with technology. Second, successful implementations start with narrow use cases, not large transformation programs.
That pattern showed up in manufacturing, logistics, and financial services. Different industries, identical constraint.
I applied it immediately. A client asked about scaling their AI investment across planning functions. Instead of recommending a broad roadmap, I suggested they start with one planning process, prove value, and expand. That recommendation came directly from synthesizing multiple weak signals into one strong pattern.
Synthesis compounds into judgment. Judgment compounds into decisions others trust.
To build this capability:
Capture ten insights weekly
Highlight the two that pass your filter
Link them to your work in one sentence
Apply one insight within seven days
Track what worked and what did not
Time investment: about ninety minutes weekly.
3. Learn by Immersion When It Matters
Fast learning helps you navigate breadth. Deep learning builds authority.
When I need to understand a domain that is unfamiliar, I use a principle from manufacturing. Go to the Gemba. In Japanese, ‘Gemba’ means the actual place. It is the idea that you cannot understand a system from conference rooms or slide decks. You have to go where the work happens.
As my boss loved to say, you cannot solve factory problems from a board room.
At UPS, I started in the warehouse. At Starbucks, I ran distribution operations and worked directly with store teams. At Microsoft Azure and Amazon AWS, I visited supplier facilities and manufacturing lines to understand infrastructure decisions. At Amazon’s Project Kuiper, I sat with RF engineers and studied how they designed component level tradeoffs and produced Computer Added Designs (CAD).
When I moved into renewable energy, I spent time on solar farms with field operators. Not to become an electrician, but to understand where theory meets reality.
Immersion collapses the gap between concept and constraint. It exposes how a system actually works. It builds credibility with practitioners who know immediately whether you are operating from theory or experience.
This applies far beyond operations. When I advise executives on AI strategy, I spend time with the teams implementing it. I look at their workflows, their data pipelines, and their change management constraints. That ground truth shapes everything I recommend.
My process:
Build a first principles mental model
Immerse deliberately by visiting the work
Update the model in real time
Reinforce with structured learning afterward
Recent example. In my first weeks at Zero100, I needed to understand how Chief Supply Chain Officers make technology investment decisions. Instead of reading analyst reports, I spoke directly with executive leaders across industries about their evaluation criteria, budget constraints, and organizational dynamics.
Those conversations revealed something reports often miss. Technology decisions are rarely about technology. They are about readiness, risk tolerance, and expectations from the Board. That insight now shapes my research.
To build this capability:
Identify one domain to understand deeply in the next ninety days
Go where the work happens
Prepare five basic questions
Document assumptions before and after immersion
Return to more formal learning with your new context
Immersion does not scale, so reserve it for domains where credibility truly matters.
Why This Matters Now
I have worked across industries that could not be more different. Retail, cloud infrastructure, satellite manufacturing, renewable energy, and enterprise research. The companies, technologies, and business models all changed.
The skill that made every transition possible stayed the same: I learned faster than the role required.
Learning speed is not about knowing everything. It is about choosing better inputs, synthesizing faster, and applying insights sooner than others.
Careers compound when you do two things well. Learn fast enough to navigate change and learn deep enough to build expertise that outlasts it.
Learning fast made my transitions possible. Learning deep made them meaningful.
If you are navigating a career transition, evaluating a new industry, or building credibility in an unfamiliar domain, focus less on consuming more information and more on learning better.
Rooting for you,
Justin
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The Gemba principle really resonates. I've found that understanding how systems actualy work beats theoretical knowledge every time. That line about solving factory problems from a board room captures something most consultants miss. You can tell when someone has spent time on the floor versus someone who just read the white papers. Curious if you've found certain industries more resistant to that hands-on learing approach than others?