🤔 Dear Lewis, how do I transition from intuition-based leadership to data-driven decisions?

A Fortune 500 director discovers her decade of "successful" leadership was built on intellectual quicksand when her analytics-savvy boss starts asking questions she can't answer.

Hey, it's Lewis. Most leadership and career advice feels like it was written by someone who's never actually managed people or navigated a layoff. This newsletter is built from the scar tissue of real moments.

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Here we are again, my friends, back for another installment where I share the real (but anonymized) stories from my coaching practice. Today's tale is about intellectual humility, imposter syndrome, and how learning a new language can transform your leadership – even when it feels like mental boot camp.

"My new boss is impossible," Sarah told me during our first call. She's a director at a Fortune 500 company, ten years into what she thought was a stellar career. "He keeps asking these pointed questions about metrics I've never tracked. It's like he expects me to be some kind of data scientist."

I could hear the frustration in her voice. Her previous boss had been satisfied with high-level updates and gut-feel decisions. Now she had a new VP with what she called a "vaunted analytics pedigree" who wanted specifics.

"He's asking about retention cohorts, customer lifetime value calculations, funnel conversion rates by segment," she continued. "My old boss never cared about this stuff. This guy is a micromanager who doesn't respect work-life balance."

I paused. "What exactly is he asking for?"

"Yesterday he wanted to know our 30-day retention rate for Q3, broken down by acquisition channel. Then he asked why our DAU/MAU ratio dropped in September and whether we'd tested the impact on long-term engagement. I had to scramble for three hours just to understand what he was talking about."

That's when I knew we had a classic case of what I call the Expectation Reality Gap.

"Sarah," I said, "what if I told you that your boss's expectations aren't too high? What if the problem is that your previous boss's expectations were too low?"

Silence.

"Think about it," I continued. "You've spent ten years in low-rigor environments. Your muscle memory is built for decisions based on hunches and high-level trends. But your new boss is operating at a different intellectual altitude."

I could practically hear her defenses going up. This is the moment when most people double down on their complaints. But Sarah surprised me.

"That's... actually terrifying to consider," she said quietly.

Here's what we discovered over the next few sessions: Sarah wasn't just dealing with a demanding boss. She was experiencing intellectual whiplash. Her entire decision-making framework – the one that had earned her promotions and praise for a decade – was suddenly being questioned.

The impostor syndrome was crushing. If metrics were this important, had all her previous decisions been inadequate? Was she actually terrible at her job and just didn't know it?

But here's the beautiful thing about learning a new language: it doesn't invalidate what you already know. It amplifies it.

I introduced Sarah to what I call the RIGOR framework – a systematic approach to building metrics fluency that transforms intellectual overwhelm into competitive advantage.

R: Recognize the Language Shift

First, we had to acknowledge what was really happening. Sarah wasn't dealing with an unreasonable boss. She was encountering a different dialect of business leadership.

"It's like you've been having business conversations in English," I told her, "and suddenly someone starts speaking to you in Mandarin. Both are legitimate languages. One just happens to be more precise for certain conversations."

We started with definitions. Real definitions. Not the hand-wavy explanations she'd been using for years.

"What's your customer acquisition cost?" I asked.

"Well, it depends on the channel and—"

"Stop. Give me the formula."

Silence.

"CAC equals total acquisition spend divided by new customers acquired in that period. Simple. Now, what's the difference between CAC and blended CAC?"

Between sessions, I made Sarah memorize the Metrics Playbook from the new Decode and Conquer 5th edition. This wasn't about making her feel stupid. It was about building vocabulary. Every language has its grammar rules, and product metrics is no different.

I: Identify the Hidden Signals

Once Sarah started learning the actual definitions, something fascinating happened. She began questioning her own past decisions.

"I've been celebrating our 'improved engagement,'" she told me after week three. "But I just realized I was looking at page views per session. That's like celebrating that people are getting more lost in our product."

This is the moment most leaders panic. If their previous success metrics were wrong, what did that say about their competence?

I pushed her further: "When might seemingly poor metrics actually be okay?"

She stared at me blankly.

"Think harder. When might lower engagement be a good sign?"

After some mental wrestling: "If... if users are finding what they need faster?"

Exactly. Now we were cooking.

"And when might seemingly good metrics be dangerous?"

"If... if people are engaging more but not converting?" She was getting it. "Or if they're engaging because the product is confusing?"

I had her work through the Hidden Signals chapter from Decode and Conquer. This taught her to look beyond surface-level metrics and identify the counterintuitive indicators that reveal true business health.

G: Generate Counterintuitive Insights

The real breakthrough came when Sarah stopped seeing metrics as right or wrong and started seeing them as tools with specific use cases.

"It's like learning that a hammer is great for nails but terrible for screws," she said during our fourth session. "I've been using page views as my hammer for everything."

We dove into the counterintuitive patterns:

• When dropping retention actually signals product improvement

• Why lower engagement can indicate better user experience

• How increased support tickets might reveal successful feature adoption

• Why segment-specific metrics often contradict aggregate numbers in meaningful ways

The mental exhaustion was real. "My brain hurts," she admitted. "But I can see how this makes me a better steward of the business. I'm not just tracking numbers anymore – I'm reading the story they're really telling."

O: Operationalize the Knowledge

Here's where most metrics education fails. People learn definitions but never connect them to decisions.

I made Sarah practice: "Your 30-day retention dropped 5%. Walk me through your analysis process."

"First, I'd segment by acquisition channel and cohort. Then I'd look at specific actions taken by retained versus churned users. I'd check if any product changes coincided with the drop. Finally, I'd examine whether this fits historical seasonal patterns."

Six weeks earlier, her answer would have been: "I'd ask the team to look into it."

R: Refine Your Instincts

The final piece was reconnecting her refined analytical skills with her existing business intuition.