In my prior articles, I stated the importance of developing a cross-functional understanding of businesses, and thinking not just tactically, but strategically. 

I mentioned how to do the latter requires you to see through all the downstream implications of a particular decision or lack of a decision.

I also promised to share an example of this from my own career. It just so happens to involve me and a colleague running from the “police.”

It all started back in 1999 during the midst of the dot com boom. I had just left McKinsey and after a failed startup attempt of my own, I worked for a company that I’ll refer to as LP.

LP provided software as a service to commerce companies looking to boost their sales. It allowed salespeople to chat with customers browsing an ecommerce website to assist them.

Today such a capability is more common, but back then it wasn’t possible until LP made the capability widely available to major online retailers in the U.S.

At the time, I was hired as “Assistant to the CEO.” Many people thought I was the CEO’s secretary. Today the more common job title would be “Chief of Staff.” In short, I was the CEO’s right-hand guy, and would basically do whatever he couldn’t get to himself.

At the time the company was growing sales by 600% per YEAR. It was absolute chaos day to day. We also had an Initial Public Offering (IPO) scheduled in about 6 months.

At the time of this story, it was November 15, 1999. Amazon had gone public recently.

Ecommerce had just gone mainstream. It was on the cover of every major business magazine every week, all year long. Dot com millionaires and billionaires were being created by the hour.

It was ecommerce fever. There were predictions that retail stores would become obsolete within 36 months. It was an incredibly crazy time.

Christmas 1999 was thought to be the industry’s first ever eChristmas. Online sales we expected to (and actually did) skyrocket.

At the time, LP had 50 Fortune 500 companies as clients — again, growing revenue at 600% per year.

One day, I was walking by the server racks in the office and looking over the shoulder of one of the engineers at the performance monitoring dashboard that measures the utilization of the servers’ resources.

One metric jumped out at me. It was the bar chart labeled “CPU Utilization” and it was bright red, showing 95%.

I had taught myself how to administer servers the year prior when I had to manage my own servers for my startup. So I knew that a 95% CPU utilization meant the main chip in the server was getting severely taxed at that moment and had no more capacity.

So I asked the software developer,

Question: How often is the CPU maxed out on this server?

Answer: All day long.

Question: What about all the other servers?

Answer: Same. All day long.

Question: Umm… Doesn’t that mean we can’t handle any increased usage load on the system?

Answer: Yes.

Question: So umm… What happens when we hit 100% utilization on all the servers?

Answer: the whole system basically crashes and stops working for everyone.

Implication level 1: Our servers are about maxed out.

Implication level 2: The biggest eChristmas selling season in the history of the industry begins in 11 days (in the United States, Christmas gift buying begins November 26th after the U.S. Thanksgiving holiday) and our system will not work.

Implication level 3: The biggest Ecommerce companies in the world use our system, and when it fails during the Christmas season (a period where in 1 month they generate 35% of their sales for the year), they will all become ex-clients.

Implication level 4: Our IPO scheduled to take place in 6 months will fail if our top clients all cancel their contracts because we severely reduced their sales for the year.

Implication level 5: Between a mass exodus of our top clients and a failed IPO, the company brand will be irreparably damaged for years.

After thinking through all the ripple effects, I took a single bar chart from the server monitoring system, extrapolated its logical ripple effect, and concluded we had an existential threat to the business on our hands.

I immediately made a case to my CEO, the COO, and the CFO of the company. They all flipped out when I showed them the data and walked them through all the implications.

They gave me a mandate:


In trying to find a creative way to get more servers to last us two weeks or so, I discovered we had an old data center we used to use that was no longer operational.

The data center was located adjacent to Chinatown in Manhattan. The data center housed several lower-end servers that were perfect for our temporary needs.

The only problem was there was a billing dispute between LP and the data center. Our systems administrator and I went down to the data center to get the servers, but when we went to leave, security would not let us leave.

They said until the billing dispute was settled, we couldn’t take our servers out of the building.

In that moment, I made a judgement call. I knew our IPO was on the line. I also figured that since LP owned those servers, it would not technically be stealing if we took the servers and ran.

So I told my colleague, “Grab one server under each arm and when I say go…

“RUN !!!”

And we did!

Security yells at us, “Hey, come back!!” They started to chase us.

My colleague was a 6’2″ caucasian guy with red hair. He’s running down Canal Street in the heart of New York City’s Chinatown with two computer servers, one under each arm. I’m running also with one server under my arm and for the life of us we can’t find a taxi.

We look ridiculous. He sticks out like a sore thumb because everyone else in Chinatown is, well, Chinese. I fit in ethnically, but we’re both carrying servers – the oversized ones that were the norm back then.

We’re both running as fast as we can — huffing and puffing — clearly out of shape and unaccustomed to the 100-meter “server carrying” dash.

I whip out my cell phone and call our CFO to come get us while we’re “on the run.”

Before he sends our head of sales, who actually owns a car (nobody owns a car in Manhattan) to come get us, we find a taxi.

We stumble into the taxi, throw our servers in and tell the taxi driver to go, go, go!

Within 12 hours, we had all the temporary servers up and running. We had doubled our system capacity overnight. And two weeks later, our high-end servers had arrived and our capacity had grown by 400%.

The system ran perfectly through the Christmas season.

A few months later, the company had a successful IPO and is now a publicly-traded company.
Today, the CEO is worth a little under $100 million.

In every stage of one’s career, there’s often one defining moment — an inflection point — where one’s career takes a turn for the better (or worse). In my initial foray into industry, the story above was my turning point.

From that point forward, I got invited to the major decision meetings. I got appointed interim Chief Technology Officer since I was the only person to notice the impending disaster and helped to save the company from it. I went from managing nobody but myself to managing a team of 25 people.

I got a major promotion. My stock options increased by 500%. I received a 50% salary increase. All of this happened in less than one year. And all of it happened without me asking for any of it.

All of my subsequent career moves in industry were launched from that inflection point from my experience with LP. Future job offers in industry were indexed to the salary that included my unasked-for 50% raise. My future stock compensation plans were also indexed to what I had at LP. The same with job title, and level of responsibility.

Career progress in industry has a cumulative effect. For example, the compensation of your next job offer is extremely highly correlated with your current compensation. If you can elevate your compensation or job responsibility today, it will quite literally benefit you for decades to come.

So was any of this really justified?

Did I come up with any mind-blowing insight?

I didn’t really think so.

When I walk you through my logic of seeing a single server being overloaded, and identifying all the natural consequences of that fact, it was hardly rocket science.

I’m sure many if not most of you would have come to the same conclusion if you were paying attention.

But here is my point.

In industry, most people are NOT paying attention to the BIG PICTURE — because it’s not in their job description.

THAT is the Achilles’ heel of people who work in industry. It’s also an opportunity to take advantage of too, if you’re thoughtful and deliberate about it.

You see the team at LP was a strong team. The head of sales was brilliant. A true rain maker. The CFO was a former CFO of a $5 billion Fortune 500 company. The engineers were good too.

The problem was everyone was focusing on their individualized areas of responsibility and the only person looking at how all the facets of the company fit together was the CEO… and me.

Please re-read that last sentence very careful.

In any business, there is only one person whose job it is to see how all the parts of a business fit together. That’s the CEO.

When you have the ability to see how the many facets of a business fit together and are interrelated with one another, suddenly the CEO sees you as a peer and colleague. There are conversations you can have with each other that others in the company simply won’t grasp.

There’s enormous value in being able to adopt this perspective.

As you go higher and higher in an organization, either formally on the organization chart, or informally via your influence, the more CEO-level thinking skills become the key that opens doors to the upper echelons of your company.

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