Right Company, Wrong Vector

In November 2011, Berkshire Hathaway bought sixty-four million shares of IBM at an average price of around one hundred and seventy dollars. The position was worth roughly $10.7 billion at cost. It was a 5.5 percent stake in the company and one of the largest single positions Berkshire had ever opened in a publicly traded name. 1

The thesis Warren Buffett put on the inside cover of that position was specific. IBM was no longer a hardware company. It was a services-led moat with deeply embedded enterprise customers who would not switch lightly. The thing he was buying was the durability of that moat against everyone trying to displace it. 2

Six years later he sold most of it, in stages, at prices below where he had bought. By the spring of 2018 the position was gone. Over the same window IBM stock was down roughly eighteen percent. The S&P 500 was up one hundred and sixteen percent. Berkshire’s other technology bet, the AAPL position Buffett had begun in 2016, had already grown larger than IBM had ever been on Berkshire’s book.

In May 2017 he told CNBC, _“I don’t value IBM the same way that I did six years ago when I started buying. I’ve revalued it somewhat downward.”_3 Nine months after the exit was complete, he was more direct. _“I was wrong, or at least I felt like I was wrong on IBM when I sold it and I was wrong when I bought it.”_4

That second sentence is the one to read carefully.

It does the only thing the vocabulary lets it do. It blames the thesis. The whole story collapses into a single axis. Was he right about the company, or was he wrong about the company. He worked out he was wrong. He said so out loud, in public, with his own name on it, which is more than almost anyone in the industry will ever do.

And the most articulate post-mortem voice in modern finance still got compressed into one word.

Wrong.

This essay is about what is missing from that word.

A Pick Is a Magnitude. A Position Is a Vector.

In physics class, a magnitude is a number. A vector is a number with a direction attached. Forty miles per hour is a magnitude. Forty miles per hour going north is a vector. The two carry different information. A magnitude tells you how much. A vector tells you how much, and where it is pointed. The investing industry has one word for both, and it is the wrong word.

If you have ever held a name through a triple and not felt the triple in your book, you have lived this. The magnitude was right. The vector was wrong.

A position is a vector with at least seven slots. Size is one of them. The thesis sentence is another. The other five are the ones the post-mortem cannot name out loud: what would have to be true for the thesis to be wrong, how long the thesis is allowed to take, what other names in the book this position is correlated to, what the position pays out if the thesis only half-lands, and how the position would be exited if the falsifier triggered.

Each of those is a separate decision. Each can move while the ticker stays the same. None of them are in the magnitude. The whole apparatus of the industry, the position percentage on a tearsheet, the weight in a 13F filing, the line in a quarterly letter, is built to compress all seven slots into the one slot the file format can hold.

A pick is a magnitude. A position is a vector. The industry’s word for both is the same word, and the word that wins is the smaller one.

The category error sits here. The investor hears “what is your largest position” and answers with a name and a percentage. The right answer, the one that survives a bad year, is a profile. The percentage is one number in that profile. It is not the profile.

Two Investors. One Company. Two Different Positions.

Run the thought experiment with two investors over Buffett’s window.

Both wrote the same thesis on the inside cover in November 2011. IBM is no longer a hardware company. It is a services-led moat with deeply embedded enterprise customers who will not switch easily. The same paragraph. The same name. The same year.

The first investor sized the position to roughly five percent of the equity book on conviction in the moat. The exit rule was “if I change my mind.” The holding period was “long term.” The falsifier was nowhere on paper. The dependency on the cloud transition being slow rather than fast was implicit, not stated. The opportunity cost against the next-best technology bet of the decade was not tested until that bet had already done the heavy work for someone else.

The second investor sized the same thesis at one percent. They wrote a falsifier in the position memo: if IBM’s services revenue declines for two consecutive quarters with management citing competitive losses to cloud-native vendors, the moat thesis is invalidated for this regime, and the position closes within the next reporting cycle. The holding period was a rolling four-quarter window, not “long term.” Re-evaluation was on the calendar at every print. The dependency on the cloud transition being slow was named explicitly, so any acceleration in cloud adoption would tighten the falsifier rather than leave it dormant.

By 2014, when IBM’s services revenue first showed real cracks with explicit cloud-competitive language from management on the call, the second investor’s falsifier triggered. They closed the position into the next reporting cycle at a small loss against entry and redeployed. The first investor read the same earnings, watched the chart hold, and stayed.

Same thesis. Same company. Same paragraph on the inside cover. Two completely different positions, three years apart in their first invalidation event, with two completely different outcomes downstream.

Two investors with the same thesis on the same company can hold completely different positions, and only one of them can be reverse-engineered from the post-mortem.

When the first investor wrote up the failure, the only sentence available was “I was wrong about IBM.” It is not actually a true sentence about the thesis. The thesis was approximately right at the level of granularity at which it was written. IBM did remain a services-led business. Most of its enterprise customers did not switch lightly. The moat existed. It just degraded faster than the size and the holding period and the missing falsifier had quietly assumed it would.

The vocabulary made it look like a thesis error. It was a vector error, in the durability slot, the falsifier slot, the holding-period slot, and the opportunity-cost slot. Four wrong directions on a vector that was being held as if it were a magnitude.

The Substrate Speaks Before the Headline

The second investor noticed something the first one did not.

A thesis is a claim about a substrate. IBM has a services moat is not the substrate. It is a sentence about the substrate. The substrate itself is the network of switching costs, the salesforce relationships, the integration debt customers had built on IBM’s stack, the technical depth of the services organisation, the rate at which competitors could credibly displace any of those things. The thesis sentence holds up only as long as the substrate underneath it does.

Substrates erode slowly. They erode in the kind of small, public, observable details that do not move the price chart for several quarters. AWS launched in 2006. By 2013 it was at scale. By 2014 enterprise cloud adoption was visibly accelerating in exactly the kind of Fortune 500 customer accounts IBM’s services moat was supposed to protect. By 2015 IBM’s own earnings calls were naming cloud competitive pressure in the services segment.

The price chart did not reflect any of that until 2016, and even then only partially. The headline followed the substrate by about three quarters.

If you have ever read a 10-Q where a segment that used to anchor the thesis is suddenly being described in defensive language, and decided to wait one more print to confirm what you already knew, you have felt this. The substrate told you. The headline took another nine months to follow.