How much of what you read today will you still care about a year from now?
Any of it?
I ask myself this question a lot, and it’s painful. If I’m honest with myself the answer is often close to none.
The Intelligent Investor by Ben Graham was written in 1934. I’ve confirmed that, eighty-three years later, it still sells more than 100,000 copies per year.
It still sells because its message is timeless. If Graham wrote What the Intelligent Investor Should Do in 1935, it may have sold well in 1934, and then fallen into the void of forgotten books soon after.
It’s amazing how much of the information we consume has a half life measured in days or months, and how little is like Graham’s book – cherished for decades because it teaches something with permanent relevance.
MIT’s endowment fund recently wrote something great:
We noticed some years ago that much of the information we consumed was expiring knowledge. Examples of expiring knowledge might include: which cable company got acquired last week? How did manager X perform last year? What is the office vacancy rate in New York City?
While the answers to these questions represent useful context that could help us make decisions today, none have long-term value. In contrast, long-term knowledge might be represented by answers to questions such as: why is the cable industry consolidating? What is the competitive advantage of manager X and is it sustainable? What are the long-term drivers of demand for office space in various cities in the U.S.?
Expiring knowledge catches more attention than it should, for two reasons. One, there’s a lot of it, eager to buzz our short attention spans. Two, we chase it down, anxious to squeeze out insight before it loses relevance.
Long-term knowledge is harder to notice because it’s buried in books rather than blasted in headlines. But its benefit is huge. It’s not just that long-term knowledge rarely expires, letting you accumulate it over time. It’s that compounds over time. Expiring knowledge tells you what happened; long-term knowledge tells you why something happened and is likely to happen again. That “why” can translate and interact with stuff you know about other topics, which is where the compounding comes in.
Take a company’s performance. Sales. Margins. Cash flow.
These are important pieces of information. But they expire. No one cares anymore about Microsoft’s Q2 2004 revenue growth. They care that Microsoft generates lots of cash over time because it has a moat. Understanding moats – why they exist, how they are defended, etc. – is long-term knowledge. When you view it this way you realize that the revenue and cash flow information is a short-term reflection of the moat. Which means the expiring information can’t be put into proper context without the permanent stuff. And once you spend enough time studying moats you start to see them (and the lack of them) in other industries – which is something Microsoft’s Q2 2004 revenue number won’t do for you.
Same with managers. There are two types of startups: Those walking through a field of landmines, and those obliviously wandering through a field of landmines. Rather than asking, “Is this company going to face a problem?” – the answer is “yes,” and problems come and go – more long-term knowledge is asking “Does this management team have the tenacity and gumption to navigate problems when they inevitably arise?” Here again, individual company problems are one-offs, but understanding how managers execute and are motivated is a scalable topic that compounds over time.
I read newspapers and books every day. I can not recall one damn thing I read in a newspaper from, say, 2011. But I can tell you details about a few great books I read in 2011 and how they changed how I think. I’ll remember them forever. I’ll keep reading newspapers. But if I read more books I’d probably develop better filters and frameworks that would help me make better sense of the news.
The point, then, isn’t that you should watch less CNBC and read more Ben Graham. It’s that if you read more Ben Graham you’ll have an easier time understanding what you should or shouldn’t pay attention to on CNBC. This applies to most fields.
I try to ask when I’m reading: Will I care about this a year from now? Ten years from now? Eighty years from now?
It’s fine if the answer is “no,” even a lot of the time. But if you’re honest with yourself you may begin to steer toward the enduring bits of knowledge.