My son Chaitanya was born today, ten years ago. He was two months premature. His birth weight just 1.4 kg – 60% lesser than the average birth weight of 3.5 kg – and he spent the first three weeks of his life in an ICU.
We were not allowed inside the ICU for the risk of infection to the newborns, and so the nurse used to “display” our son from behind two glass doors for the first one week. Even my wife was not allowed entry to the ICU for the first week. Every time we asked how the baby was doing, the nurse would pull out her clipboard and dictate to us his ‘quantitative status’ – his heart rate, temperature, oxygen level, infection level, etc.
A week after Chaitanya’s birth, when my wife was first allowed to meet him, she realized he was lying still in his incubator which the nurse said was fine as he was too weak for any movement. Even his eyes were still. “He will be like that for a few more days, ma’am,” the nurse told my wife, “till he gains some strength.”
My wife was not ready for this, and so she laid Chaitanya in her lap, and started to hum
her favourite ‘mother’ song
, which most Hindi-speaking mothers must have sung over and over again in their lifetimes.
Chaitanya moved his eyes and looked at his mother. The nurse, lifting her eyes off her statistical clipboard, was shocked.
It was then that my wife knew her baby was doing fine, without bothering about any “numbers” that the nurse was blurting out by her side. From then on and till we were in the hospital, I asked “How is he doing?” to my wife and rarely the nurse.
Being an analyst and investor, I have come to know intuitively that, whether it is about a person’s or a company’s health, quantitative measures or numbers, while critically important, tell us only part of the story.
In business analysis, for example, you can calculate all the ratios you can find from now until the end of the world. But unless you try to find the cause of the numbers you come up with, you are playing a useless game.
Unless you understand the working of the business – the underpinnings, the culture, the management, growth runway, etc. – no amount of financial analysis would help you.
I have learned this the hard way. Refusing to own some amazing companies – which felt like amazing then – just because they had little debt on their balance sheets, or a temporary negative free cash flow situation, or just because the stock price had run up a few percentage points more than what I was comfortable with – has caused me a lot of agony in the past (in terms of the mistakes of omission).
“Investing is simple, but not easy,” said Charlie Munger.
Calculating past growth and profitability numbers for a business and understanding whether those are good or bad is simple, but actually trying to understand a business deeply enough to visualize how it will look like in the future is not easy.
Knowing that a business has moat as seen from its superior profitability and clean balance sheet is simple, but understanding whether this moat is sustainable or fleeting is not easy.
Calculating book value of a company is simple, but understanding whether that book really has value, and roughly how much, is not easy.
Knowing the results that numbers shout out of financial statements is simple, but knowing which of those results are signal and which are noise is not easy.
Knowing how DCF works is simple, but looking at businesses with a DCF frame of mind is not easy.
Calculating precise intrinsic values for businesses is simple, but trusting approximations that really work is not easy. (Keynes said – “It’s better to be approximately right than precisely wrong.”)
Knowing beta is a measure of volatility is simple, but appreciating that volatility isn’t the real risk you face in investing is not easy.
Understanding that money can multiply 100x in 25 years when you compound at 20% annually is simple, but sitting through these 25 years patiently when others are cashing in after having made 5-10x is not easy.
Marshall Jaffe wrote in his post titled The Limits of Data in Finance and Life –
All of our decisions are driven by partial information; we just can’t know everything. As objective as we try to be, relying too heavily on any one tool, however useful, can actually separate us from the very reality we think we’re measuring. The one thing that can offset this potential and keep us firmly in the real world is the inclusion of our imperfect, behaviorally biased, subjective but common sense observations.
Understanding the limits of numbers is useful for analysts and investors. Before getting swept up in running financial screeners, collecting numbers, and building models to predict the future of businesses, it is worth considering why you think numbers would solve your problem.
Of course, knowing and understanding the numbers – the vital stats – whether in health or investing, is important to know a part of where you stand today. But if you just depend on those stats to tell you whether things are all fine or not and where they are likely to head, you are missing out on the real, bigger picture.
That’s about it from me for today.
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