While investing, don’t be misled by numbers

Here’s a fascinating idea, verbatim from a talk by Rory Sutherland, a well-known advertising executive. “People look at Maths, and as soon as there are things in numerical form, you’ve won the argument. If you’re one of those marketers who’s trying to use words, and some other b_____ turns up with a spreadsheet, you’ve basically lost. The b______ with the spreadsheet always wins.” Sutherland is the Vice Chairman of the O&M advertising group and has pioneered the use of behavioural science in advertising. The above quote shows his preference for words and ideas over numbers.

Do such ideas have a place in investing? As a first reaction, many people would say no, they don’t. In investing, numbers play a central role. ‘Data-driven’ is the buzzword in everything, including investing. According to this ideology, the way to judge an investment— in fact, the only way to judge an investment— is to look at the numbers. However, in practice, what one might call the human factor plays just as important a role. Qualitative factors such as management competence, company culture, and industry trends can significantly impact a company’s growth and success. These factors may not be easily quantifiable in a spreadsheet, but they are key to investing.

Think of great companies like HDFC Bank, Asian Paints, Infosys, TCS, and so many others. Each of them is in a business with a dozen or more other companies. There is nothing unique about their businesses. What sets them apart is management quality. It’s not about the line of business but what the company’s management will make of it, how they will finetune it and how they will execute it. Almost all successful investment analysis is essentially a search for quality people. You may think that you are looking at financial numbers, but those are just clues to what actually matters. By incorporating qualitative factors, investors and analysts may be able to make more informed choices and potentially uncover opportunities that purely numerical data might overlook.

I’m not arguing that the numbers do not matter. Numerical analysis is the bedrock of investment analysis and planning. It’s important to be aware of both sides of the story. Unlike qualitative factors, quantitative data offers a clear and objective basis for making investment decisions. Financial ratios, historical performance, and other numerical data help investors by providing concrete evidence of a company’s financial health and growth prospects. Moreover, numbers are standardised, so to speak. Comparing diverse investment options, whether in stocks, mutual funds, or even fixed income, is impossible without numbers. In fact, there is no way to track and compare the performance of investments without using quantitative data.

There’s yet another layer of complexity to this question. While judging the human factor in corporate management is important, the quality of this judgement itself matters. When you bring the human factor of corporate management or an investment manager into the picture, the human factor of the analyst and the investor also comes in. I mean, anyone who is minimally knowledgeable can build a spreadsheet that sorts stocks by EPS or valuation. If the data and the formulae are correct, it works. In contrast, sorting companies by management quality takes years of experience and good judgement; even then, there’s a lot more room for error. Or rather, there’s a lot more room for self-delusion.
We’ve often heard the advice, “Just invest in a set of good stocks, monitor them closely and hold for years.” Good advice, right? And so simple, isn’t it? Actually, this advice is pretty useless, and I say that even though I have given it myself a few times. In fact, it’s not really advice but mere rhetoric. This old Wall Street joke is a favourite of mine: The newcomer asks a market veteran, “How do I make money on the stock market?” The old master replies, “Why, that’s very simple. Just buy low, sell high.” So the young man asks, “Yes, but how do I do that?” The reply comes, “That’s very difficult. It takes a lifetime to learn.”

(The author is CEO, VALUE RESEARCH)

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