Buffett spends countless hours researching each of his equities. Before making a decision, he reads annual reports, news publications and any other information he can get his hands on. His decisions are informed by research, and based on the strict fundamentals that work best for his style of investing.
The way Buffett operates is not unlike the best use cases for big data. Among other things, his success lies in his ability to make good decisions in accordance with quality benchmarks. This is the key to using big data well, and to business success in general.
Big data users can learn from Warren Buffett. His brain, in effect, is a kind of big data engine. Here are three lessons that Buffett provides for big data users:
1. Know What You’re Looking For
By analyzing large amounts of data from diverse sources, we can gain context and correlations that wouldn’t have otherwise occurred to us. Buffett pulls from actuary reports and bond publications; big data can suck information out of nearly everything, from social media to expense reports.
But it is all for nothing if you don’t know what you’re looking for. You need structure around your queries.
Buffett has a few rules of thumb. He looks for low-volatility stocks with a low price-to-book ratio. They should be profitable and growing, among other considerations.
Similarly, if you ask your data analytics platform the right questions, you’ll know the best answers when you see them. Perhaps you’re looking for a Scotch-drinking customer base that prefers premium product and prioritizes convenience over shopping around. If you know that before you ask your data engine to generate their social media preferences, you’ll get a much better result than if you asked the same question about Scotch drinkers in general.
2. Understand How the Object of Your Research Works
Buffett once said: “Never invest in a business you can’t understand.” Given Buffett’s rational investment style, one can surmise the meaning behind that quote. If you don’t understand the mechanics of your investment, you’re relying too much on emotion and guesswork. Or else the business itself isn’t viable.
Likewise, if you don’t understand how the organization or customer base you’re running a big data query on works, you’re relying too heavily on assumptions. You could ask questions of the data that have nothing to do with the reality of the situation. Asking questions about the rate of email responses in a customer support organization that relies mostly on forums won’t get you very far.
3. Use Solid Benchmarks
Some of Warren Buffett’s more famous quotes illustrate the precision and simplicity of his benchmarks:
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“Rule No. 1: never lose money. Rule No. 2: don’t forget rule No. 1.”
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“Only buy something that you’d be perfectly happy to hold if the market shut down for 10 years.”
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“It’s far better to buy a wonderful company at a fair price than a fair company at a wonderful price.”
These benchmarks demand the best. They don’t compromise. Arrange your own benchmarks to similar standards, ask the right questions, and make data driven decisions that reflect your high standards and style.
Make Data Your Servant
Maybe one of Warren Buffett’s biggest secrets to success is that he made the data work for him. If you aspire to do the same, data will quickly become your best friend.
Author: Chanu Damarla, Senior Director of Product Management at GoodData.
(image: stock market genius / shutterstock)
