Managers who influence decisions and strategy must see through the numbers to avoid expensive and foolish mistakes.

One out of 5 adults in the United Kingdom struggles with mental arithmetic, according to a study by YouGov. Among those surveyed, 35% need to use a regular calculator to add numbers that exceed one hundred. More alarmingly, those aged eighteen to twenty-four are about 3 times as likely to use regular calculators for very basic tasks compared with people who are fifty-five and older. Furthermore, 13% of those fifty-five and older make mistakes while 22% of those younger than forty-five make mistakes when performing simple multiplication tasks. The United Kingdom seems to be the representative of most Western countries. United States adults appear to score even lower.

There is little to none margin for error in the business universe. Managers who influence decisions and strategy must see through the numbers to avoid foolish and expensive mistakes. Paradoxically, as we progress from excel sheets and calculators to artificial intelligence and machine learning, our ability to make quick sense of numbers and make sure they are reasonable is not only more rare but even more required. Although it is necessary and recommended to use a scientific calculator when performing advanced operations that cannot be calculated without external help, it is advisable to get used to perform extremely simple operations through mental arithmetic.

Corporations today seek a more granular analysis that generates massive data cubes across the business lines, channels and geographies all the way down to the very customer-level contribution margin. Latest prediction models increasingly target to forecast profit opportunities that will guide operational priorities and  resource allocation. However, it can be considered anachronistic to rely on large teams of analysts to cope with all these data because cutting-edge algorithms can greatly improve prediction precision and new digital tools enable a very fine targeting with personalisation and accuracy.

However, strategic fundamentals remain the same. Companies still need to get their clients to pay more than what it costs to serve them. Usually, most business cases have just a handful of assumptions that truly matter. Is average sell-price realistic compared to the market share and volume it represents? Are costs consistent with past experience and benchmarks? Is the cash profile controllable to cover contingencies and sustain the investment?

Senior managers must quickly determine which numbers are right so they can identify issues and prevent terrible mistakes. Properly assessing plans and pressure testing assumptions always requires real-time calculation of pivotal numbers.

Hypotheses are made about contributing factors and impact, adding up the assumptions to predict the break-even points and the value. As teams launch into analytics, they jump to compare the findings with the hypotheses. When there is a discrepancy, they will study whether there are mistakes with the model or if the assumptions were wrong.

A much better math fluency is needed to get rid of the confirmation bias that frequently results in the initial estimation. Mental math will not only help enhance your business-decision making capabilities, it will also help you save time and money. Perhaps, if you train your proficiency with probabilities, you could better understand how our world works, not to mention see an enhanced ability to determine whether you will need a pair of sunglasses or an umbrella. Despite all my love for math, I do not get all right frequently!

The bio is the following: “Iñigo is a London-based digital copywriter passionate about the new technologies and the online universe. He spends his time writing about the topics he loves, travelling as much as he can and playing sports