The numbers game that cheats business of its real sense of value

Using hard data, such as sales and income figures, as facts on which to base decisions is a dangerous trap that too many businesses are falling into

Alan_MitchellSpare a thought for those fighting to survive at the front line of the credit crunch. How on earth would you cope if you were facing a market that was 50% down on last year, with tens of thousands of people depending on it for their livelihoods?The news from the motor industry is frightening. UK sales of new cars are down 22% on a year ago. Sales of trucks are down 42%. Vans down 58%. In the US, the figures are even crazier. General Motors’ sales are down 53% compared to a year ago. Ford is down 44%.

Where next? At a get-together organised last week by the strategic innovation firm The Foundation, Evening Standard City editor Anthony Hilton suggested that things might not be as bad as they seem. Thanks to manufacturers’ adoption of techniques such as “just in time”, they are responding much faster to the fall-off in demand, he observed. With factories closed temporarily, stock is being sold off. We might see a rise in demand as early as the autumn. So perhaps it’s just a temporary blip after all.

Looking across the water to the US, however, the Financial Times was less sanguine. Perhaps we’ll never return to a time when the industry sold 16 million units a year, it wondered. Perhaps this year’s forecast of 9 million units is not an aberration after all – just the new normal. Well, which is it? 9 million or 16 million? It’s breathtaking that both figures can be discussed seriously at the same time.

This raises a question about numbers. Which numbers can we trust?It’s an article of faith among many business people that hard factual numbers, such as income from sales, are the ultimate touchstone for decision-making/ numbers like these don’t lie. After all, they are hard, undeniable, incontrovertible facts. But are they? Really?When the City was making unimaginable amounts of money gambling on asset prices, it thought it was looking at hard, undeniable facts. But these “facts” suckered the City into believing that gambling was the same as wealth creation. Yes, the banks had hard evidence of the money they were making – it was there, in black and white, in the report and accounts. But if you look just at money numbers, you cannot tell the difference between income earned from gambling and income earned from genuine value delivery, because in a spreadsheet all numbers look the same. They’re just numbers.

Now take the credit bubble. If you were a car marketer looking at the hard data of actual sales over the past ten years, you would have seen a steady – apparently rock solid – rise. Your evidence of success is sales and the message of the data is plain: each year we sell more. So what are we going to do? Plan for demand to fall off a cliff on the basis that it is a bubble? Or extrapolate just a little further?Cash cows can also suck you into the traps laid by hard incontrovertible evidence. Cash cows usually kill their host businesses via a painfully familiar pattern. The company looks at the data – the hard evidence of its actual sales and income – and knows what side its bread is buttered on. Numerous outsiders warn it that this heyday cannot last forever, that new competitors are emerging, that market conditions are changing. But right now, looking at things from inside the company, any rational person looking at the data will see there’s no better way to invest your money than do more of what you are currently doing.

“Invest in new disruptive technologies, business models or distribution channels? Sure thing! … One day. But right now those investments won’t earn anything like what we can earn right now just doing more of the same.”

Ten years ago, for example, ITV was earning fabulous margins of 60% or so. Its advertiser clients were queuing up to give it business. It had a near-monopoly stranglehold. In theory, this would have been just the right time to start investing in the new digital platforms that would revolutionise the industry. But these investments were very risky. The likely returns looked pitiful. Looking at the hard data in front of you, what decision would you have made?There are many other ways in which hard, incontrovertible sales and income data conspire to deceive us. Sales promotions are a classic example. There is no denying it, promotions such as buy one get one free often have huge sales effects. What’s not half as clear, however, is whether you actually increase overall consumption by doing them or merely time-shift the same consumption into different purchasing periods (answer: it depends). Ditto: have you actually gained market share or merely ended up purchasing the same market share for a much higher cost, once you take account of your competitors’ retaliatory promotions? In cases like this, it’s the numbers behind the numbers that really matter. But numbers behind numbers are usually much harder to get at. And their decision-making implications are usually much less clear cut.

Hard data hypnosis can even be triggered by operational issues. When Tesco first launched its home shopping service, it was staggered by the difference between what its customers clicked on to order and what its hard sales data told it. It realised that the clicks were telling it what its customers really wanted to buy. Its sales data was only telling it what they ended up buying when the stuff they really wanted to buy was out of stock. In cases like this, if you build decision-making only on hard, factual data – “oh look, that’s selling well, let’s order more of it” – then your decisions may not be very good at all.

Is there a way of out of the hard data trap? There certainly isn’t a formula, but there might be some useful rules of thumb. One such rule of thumb is to treat any quest to maximise – sales, profits, whatever – as if it were a treacherous snake. It’s a pretty fair assumption that business models and practices built on maximisation are not sustainable, and vice versa. Thinking in terms of sustainability forces you to look beyond numbers alone.

That begs the question of what sustainable business models look like. Again, there’s no formula. But it looks like it’s something to do with focusing on underlying, enduring human needs and value. What do our customers really want?Does financial gambling enrich the lives of ordinary people? No. Do cash cows? Very rarely. If you’re making your numbers in a way that doesn’t connect with enduring human value, something is probably suspect.

There’s something comforting about the solidity of this benchmark of human value. When Amazon chief executive Geoff Bezos was asked how he prioritised innovation investments for example, his reply was that he looked for the things that weren’t going to change. Looking ahead ten years, he asked, will customers want to pay more? Unlikely, so therefore it’s a good idea to focus innovation on things that cut operational costs. Will they want slower deliveries? Probably not, so it may be a good idea to innovate around faster delivery. Will they want better or worse service? You get the picture.

Likewise, Tesco realised that many people wanted to spend less time shopping so, even as it was investing in its cash cow superstores, it needed to also invest in home shopping. Toyota invested in greener hybrid technologies even as Detroit invested in gas guzzlers. And some banks had the guts to stay clear of derivatives.

Hard numbers as evidence? Sure, we need hard numbers. But – much more important – we need to know what the numbers mean, because they can never be a substitute for judgement. 


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