The Pitfalls of Productivity

Metrics, KPI’s and incentives can be dangerous things. Just ask the CEO and senior leaders of Wells Fargo, who were proud of an incentive scheme rewarding staff for opening new accounts until it landed them in court and in front of a baying senate. Staff had responded to the scheme by opening false accounts en masse, in many cases robbing real customers of their money.

I saw many such pitfalls during my time in business, though none as openly fraudulent as this one. Management rightly tried to use simple, targetable metrics to steer their businesses, a practice that only became more widespread once scorecards and dashboards came into vogue. Sometimes the real target was the leader’s own bonus package, but more often than not I witnessed a genuine attempt to improve a complex business.

But the attempt backfired almost as often as it succeeded. A common example is the trade off between volume and margin. Sales people love volume targets and respond well to incentives on volume, but the risk is that they chase down prices in their zeal or target customers of low value. In the short term, margin incentives can make more sense, but not if they result in collusion with competitors or in pulling back from profitable, if marginal, clients. Further, margin is usually more complicated to measure and influence, and sales people value simplicity.

The most dangerous indicators are usually ratios, KPI’s measures as X per Y. A margin target is usually a ratio, something like dollars per litre. An acid test of a good ratio is that it is always beneficial to both increase the numerator and to decrease the denominator. In the case of a margin KPI, it will almost always be good to grow the dollars, but often not good to reduce the litres. Further, reducing the litres is the easiest way to shift the indicator in the short term. So such a margin target runs a severe risk of a department follow a “golden litre”, that is shrinking the business down just to the most profitable clients, a sure recipe for a business death spiral.

Shell and others tried to get around the volume/margin dilemma by targeting a concept called contribution. This was sound, and generally successful, but it lacked simplicity and often left sales people confused.

In call centers, a common incentive KPI is time per call. True, dealing with complaints and enquiries quickly is a good general idea, but not at the expense of being thorough. In some cases, employees have been known to put the phone down on customers where the call showed signs of dragging on.

In Shell retail, another example of a ratio metric was called efficiency index, defined as sales volume per station compared with the market average. This had the same downside, namely that while growing volume is certainly good, reducing station numbers can be easier and unhelpful to the business. What if those stations still made a good contribution, and had low capital and costs to serve, low risks and low effort intensity? That was usually the case with dealer owned stations. I preferred a metric of company owned efficiency index, once again with the downside of loss of simplicity. I guess the moral is that business can be complex.

And if business is complex, so is macroeconomics. Central banks and governments face the same pitfalls in trying to find and influence levers to improve performance. And most politicians make the CEO of Wells Fargo seem honest. Maggie Thatcher relentlessly tinkered with definitions to try to obscure the scale of unemployment her policies caused. The Kirchner’s in Argentina gutted their statistics. We can trust very little data coming out of China, and the investors know it, but fear shouting out for the same reasons they pretended all was well with sub-prime mortgages eight years ago – their own golden eggs depend on the deception.

Even honest Economists have difficulties, one notable one being that times change. Forty years ago policy was all about avoiding devaluation, then it became a helpful tool, only we didn’t see how helpful until the Euro zone discarded it. Much of the current weaponry was designed to control inflation, but now we realise that we need more of it not less.

There is a faction trying to redefine GDP, or at least to replace the current definition of GDP in many key indicators. Partly this is because GDP itself has become slightly out-dated, because it doesn’t really reflect things that have low manufacturing component or are almost free like internet access or Airbnb bookings.

One thing we can still do is to choose to use GDP total or GDP per capita. Businesses like GDP total, because that drives activity and demand for them. But for wellbeing of citizens, GDP per capita matters more. Japanese GDP is declining, but mainly because the population is shrinking. That carries challenges, but one of those is not immediate poverty, since GDP per capita is still rising.

An indicator that seems to have survived the test of time is productivity, defined as some measure output per a chosen unit of input, usually labour hour.

 I first studied Economics in the 1970’s, and at the time UK labour productivity was suffering compared with that of Germany and others. Pundits had easy explanations. British workers were lazy, and usually on strike. British managers lacked drive. Germany benefited from having lost the war, because it meant its infrastructure could be replaced.

Even back then, it was possible to see the problem with the indicator. Higher productivity was generally good, but which of these explanations was most likely to be right, or was it a combination or something else? And what exactly could policymakers do to improve things? In practice, the politicians chose their own causes and remedies – so for example the right demonised trade unions.

Since then bigger problems with the indicator have emerged. It seems difficult to predict and sometimes moves in surprising ways. But worse than that, it suffers from the classic problem with ratios – increasing the numerator is good, but reducing the denominator is not unless there is full employment, which there rarely is nowadays. Indeed, much government policy is designed to create jobs, irrespective of any output generated.

So we have an indicator that has lost its lustre. The numerator seems poorly measured, due to the trend away from manufacturing. The denominator is not something governments want to reduce. And the metric is not intuitive or simple or even particularly actionable.

So why do we still measure it? I suppose there is some potential merit to trying to improve output per unit of input, if only the output could be measured and the input was somehow constrained. I’ve read many explanations for its trend, but not my own pet theory, which is that it measures the sort of portfolio of work an economy specialises in. Policy in the UK, and increasingly the US, drives more people into low wage service jobs. As this constitutes a greater share of the mix, productivity goes down. But so what?

Productivity fails so many tests of a good indicator. Perhaps the only reason it is still popular is to support a pet theory of a politician or partisan economist, such as enabling union bashing or lobbying for infrastructure investment. It is time to consign this indicator to the dustbin.