Building targets, constructing behaviour

Recently, the press reported that UK construction company Bovis Homes Group PLC have run into trouble for encouraging new homeowners to move into unfinished homes and have therefore faced a barrage of complaints about construction defects. It turns out that these practices were motivated by a desire to hit ambitious growth targets. Yet it has all had a substantial impact on trading position and mark downs for Bovis shares.1

I have blogged about targets before. It is worth repeating what I said there about the thoughts of John Pullinger, head of the UK Statistics Authority. He gave a trenchant warning about the “unsophisticated” use of targets. He cautioned:2

Anywhere we have had targets, there is a danger that they become an end in themselves and people lose sight of what they’re trying to achieve. We have numbers everywhere but haven’t been well enough schooled on how to use them and that’s where problems occur.

He went on.

The whole point of all these things is to change behaviour. The trick is to have a sophisticated understanding of what will happen when you put these things out.

That message was clearly one that Bovis didn’t get. They legitimately adopted an ambitious growth target but they forgot a couple of things. They forgot that targets, if not properly risk assessed, can create perverse incentives to distort the system. They forgot to think about how manager behaviour might be influenced. Leaders need to be able to harness insights from behavioural economics. Further, a mature system of goal deployment imposes a range of metrics across a business, each of which has to contribute to the global organisational plan. It is no use only measuring sales if measures of customer satisfaction and input measures about quality are neglected or even deliberately subverted. An organisation needs a rich dashboard and needs to know how to use it.

Critically, it is a matter of discipline. Employees must be left in no doubt that lack of care in maintaining the integrity of the organisational system and pursuing customer excellence will not be excused by mere adherence to a target, no matter how heroic. Bovis was clearly a culture where attention to customer requirements was not thought important by the staff. That is inevitably a failure of leadership.

Compare and contrast

Bovis are an interesting contrast with supermarket chain Sainsbury’s who featured in a law report in the same issue of The Times.3 Bovis and Sainsbury’s clearly have very different approaches as to how they communicate to their managers what is important.

Sainsbury’s operated a rigorous system of surveying staff engagement which aimed to embrace all employees. It was “deeply engrained in Sainsbury’s culture and was a critical part of Sainsbury’s strategy”. An HR manager sent an email to five store managers suggesting that the rigour could be relaxed. Not all employees needed to be engaged, he said, and participation could be restricted to the most enthusiastic. That would have been a clear distortion of the process.

Mr Colin Adesokan was a senior manager who subsequently learned of the email. He asked the HR manager to explain what he had meant but received no response and the email was recirculated. Adesokan did nothing. When his inaction came to the attention of the chief executive, Adesokan was dismissed summarily for gross misconduct.

He sued his employer and the matter ended up in the Court of Appeal, Adesokan arguing that such mere inaction over a colleague’s behaviour was incapable of constituting gross misconduct. The Court of Appeal did not agree. They found that, given the significance placed by Sainsbury’s on the engagement process, the trial judge had been entitled to find that Adesokan had been seriously in dereliction of his duty. That failing constituted gross misconduct because it had the effect of undermining the trust and confidence in the employment relationship. Adesokan seemed to have been indifferent to what, in Sainsbury’s eyes, was a very serious breach of an important procedure. Sainsbury’s had been entitled to dismiss him summarily for gross misconduct.

That is process discipline. That is how to manage it.

Display constancy of purpose in communicating what is important. Do not turn a blind eye to breaches. Do not tolerate those who would turn the blind eye. When you combine that with mature goal deployment and sophistication as to how to interpret variation in metrics then you are beginning to master, at least some parts of, how to run a business.

References

  1. “Share price plunges as Bovis tries to rebuild customers’ trust” (paywall), The Times (London), 20 February 2017
  2. “Targets could be skewing the truth, statistics chief warns” (paywall), The Times (London), 26 May 2014
  3. Adesokan v Sainsbury’s Supermarkets Ltd [2017] EWCA Civ 22, The Times, 21 February 2017 (paywall)
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Productivity and how to improve it: I -The foundational narrative

Again, much talk in the UK media recently about weak productivity statistics. Chancellor of the Exchequer (Finance Minister) George Osborne has launched a 15 point macroeconomic strategy aimed at improving national productivity. Some of the points are aimed at incentivising investment and training. There will be few who argue against that though I shall come back to the investment issue when I come to talk about signal and noise. I have already discussed training here. In any event, the strategy is fine as far as these things go. Which is not very far.

There remains the microeconomic task for all of us of actually improving our own productivity and that of the systems we manage. That is not the job of government.

Neither can I offer any generalised system for improving productivity. It will always be industry and organisation dependent. However, I wanted to write about some of the things that you have to understand if your efforts to improve output are going to be successful and sustainable.

  • Customer value and waste.
  • The difference between signal and noise.
  • How to recognise flow and manage a constraint.

Before going on to those in future weeks I first wanted to go back and look at what has become the foundational narrative of productivity improvement, the Hawthorne experiments. They still offer some surprising insights.

The Hawthorne experiments

In 1923, the US electrical engineering industry was looking to increase the adoption of electric lighting in American factories. Uptake had been disappointing despite the claims being made for increased productivity.

[Tests in nine companies have shown that] raising the average initial illumination from about 2.3 to 11.2 foot-candles resulted in an increase in production of more than 15%, at an additional cost of only 1.9% of the payroll.

Earl A Anderson
General Electric
Electrical World (1923)

E P Hyde, director of research at GE’s National Lamp Works, lobbied government for the establishment of a Committee on Industrial Lighting (“the CIL”) to co-ordinate marketing-oriented research. Western Electric volunteered to host tests at their Hawthorne Works in Cicero, IL.

Western Electric came up with a study design that comprised a team of experienced workers assembling relays, winding their coils and inspecting them. Tests commenced in November 1924 with active support from an elite group of academic and industrial engineers including the young Vannevar Bush, who would himself go on to an eminent career in government and science policy. Thomas Edison became honorary chairman of the CIL.

It’s a tantalising historical fact that Walter Shewhart was employed at the Hawthorne Works at the time but I have never seen anything suggesting his involvement in the experiments, nor that of his mentor George G Edwards, nor protégé Joseph Juran. In later life, Juran was dismissive of the personal impact that Shewhart had had on operations there.

However, initial results showed no influence of light level on productivity at all. Productivity rose throughout the test but was wholly uncorrelated with lighting level. Theories about the impact of human factors such as supervision and motivation started to proliferate.

A further schedule of tests was programmed starting in September 1926. Now, the lighting level was to be reduced to near darkness so that the threshold of effective work could be identified. Here is the summary data (from Richard Gillespie Manufacturing Knowledge: A History of the Hawthorne Experiments, Cambridge, 1991).

Hawthorne data-1

It requires no sophisticated statistical analysis to see that the data is all noise and no signal. Much to the disappointment of the CIL, and the industry, there was no evidence that illumination made any difference at all, even down to conditions of near darkness. It’s striking that the highest lighting levels embraced the full range of variation in productivity from the lowest to the highest. What had seemed so self evidently a boon to productivity was purely incidental. It is never safe to assume that a change will be an improvement. As W Edwards Deming insisted, “In God was trust. All others bring data.”

But the data still seemed to show a relentless improvement of productivity over time. The participants were all very experienced in the task at the start of the study so there should have been no learning by doing. There seemed no other explanation than that the participants were somehow subliminally motivated by the experimental setting. Or something.

Hawthorne data-2

That subliminally motivated increase in productivity came to be known as the Hawthorne effect. Attempts to explain it led to the development of whole fields of investigation and organisational theory, by Elton Mayo and others. It really was the foundation of the management consulting industry. Gillespie (supra) gives a rich and intriguing account.

A revisionist narrative

Because of the “failure” of the experiments’ purpose there was a falling off of interest and only the above summary results were ever published. The raw data were believed destroyed. Now “you know, at least you ought to know, for I have often told you so” about Shewhart’s two rules for data presentation.

  1. Data should always be presented in such a way as to preserve the evidence in the data for all the predictions that might be made from the data.
  2. Whenever an average, range or histogram is used to summarise observations, the summary must not mislead the user into taking any action that the user would not take if the data were presented in context.

The lack of any systematic investigation of the raw data led to the development of a discipline myth that every single experimental adjustment had led forthwith to an increase in productivity.

In 2009, Steven Levitt, best known to the public as the author of Freakonomics, along with John List and their research team, miraculously discovered a microfiche of the raw study data at a “small library in Milwaukee, WI” and the remainder in Boston, MA. They went on to analyse the data from scratch (Was there Really a Hawthorne Effect at the Hawthorne Plant? An Analysis of the Original Illumination Experiments, National Bureau of Economic Research, Working Paper 15016, 2009).

LevittHawthonePlot

Figure 3 of Levitt and List’s paper (reproduced above) shows the raw productivity measurements for each of the experiments. Levitt and List show how a simple plot such as this reveals important insights into how the experiments developed. It is a plot that yields a lot of information.

Levitt and List note that, in the first phase of experiments, productivity rose then fell when experiments were suspended. They speculate as to whether there was a seasonal effect with lower summer productivity.

The second period of experiments is that between the third and fourth vertical lines in the figure. Only room 1 experienced experimental variation in this period yet Levitt and List contend that productivity increased in all three rooms, falling again at the end of experimentation.

During the final period, data was only collected from room 1 where productivity continued to rise, even beyond the end of the experiment. Looking at the data overall, Levitt and List find some evidence that productivity responded more to changes in artificial light than to natural light. The evidence that increases in productivity were associated with every single experimental adjustment is weak. To this day, there is no compelling explanation of the increases in productivity.

Lessons in productivity improvement

Deming used to talk of “disappointment in great ideas”, the propensity for things that looked so good on paper simply to fail to deliver the anticipated benefits. Nobel laureate psychologist Daniel Kahneman warns against our individual bounded rationality.

To guard against entrapment by the vanity of imagination we need measurement and data to answer the ineluctable question of whether the change we implemented so passionately resulted in improvement. To be able to answer that question demands the separation of signal from noise. That requires trenchant data criticism.

And even then, some factors may yet be beyond our current knowledge. Bounded rationality again. That is why the trick of continual improvement in productivity is to use the rigorous criticism of historical data to build collective knowledge incrementally.

If you torture the data enough, nature will always confess.

Ronald Coase

Eventually.

The Productivity Paradox

File:City of London skyline at dusk.jpgThis last week saw a further report from the Bank of England that UK productivity has fallen inexplicably behind the nation’s aspirations. There is a compelling picture of the development of productivity over time on the Office of National Statistics (“ONS”) website here.

There is general puzzlement, and disquiet, among UK economists as to why productivity is not improving. It seems to suggest that cutting the costs of production is not at the top of UK business agendas. It’s true that there are other important things to worry about: design and redesign of products and services, reputation, customer experience, workplace engagement, safety and sustainability.

But I suspect that there is nothing more important than productivity. It is only by learning how to do more with less that resources can be freed up to develop novel income streams. Even on matters of safety and environment, it is the efficient organisation that finds the resources to take those matters seriously.

The road to increased productivity is well mapped out. The continual improvement of the alignment between the Voice of the Process and the Voice of the Customer, by the means of diligent criticism of historical data is an open secret.

Trust in forecasting

File:City of London skyline at dusk.jpgStephen King (global economist at HSBC) made some profound comments about forecasting in The Times (London) (paywall) yesterday.

He points out that it is only a year since the International Monetary Fund (IMF) criticised UK economic strategy and forecast 0.7% GDP growth in 2013 and 1.5% in 2014. The latest estimate for 2013 is growth is 1.9%. The IMF now forecasts growth for 2014 at 2.4% and notes the strength of the UK economy. I should note that the UK Treasury’s forecasts were little different from the IMF’s.

Why, asks King, should we take any notice of the IMF forecast, or their opinions, now when they are so unapologetic about last year’s under estimate and their supporting comments?

The fact is that any forecast should come attached to an historic record of previous forecasts and actual outcomes, preferably on a deviation from aim chart. In fact, wherever somebody offers a forecast and there is no accompanying historic deviation from aim chart, I think it a reasonable inference that they have something to hide. The critical matter is that the chart must show a stable and predictable process of forecasting. If it does then we can start to make tentative efforts at estimating accuracy and precision. If not then there is simply no rational forecast. It would be generous to characterise such attempts at foresight as guesses.

Despite the experience base, forecasting is all about understanding fundamentals. King goes on to have doubts about the depth of the UK’s recovery and, in particular, concerns about productivity. The ONS data is here. He observes that businesses are choosing to expand by hiring cheap labour and suggests macroeconomic remedies to foster productivity growth such as encouraging small and medium sized enterprises, and enhancing educational effectiveness.

It comes back to a paradox that I have discussed before. There is a well signposted path to improved productivity that seems to remain The Road Not Taken. Everyone says they do it but it is clear from King’s observations on productivity that, in the UK at least, they do not. That would be consistent with the chronically poor service endemic in several industries. Productivity and quality go hand in hand.

I wonder if there is a preference in the UK for hiring state subsidised cheap labour over the rigorous and sustained thinking required to make real productivity improvements. I have speculated elsewhere that producers may feel themselves trading in a market for lemons. The macroeconomic causes of low productivity growth are difficult for non-economists such as myself to divine.

However, every individual company has the opportunity to take its own path and “Put its sticker on a lemon”. Governments may look to societal remedies but as an indefatigable female politician once trenchantly put it:

The individual is the true reality in life. A cosmos in himself, he does not exist for the State, nor for that abstraction called “society,” or the “nation,” which is only a collection of individuals. Man, the individual, has always been and, necessarily is the sole source and motive power of evolution and progress.

Emma Goldman
The Individual, Society and the State, 1940