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.

FIFA and the Iron Law of Oligarchy

Йозеф Блаттер.jpgIn 1911, Robert Michels embarked on one of the earliest investigations into organisational culture. Michels was a pioneering sociologist, a student of Max Weber. In his book Political Parties he aggregated evidence about a range of trade unions and political groups, in particular the German Social Democratic Party.

He concluded that, as organisations become larger and more complex, a bureaucracy inevitably forms to take, co-ordinate and optimise decisions. It is the most straightforward way of creating alignment in decision making and unified direction of purpose and policy. Decision taking power ends up in the hands of a few bureaucrats and they increasingly use such power to further their own interests, isolating themselves from the rest of the organisation to protect their privilege. Michels called this the Iron Law of Oligarchy.

These are very difficult matters to capture quantitavely and Michels’ limited evidential sampling frame has more of the feel of anecdote than data. “Iron Law” surely takes the matter too far. However, when we look at the allegations concerning misconduct within FIFA it is tempting to feel that Michels’ theory is validated, or at least has gathered another anecdote to take the evidence base closer to data.

But beyond that, what Michels surely identifies is a danger that a bureaucracy, a management cadre, can successfully isolate itself from superior and inferior strata in an organisation, limiting the mobility of business data and fostering their own ease. The legitimate objectives of the organisation suffer.

Michels failed to identify a realistic solution, being seduced by the easy, but misguided, certainties of fascism. However, I think that a rigorous approach to the use of data can guard against some abuses without compromising human rights.

Oligarchs love traffic lights

I remember hearing the story of a CEO newly installed in a mature organisation. His direct reports had instituted a “traffic light” system to report status to the weekly management meeting. A green light meant all was well. An amber light meant that some intervention was needed. A red light signalled that threats to the company’s goals had emerged. At his first meeting, the CEO found that nearly all “lights” were green, with a few amber. The new CEO perceived an opportunity to assert his authority and show his analytical skills. He insisted that could not be so. There must be more problems and he demanded that the next meeting be an opportunity for honesty and confronting reality.

At the next meeting there was a kaleidoscope of red, amber and green “lights”. Of course, it turned out that the managers had flagged as red the things that were either actually fine or could be remedied quickly. They could then report green at the following meeting. Real career limiting problems were hidden behind green lights. The direct reports certainly didn’t want those exposed.

Openness and accountability

I’ve quoted Nobel laureate economist Kenneth Arrow before.

… a manager is an information channel of decidedly limited capacity.

Essays in the Theory of Risk-Bearing

Perhaps the fundamental problem of organisational design is how to enable communication of information so that:

  • Individual managers are not overloaded.
  • Confidence in the reliable satisfaction of process and organisational goals is shared.
  • Systemic shortfalls in process capability are transparent to the managers responsible, and their managers.
  • Leading indicators yield early warnings of threats to the system.
  • Agile responses to market opportunities are catalysed.
  • Governance functions can exploit the borrowing strength of diverse data sources to identify misreporting and misconduct.

All that requires using analytics to distinguish between signal and noise. Traffic lights offer a lousy system of intra-organisational analytics. Traffic light systems leave it up to the individual manager to decide what is “signal” and what “noise”. Nobel laureate psychologist Daniel Kahneman has studied how easily managers are confused and misled in subjective attempts to separate signal and noise. It is dangerous to think that What you see is all there is. Traffic lights offer a motley cloak to an oligarch wishing to shield his sphere of responsibility from scrutiny.

The answer is trenchant and candid criticism of historical data. That’s the only data you have. A rigorous system of goal deployment and mature use of process behaviour charts delivers a potent stimulus to reluctant data sharers. Process behaviour charts capture the development of process performance over time, for better or for worse. They challenge the current reality of performance through the Voice of the Customer. They capture a shared heuristic for characterising variation as signal or noise.

Individual managers may well prefer to interpret the chart with various competing narratives. The message of the data, the Voice of the Process, will not always be unambiguous. But collaborative sharing of data compels an organisation to address its structural and people issues. Shared data generation and investigation encourage an organisation to find practical ways of fostering team work, enabling problem solving and motivating participation. It is the data that can support the organic emergence of a shared organisational narrative that adds further value to the data and how it is used and developed. None of these organisational and people matters have generalised solutions but a proper focus on data drives an organisation to find practical strategies that work within their own context. And to test the effectiveness of those strategies.

Every week the press discloses allegations of hidden or fabricated assets, repudiated valuations, fraud, misfeasance, regulators blindsided, creative reporting, anti-competitive behaviour, abused human rights and freedoms.

Where a proper system of intra-organisational analytics is absent, you constantly have to ask yourself whether you have another FIFA on your hands. The FIFA allegations may be true or false but that they can be made surely betrays an absence of effective governance.

#oligarchslovetrafficlights

Deconstructing Deming XI B – Eliminate numerical goals for management

11. Part B. Eliminate numerical goals for management.

W. Edwards Deming.jpgA supposed corollary to the elimination of numerical quotas for the workforce.

This topic seems to form a very large part of what passes for exploration and development of Deming’s ideas in the present day. It gets tied in to criticisms of remuneration practices and annual appraisal, and target-setting in general (management by objectives). It seems to me that interest flows principally from a community who have some passionately held emotional attitudes to these issues. Advocates are enthusiastic to advance the views of theorists like Alfie Kohn who deny, in terms, the effectiveness of traditional incentives. It is sad that those attitudes stifle analytical debate. I fear that the problem started with Deming himself.

Deming’s detailed arguments are set out in Out of the Crisis (at pp75-76). There are two principle reasoned objections.

  1. Managers will seek empty justification from the most convenient executive time series to hand.
  2. Surely, if we can improve now, we would have done so previously, so managers will fall back on (1).

The executive time series

I’ve used the time series below in some other blogs (here in 2013 and here in 2012). It represents the anual number of suicides on UK railways. This is just the data up to 2013.
RailwaySuicides2

The process behaviour chart shows a stable system of trouble. There is variation from year to year but no significant (sic) pattern. There is noise but no signal. There is an average of just over 200 fatalities, varying irregularly between around 175 and 250. Sadly, as I have discussed in earlier blogs, simply selecting a pair of observations enables a polemicist to advance any theory they choose.

In Railway Suicides in the UK: risk factors and prevention strategies, Kamaldeep Bhui and Jason Chalangary of the Wolfson Institute of Preventive Medicine, and Edgar Jones of the Institute of Psychiatry, King’s College, London quoted the Rail Safety and Standards Board (RSSB) in the following two assertions.

  • Suicides rose from 192 in 2001-02 to a peak 233 in 2009-10; and
  • The total fell from 233 to 208 in 2010-11 because of actions taken.

Each of these points is what Don Wheeler calls an executive time series. Selective attention, or inattention, on just two numbers from a sequence of irregular variation can be used to justify any theory. Deming feared such behaviour could be perverted to justify satisfaction of any goal. Of course, the process behaviour chart, nowhere more strongly advocated than by Deming himself in Out of the Crisis, is the robust defence against such deceptions. Diligent criticism of historical data by means of process behaviour charts is exactly what is needed to improve the business and exactly what guards against success-oriented interpretations.

Wishful thinking, and the more subtle cognitive biases studied by Daniel Kahneman and others, will always assist us in finding support for our position somewhere in the data. Process behaviour charts keep us objective.

If not now, when?

If I am not for myself, then who will be for me?
And when I am for myself, then what am “I”?
And if not now, when?

Hillel the Elder

Deming criticises managerial targets on the grounds that, were the means of achieving the target known, it would already have been achieved and, further, that without having the means efforts are futile at best. It’s important to remember that Deming is not here, I think, talking about efforts to stabilise a business process. Deming is talking about working to improve an already stable, but incapable, process.

There are trite reasons why a target might legitimately be mandated where it has not been historically realised. External market conditions change. A manager might unremarkably be instructed to “Make 20% more of product X and 40% less of product Y“. That plays in to the broader picture of targets’ role in co-ordinating the parts of a system, internal to the organisation of more widely. It may be a straightforward matter to change the output of a well-understood, stable system by an adjustment of the inputs.

Deming says:

If you have a stable system, then there is no use to specify a goal. You will get whatever the system will deliver.

But it is the manager’s job to work on a stable system to improve its capability (Out of the Crisis at pp321-322). That requires capital and a plan. It involves a target because the target captures the consensus of the whole system as to what is required, how much to spend, what the new system looks like to its customer. Simply settling for the existing process, being managed through systematic productivity to do its best, is exactly what Deming criticises at his Point 1 (Constancy of purpose for improvement).

Numerical goals are essential

… a manager is an information channel of decidedly limited capacity.

Kenneth Arrow
Essays in the Theory of Risk-Bearing

Deming’s followers have, to some extent, conceded those criticisms. They say that it is only arbitrary targets that are deprecated and not the legitimate Voice of the Customer/ Voice of the Business. But I think they make a distinction without a difference through the weasel words “arbitrary” and “legitimate”. Deming himself was content to allow managerial targets relating to two categories of existential risk.

However, those two examples are not of any qualitatively different type from the “Increase sales by 10%” that he condemns. Certainly back when Deming was writing Out of the Crisis most OELs were based on LD50 studies, a methodology that I am sure Deming would have been the first to criticise.

Properly defined targets are essential to business survival as they are one of the principal means by which the integrated function of the whole system is communicated. If my factory is producing more than I can sell, I will not work on increasing capacity until somebody promises me that there is a plan to improve sales. And I need to know the target of the sales plan to know where to aim with plant capacity. It is no good just to say “Make as much as you can. Sell as much as you can.” That is to guarantee discoordination and inefficiency. It is unsurprising that Deming’s thinking has found so little real world implementation when he seeks to deprive managers of one of the principle tools of managing.

Targets are dangerous

I have previously blogged about what is needed to implement effective targets. An ill judged target can induce perverse incentives. These can be catastrophic for an organisation, particularly one where the rigorous criticism of historical data is absent.

The art of managing footballers

Van Persie (15300483040) (crop).jpg… or is it a science? Robin van Persie’s penalty miss against West Bromwich Albion on 2 May 2015 was certainly welcome news to my ears. It eased the relegation pressures on West Brom and allowed us to advance to 40 points for the season. Relegation fears are only “mathematical” now. However, the miss also resulted in van Persie being relieved of penalty taking duties, by Manchester United manager Louis van Gaal, until further notice.

He is now at the end of the road. It is always [like that]. Wayne [Rooney] has missed also so when you miss you are at the bottom again.

The Daily Mail report linked above goes on to say that van Persie had converted his previous 6 penalties.

Van Gaal was, of course, referring to Rooney’s shot over the crossbar against West Ham in February 2013, when Rooney had himself invited then manager Sir Alex Ferguson to retire him as designated penalty taker. Rooney’s record had apparently been 9 misses from 27 penalties. I have all this from this Daily Telegraph report.

I wonder if statistics can offer any insight into soccer management?

The benchmark

It was very difficult to find, very quickly, any exhaustive statistics on penalty conversion rates on the web. However, I would like to start by establishing what constituted “good” performance for a penalty taker. As a starting point I have looked at Table 2 on this Premier League website. The data is from February 2014 and shows, at that date, data on the players with the best conversion rates in the League’s history. Players who took fewer than 10 penalties were excluded. It shows that of the ten top converting players, who must rank as the very good if not the ten best, in the aggregate they converted 155 of 166 penalties. That is a conversion rate of 93.4%. At first sight that suggests a useful baseline against which to assess any individual penalty taker.

Several questions come to mind. The aggregate statistics do not tell us how individual players have developed over time, whether improving or losing their nerve. That said, it is difficult to perform that sort of analysis on these comparatively low volumes of data when collected in this way. There is however data (Table 4) on the overall conversion rate in the Premier League since its inception.

Penalties

That looks to me like a fairly stable system. That would be expected as players come and go and this is the aggregate of many effects. Perhaps there is latterly reduced season-to-season variation, which would be odd, but I am not really interested in that and have not pursued it. I am aware that during this period there has been a rule change allowing goalkeepers to move before the kick his taken but I have just spent 30 minutes on the web and failed to establish the date when that happened. The total aggregate statistics up to 2014 are 1,438 penalties converted out of 1,888. That is a conversion rate of 76.2%.

I did wonder if there was any evidence that some of the top ten players were better than others or whether the data was consistent with a common elite conversion rate of 93.4%. In that case the table positions would reflect nothing more than sampling variation. Somewhat reluctantly I calculated the chi-squared statistic for the table of successes and failures (I know! But what else to do?). The statistic came out as 2.02 which, with 9 degrees of freedom, has a p-value (I know!) of 0.8%. That is very suggestive of a genuine ranking among the elite penalty takers.

It inevitably follows that the elite are doing better than the overall success rate of 76.2%. Considering all that together I am happy to proceed with 93.4% as the sort of benchmark for a penalty taker that a team like Manchester United would aspire to.

Van Persie

This website, dated 6 Sept 2012, told me that van Persie had converted 18 penalties with a 77% success rate. That does not quite fit either 18/23 or 18/24 but let us take it at face value. If that is accurate then that is, more or less, the data on which Ferguson gave van Persie the job in February 2013. It is a surprising appointment given the Premier League average of 76.2% and the elite benchmark but perhaps it was the best that could be mustered from the squad.

Rooney’s 9 misses out of 27 yields a success rate of 67%. Not so much lower than van Persie’s historical performance but, in all the circumstances, it was not good enough.

The dismissal

What is fascinating is that, no matter what van Persie’s historical record on which he was appointed penalty taker, before his 2 May miss he had scored 6 out of 6. The miss made it 6 out of 7, 85.7%. That was his recent record of performance, even if selected to some extent to show him in a good light.

Selection of that run is a danger. It is often “convenient” to select a subset of data that favours a cherished hypothesis. Though there might be that selectivity, where was the real signal that van Persie had deteriorated or that the club would perform better were he replaced?

The process

Of course, a manager has more information than the straightforward success/ fail ratio. A coach may have observed goalkeepers increasingly guessing a penalty taker’s shot direction. There may have been many near-saves, a hesitancy on the part of the player, trepidation in training. Those are all factors that a manager must take into account. That may lead to the rotation of even the most impressive performer. Perhaps.

But that is not the process that van Gaal advocates. Keep scoring until you miss then go to the bottom of the list. The bottom! Even scorers in the elite-10 miss sometimes. Is it rational to then replace them with an alternative that will most likely be more average (i.e. worse)? And then make them wait until everyone else has missed.

With an average success rate of 76.2% it is more likely than not that van Persie’s replacement will score their first penalty. Van Gaal will be vindicated. That is the phenomenon called regression to the mean. An extreme event (a miss) is most likely followed by something more average (a goal). Economist Daniel Kahneman explores this at length in his book Thinking, Fast and Slow.

It is an odd strategy to adopt. Keep the able until they fail. Then replace them with somebody less able. But different.

 

Deconstructing Deming XI A – Eliminate numerical quotas for the workforce

11. Part A. Eliminate numerical quotas for the workforce.

W Edwards DemingI find this probably the most confused part of Deming’s thinking. Carefully reading Out of the Crisis (at pp70-75) Deming’s attack is not on standardised work, that is advocated as central to his message, but against specifications for the volume of work: calls answered per hour, finished parts per day.

Deming recognises management’s need to predict costs and revenues but condemns quotas as destructive of achieving productivity.

Deming also deprecates such quotas as corroding workplace pride. I shall return to that in Point 12.

Deming’s criticism of work quotas goes as follows.

  • Some individuals may achieve them easily and their productive capacity will then stand idle.
  • Some individuals may struggle and suffer poor moral.
  • Some individuals may compromise quality so as to make a quota or so as to make it sooner.
  • Achievement of quotas may be frustrated by faults in “the system” which are outside the individual worker’s control.

Deming gives the following example of how he would advise financial planning in a call centre of 500 people (at pp73-74).

  1. Set a preliminary budget.
  2. Make it clear to every one of the 500 that their aim is to give satisfaction to the customer, to take pride in their work.
  3. Everybody will keep a record of calls made.
  4. Customers with special problems will be referred to the supervisor.
  5. At the end of each week, sample 100 individuals’ record and summarise the data.
  6. Repeat steps 2 to 5 for several weeks.
  7. Analyse the data.
  8. Establish a continuing study following the above steps but on a reducing basis.
  9. Use the data to predict costs.

Now there is much merit in forecasting costs based on actual data. Further, improving performance based on the relentless criticism of historical data is essential. However, I think Deming’s prescription naïve and idealistic. The trick is to extract the ideals and industrialise them.

Planning

The simple matter is that any new enterprise has to be established on the basis of a robust business plan. There is competition for resources: people, capital, infrastructure … and everyone has to make their case. It is impossible to do that without judgment. No matter how much historical data or even qualitative experience is to hand we cannot simply project it into the future without establishing further conditions (RearView). It is unlikely this can ever be done exactly in a new establishment.

That competition for resources then prevents us from taking an overly conservative view of what can be achieved. Setting the bar too low for call centre operators starts off from an uncompetitive position. Further, the modest answering rate in the plan has to be resourced with infrastructure. Intentions to improve the answering rate post-launch are all very well but what will happen to the personnel and materiel that we bought in to accommodate the unambitious start-up?

Sometimes work needs to be set at a rate that is recognised by a team of co-workers and other parts of the organisation. Excess production is as contrary to the philosophy of lean operations as is shortage. The idea of takt time allows production lines to be balanced, receipts and deliveries co-ordinated, stock turns to be minimised and cash flows improved. In many situations that is sufficient to answer Deming’s fears about individuals distorting production to bank an accomplished target.

Stretch

What is now proved was once but imagined.

William Blake

Is it so wrong to set a target that nobody involved has seen achieved before? Deming would say that it was fine so long as there was a plan defining the means by which this could be achieved. There are many compelling stories from sports science telling how records have been broken by incremental improvement (e.g. Dave Brailsford and the GB cycling team).

But what about setting an ambitious stretch target without a plan for achieving it? That would be brave indeed. It would be based on no more than an exhortation to the call centre operators to work more furiously, more furiously than anyone had ever done before. I cannot say that would never work. In my athletics days I ran some of my best times when team mates were urging me on from the sidelines. However, as a business strategy it faces the social realities of employees’ collective ability to resist quietly that to which they do not assent. With a carefully recruited and motivated team it could work. It would certainly require a high degree of collective problem solving and improvement by the operators. But of all strategies for operational excellence it looks the most limited and the most risky. There is no obvious Plan B.

The Ringelmann effect

There is a tension between unrealistic stretch targets and a further problem that Deming ignores entirely, the Ringelmann effect. It may sadden the hearts of those who believe in the inherent fulfilling joy of work and best intentions of workers to do a good job but evidence is overwhelming that there are situations where individuals exert less effort in a group environment than they would if acting individually.

In 1913, Max Ringelmann conducted experiments that showed that individuals pulled less strenuously on a rope when pulling in a group than when pulling alone.

A realistically set and communicated takt time can assist in concentrating effort and communicating common work standards and the expectations of peers.

The poor supervisor

If Deming was so pessimistic as to believe that workers would sacrifice quality to hit targets then they would surely be more than happy to shunt enquiries off to their supervisor in order to post commendable performance. All that Deming’s proposal does is to divert the whole problem of difficult calls to the supervisor who, presumably, is either beset with his own performance problems or operates outside business measurement.

Deconstructing Deming X – Eliminate slogans!

10. Eliminate slogans, exhortations and targets for the workforce.

W Edwards Deming

Neither snow nor rain nor heat nor gloom of night stays these couriers from the swift completion of their appointed rounds.

Inscription on the James Farley Post Office, New York City, New York, USA
William Mitchell Kendall pace Herodotus

Now, that’s what I call a slogan. Is this what Point 10 of Deming’s 14 Points was condemning? There are three heads here, all making quite distinct criticisms of modern management. The important dimension of this criticism is the way in which managers use data in communicating with the wider organisation, in setting imperatives and priorities and in determining what individual workers will consider important when they are free from immediate supervision.

Eliminate slogans!

The US postal inscription at the head of this blog certainly falls within the category of slogans. Apparently the root of the word “slogan” is the Scottish Gaelic sluagh-ghairm meaning a battle cry. It seeks to articulate a solidarity and commitment to purpose that transcends individual doubts or rationalisation. That is what the US postal inscription seeks to do. Beyond the data on customer satisfaction, the demands of the business to protect and promote its reputation, the service levels in place for individual value streams, the tension between current performance and aspiration, the disappointment of missed objectives, it seeks to draw together the whole of the organisation around an ideal.

Slogans are part of the broader oral culture of an organisation. In the words of Lawrence Freedman (Strategy: A History, Oxford, 2013, p564) stories, and I think by extension slogans:

[make] it possible to avoid abstractions, reduce complexity, and make vital points indirectly, stressing the importance of being alert to serendipitous opportunities, discontented staff, or the one small point that might ruin an otherwise brilliant campaign.

But Freedman was quick to point out the use of stories by consultants and in organisations frequently confused anecdote with data. They were commonly used selectively and often contrived. Freedman sought to extract some residual value from the culture of business stories, in particular drawing on the work of psychologist Jerome Bruner along with Daniel Kahneman’s System 1 and System 2 thinking. The purpose of the narrative of an organisation, including its slogans and shared stories, is not to predict events but to define a context for action when reality is inevitably overtaken by a special cause.

In building such a rich narrative, slogans alone are an inert and lifeless tactic unless woven with the continual, rigorous criticism of historical data. In fact, it is the process behaviour chart that acts as the armature around which the narrative can be wound. Building the narrative will be critical to how individuals respond to the messages of the chart.

Deming himself coined plenty of slogans: “Drive out fear”, “Create joy in work”, … . They are not forbidden. But to be effective they must form a verisimilar commentary on, and motivation for, the hard numbers and ineluctable signals of the process behaviour chart.

Eliminate exhortations!

I had thought I would dismiss this in a single clause. It is, though, a little more complicated. The sports team captain who urges her teammates onwards to take the last gasp scoring opportunity doesn’t necessarily urge in vain. There is no analysis of this scenario. It is only muscle, nerve, sweat and emotion.

The English team just suffered a humiliating exit from the Cricket World Cup. The head coach’s response was “We’ll have to look at the data.” Andrew Miller in The Times (London) (10 March 2015) reflected most cricket fans’ view when he observed that “a team of meticulously prepared cricketers suffered a collective loss of nerve and confidence.” Exhortations might not have gone amiss.

It is not, though, a management strategy. If your principal means of managing risk, achieving compelling objectives, creating value and consistently delivering customer excellence, day in, day out is to yell “one more heave!” then you had better not lose your voice. In the long run, I am on the side of the analysts.

Slogans and exhortations will prove a brittle veneer on a stable system of trouble (RearView). It is there that they will inevitably corrode engagement, breed cynicism, foster distrust, and mask decline. Only the process behaviour chart can guard against the risk.

Eliminate targets for the workforce!

This one is more complicated. How do I communicate to the rest of the organisation what I need from them? What are the consequences when they don’t deliver? How do the rest of the organisation communicate with me? This really breaks down into two separate topics and they happen to be the two halves of Deming’s Point 11.

I shall return to those in my next two posts in the Deconstructing Deming series.

 

Deconstructing Deming IX – Break down barriers between staff areas

9. Break down barriers between staff areas.

W Edwards Deming

Something there is that doesn’t love a wall,
That wants it down!

Robert Frost
Mending Wall (1914)

Point 9 of Deming’s 14 Points. One that is always attractive to a self describing iconoclast. Barriers must be bad if they prevent the exchange and interaction of ideas, or worse if they lead to optimisation within a subunit that suboptimises the wider system. Deming was thinking of managers such as John Browett. Browett was given charge of Apple’s retail operations and immediately started to cut staff numbers and hours in order to reduce his own budget. However, Apple’s avowed strategy is to foster reputation and brand loyalty through a distinctive, unconventional and delightfully effective Apple Store encounter. My wife is more of an enthusiast for Apple products than I, but I am always wowed by our Store visits.

I feel sorry for Browett as he was clearly left to guess the corporation’s strategy. Some organisational functions are just there because they enable the principle value streams. Without them profits would fall. Silo management is the term mockingly used to satirise a management dominated by pillars of functional expertise bolstered by professional status and mute to its “rival” silos.

Deming reminded us that somebody in a leadership position does need to maintain a synoptic view of the business system to prevent Browett type misunderstandings.

Deming system diagramAnybody who has been to a Deming seminar will have seen the Deming system diagram. Deming invited participants to focus on the system that created revenues for the organisation and, further, to see that system as a network of processes. Deming used the diagram to emphasis that the critical business processes transect organisational boundaries. Raw materials, whether physical or transactional, run into and out of the silos. Some processes don’t transform the raw materials but act as critical support for the supplier-customer strand. Deming argued that equipment maintenance, product development etc. are nonetheless processes transforming their own inputs into vital enablers and accelerants of the revenue generating activities.

Further, held Deming, those processes run across the external boundaries of the organisation into suppliers and customer. A manufacturer making car tyres is part of a bigger picture including the manufacture of the tyre rubber and even the way the end user drives his motor car. Only by understanding the whole can the tyre performance be optimised, customer value maximised, and growing market share and revenues realised.

Yet the power of the functions remains and is seldom mitigated by implementing process management. Process management is something with which organisations still struggle.Those who try to follow the idea of dispersing expertise into the processes frequently find that individuals embedded in cross-functional teams perform less well than within their concentrated centres of excellence. It is worth remembering how two counterbalancing forces arise.

Behaviour

Any proposed system of reward must be risk assessed against the behaviours it is likely to encourage or discourage. Managers given the job of reducing the cost of running their own silo will do just that. All managers are optimising within their own bounded rationality.

Goal deployment

One tactic that can help prevent managers from optimising their own subsystem at the expense of the greater is to adopt some system of goal deployment such as hoshin kanri. Visibility, both horizontally and vertically, of how individual results contribute to organisational goals, effected through objective supervision and strategic governance, ought to discourage suboptimisation and reveal any such trends at an early time.

Professional expertise is important

In 1776, Scottish philosopher Adam Smith told the parable of the pin maker. Smith set out a detailed argument for the benefits of specialisation and the division of labour. The silos provide the means of rewarding the development of expertise in itself, something whose value may only be seen in the future, and of fostering the application of that expertise in management.

Deming was somewhat inimical to this idea and thought that managers should work in a variety of roles across functions as they ascended the hierarchy, as he felt they did in Japan. Yet it is critical in that environment to maintain the virtues of the silos as incubators of expertise. This is not so easily achieved.

Organisational boundaries exist for a reason

In The Democratic Corporation (1994) Russell Ackoff asked why we could not make a business out of mutually and severally co-operating individuals, each negotiating a web of personal contracts that made up the system that delivered the goods.

Nobel laureate economist Ronald Coase had already answered the question in his 1937 paper The Nature of the Firm. Coase explained why organisations are promoted and employ the people who might otherwise be a market of interacting individual contractors. It simply came down to the costs of operating such a market and the savings that could be made from making a global decision to bring some people and facilities under a single enduring roof.

Organisational and even function boundaries often arise from subtle cost structures. Perhaps these develop over time as more connected ways of remote working become commonplace. But it is important to analyse the forces that created and perpetuate the silos. Otherwise, it should be no surprise when the benefits of process management go unrealised.