Why did the polls get it wrong?

This week has seen much soul-searching by the UK polling industry over their performance leading up to the 2015 UK general election on 7 May. The polls had seemed to predict that Conservative and Labour Parties were neck and neck on the popular vote. In the actual election, the Conservatives polled 37.8% to Labour’s 31.2% leading to a working majority in the House of Commons, once the votes were divided among the seats contested. I can assure my readers that it was a shock result. Over breakfast on 7 May I told my wife that the probability of a Conservative majority in the House was nil. I hold my hands up.

An enquiry was set up by the industry led by the National Centre for Research Methods (NCRM). They presented their preliminary findings on 19 January 2016. The principal conclusion was that the failure to predict the voting share was because of biases in the way that the data were sampled and inadequate methods for correcting for those biases. I’m not so sure.

Population -> Frame -> Sample

The first thing students learn when studying statistics is the critical importance, and practical means, of specifying a sampling frame. If the sampling frame is not representative of the population of concern then simply collecting more and more data will not yield a prediction of greater accuracy. The errors associated with the specification of the frame are inherent to the sampling method. Creating a representative frame is very hard in opinion polling because of the difficulty in contacting particular individuals efficiently. It turns out that Conservative voters are harder than Labour voters to get hold of, so that they can be questioned. The NCRM study concluded that, within the commercial constraints of an opinion poll, there was a lower probability that a Conservative voter would be contacted. They therefore tended to be under-represented in the data causing a substantial bias towards Labour.

This is a well known problem in polling practice and there are demographic factors that can be used to make a statistical adjustment. Samples can be stratified. NCRM concluded that, in the run up to the 2015 election, there were important biases tending to under state the Conservative vote and the existing correction factors were inadequate. Fresh sampling strategies were needed to eradicate the bias and improve prediction. There are understandable fears that this will make polling more costly. More calls will be needed to catch Conservatives at home.

Of course, that all sounds an eminently believable narrative. These sorts of sampling frame biases are familiar but enormously troublesome for pollsters. However, I wanted to look at the data myself.

Plot data in time order

That is the starting point of all statistical analysis. Polls continued after the election, though with lesser frequency. I wanted to look at that data after the election in addition to the pre-election data. Here is a plot of poll results against time for Conservative and Labour. I have used data from 25 January to the end of 2015.1, 2 I have not managed to jitter the points so there is some overprinting of Conservative by Labour pre-election.

Polling201501

Now that is an arresting plot. Yet again plotting against time elucidates the cause system. Something happened on the date of the election. Before the election the polls had the two parties neck and neck. The instant (sic) the election was done there was clear red/ blue water between the parties. Applying my (very moderate) level of domain knowledge to the data before, the poll results look stable and predictable. There is a shift after the election to a new datum that remains stable and predictable. The respective arithmetic means are given below.

Party Mean Poll Before Election Mean Poll After
Conservative 33.3% 37.8% 38.8%
Labour 33.5% 31.2% 30.9%

The mean of the post-election polls is doing fairly well but is markedly different from the pre-election results. Now, it is trite statistics that the variation we observe on a chart is the aggregate of variation from two sources.

  • Variation from the thing of interest; and
  • Variation from the measurement process.

As far as I can gather, the sampling methods used by the polling companies have not so far been modified. They were awaiting the NCRM report. They certainly weren’t modified in the few days following the election. The abrupt change on 7 May cannot be because of corrected sampling methods. The misleading pre-election data and the “impressive” post-election polls were derived from common sampling practices. It seems to me difficult to reconcile NCRM’s narrative to the historical data. The shift in the data certainly needs explanation within that account.

What did change on the election date was that a distant intention turned into the recall of a past action. What everyone wants to know in advance is the result of the election. Unsurprisingly, and as we generally find, it is not possible to sample the future. Pollsters, and their clients, have to be content with individuals’ perceptions of how they will vote. The vast majority of people pay very little attention to politics at all and the general level of interest outside election time is de minimis. Standing in a polling booth with a ballot paper is a very different matter from being asked about intentions some days, weeks or months hence. Most people take voting very seriously. It is not obvious that the same diligence is directed towards answering pollster’s questions.

Perhaps the problems aren’t statistical at all and are more concerned with what psychologists call affective forecasting, predicting how we will feel and behave under future circumstances. Individuals are notoriously susceptible to all sorts of biases and inconsistencies in such forecasts. It must at least be a plausible source of error that intentions are only imperfectly formed in advance and mapping into votes is not straightforward. Is it possible that after the election respondents, once again disengaged from politics, simply recalled how they had voted in May? That would explain the good alignment with actual election results.

Imperfect foresight of voting intention before the election and 20/25 hindsight after is, I think, a narrative that sits well with the data. There is no reason whatever why internal reflections in the Cartesian theatre of future voting should be an unbiased predictor of actual votes. In fact, I think it would be a surprise, and one demanding explanation, if they were so.

The NCRM report does make some limited reference to post-election re-interviews of contacts. However, this is presented in the context of a possible “late swing” rather than affective forecasting. There are no conclusions I can use.

Meta-analysis

The UK polls took a horrible beating when they signally failed to predict the result of the 1992 election in under-estimating the Conservative lead by around 8%.3 Things then felt better. The 1997 election was happier, where Labour led by 13% at the election with final polls in the range of 10 to 18%.4 In 2001 each poll managed to get the Conservative vote within 3% but all over-estimated the Labour vote, some pollsters by as much as 5%.5 In 2005, the final poll had Labour on 38% and Conservative,  33%. The popular vote was Labour 36.2% and Conservative 33.2%.6 In 2010 the final poll had Labour on 29% and Conservative, 36%, with a popular vote of 29.7%/36.9%.7 The debacle of 1992 was all but forgotten when 2015 returned to pundits’ dismay.

Given the history and given the inherent difficulties of sampling and affective forecasting, I’m not sure why we are so surprised when the polls get it wrong. Unfortunately for the election strategist they are all we have. That is a common theme with real world data. Because of its imperfections it has to be interpreted within the context of other sources of evidence rather than followed slavishly. The objective is not to be driven by data but to be led by the insights it yields.

References

  1. Opinion polling for the 2015 United Kingdom general election. (2016, January 19). In Wikipedia, The Free Encyclopedia. Retrieved 22:57, January 20, 2016, from https://en.wikipedia.org/w/index.php?title=Opinion_polling_for_the_2015_United_Kingdom_general_election&oldid=700601063
  2. Opinion polling for the next United Kingdom general election. (2016, January 18). In Wikipedia, The Free Encyclopedia. Retrieved 22:55, January 20, 2016, from https://en.wikipedia.org/w/index.php?title=Opinion_polling_for_the_next_United_Kingdom_general_election&oldid=700453899
  3. Butler, D & Kavanagh, D (1992) The British General Election of 1992, Macmillan, Chapter 7
  4. — (1997) The British General Election of 1997, Macmillan, Chapter 7
  5. — (2002) The British General Election of 2001, Palgrave-Macmillan, Chapter 7
  6. Kavanagh, D & Butler, D (2005) The British General Election of 2005, Palgrave-Macmillan, Chapter 7
  7. Cowley, P & Kavanagh, D (2010) The British General Election of 2010, Palgrave-Macmillan, Chapter 7
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The Iron Law at Volkswagen

So Michael Horn, VW’s US CEO has made a “sincere apology” for what went on at VW.

And like so many “sincere apologies” he blamed somebody else. “My understanding is that it was a couple of software engineers who put these in.”

As an old automotive hand I have always been very proud of the industry. I have held it up as a model of efficiency, aesthetic aspiration, ambition, enlightenment and probity. My wife will tell you how many times I have responded to tales of workplace chaos with “It couldn’t happen in a car plant”. Fortunately we don’t own a VW but I still feel betrayed by this. Here’s why.

A known risk

Everybody knew from the infancy of emissions testing, which came along at about the same time as the adoption of engine management systems, the risks of a “cheat device”. It was obvious to all that engineers might be tempted to manoeuvre a recalcitrant engine through a challenging emissions test by writing software so as to detect test conditions and thereon modify performance.

In the better sort of motor company, engineers were left in no doubt that this was forbidden and the issue was heavily policed with code reviews and process surveillance.

This was not something that nobody saw coming, not a blind spot of risk identification.

The Iron Law

I wrote before about the Iron Law of Oligarchy. Decision taking executives in an organisation try not to pass information upwards. That will only result in interference and enquiry. Supervisory boards are well aware of this phenomenon because, during their own rise to the board, they themselves were the senior managers who constituted the oligarchy and who kept all the information to themselves. As I guessed last time I wrote, decisions like this don’t get taken at board level. They are taken out of the line of sight of the board.

Governance

So here we have a known risk. A threat that would likely not be detected in the usual run of line management. And it was of such a magnitude as would inflict hideous ruin on Volkswagen’s value, accrued over decades of hard built customer reputation. Volkswagen, an eminent manufacturer with huge resources, material, human and intellectual. What was the governance function to do?

Borrowing strength again

It would have been simple, actually simple, to secret shop the occasional vehicle and run it through an on-road emissions test. Any surprising discrepancy between the results and the regulatory tests would then have been a signal that the company was at risk and triggered further investigation. An important check on any data integrity is to compare it with cognate data collected by an independent route, data that shares borrowing strength.

Volkswagen’s governance function simply didn’t do the simple thing. Never have so many ISO 31000 manuals been printed in vain. Theirs were the pot odds of a jaywalker.

Knowledge

In the English breach of trust case of Baden, Delvaux and Lecuit v Société Générale [1983] BCLC 325, Mr Justice Peter Gibson identified five levels of knowledge that might implicate somebody in wrongdoing.

  • Actual knowledge.
  • Wilfully shutting one’s eyes to the obvious (Nelsonian knowledge).
  • Wilfully and recklessly failing to make such enquiries as an honest and reasonable man would make.
  • Knowledge of circumstances that would indicate the facts to an honest and reasonable man.
  • Knowledge of circumstances that would put an honest and reasonable man on enquiry.

I wonder where VW would place themselves in that.

How do you sound when you feel sorry?

… is the somewhat barbed rejoinder to an ungracious apology. Let me explain how to be sorry. There are three “R”s.

  • Remorse: Different from the “regret” that you got caught. A genuine internal emotional reaction. The public are good at spotting when emotions are genuine but it is best evidenced by the following two “R”s.
  • Reparation: Trying to undo the damage. VW will not have much choice about this as far as the motorists are concerned but the shareholders may be a different matter. I don’t think Horn’s director’s insurance will go very far.
  • Reform: This is the barycentre of repentance. Can VW now change the way it operates to adopt genuine governance and systematic risk management?

Mr Horn tells us that he has little control over what happens in his company. That is probably true. I trust that he will remember that at his next remuneration review. If there is one.

When they said, “Repent!”, I wonder what they meant.

Leonard Cohen
The Future

First thoughts on VW’s emmissions debacle

It is far too soon to tell exactly what went on at VW, in the wider motor industry, within the respective regulators and within governments. However, the way that the news has come out, and the financial and operational impact that it is likely to have, are enough to encourage all enterprises to revisit their risk management, governance and customer reputation management policies. Corporate scandals are not a new phenomenon, from the collapse of the Medici Bank in 1494, Warren Hastings’ alleged despotism in the British East India Company, down to the FIFA corruption allegations that broke earlier this year. Organisational scandals are as old as organisations. The bigger the organisations get, the bigger the scandals are going to be.

Normal Scandals

In 1984, Scott Perrow published his pessimistic analysis of what he saw as the inevitability of Normal Accidents in complex technologies. I am sure that there is a market for a book entitled Normal Scandals: Living with High-Risk Organisational Structures. But I don’t share Perrow’s pessimism. Life is getting safer. Let’s adopt the spirit of continual improvement to make investment safer too. That’s investment for those of us trying to accumulate a modest portfolio for retirement. Those who aspire to join the super rich will still have to take their chances.

I fully understand that organisations sometimes have to take existential risks to stay in business. The development of Rolls-Royce’s RB211 aero-engine well illustrates what happens when a manufacturer finds itself with proven technologies that are inadequately aligned with the Voice of the Customer. The market will not wait while the business catches up. There is time to develop a response but only if that solution works first time. In the case of Rolls-Royce it didn’t and insolvency followed. However, there was no alternative but to try.

What happened at VW? I just wonder whether the Iron Law of Oligarchy was at work. To imagine that a supervisory board sits around discussing the details of engine management software is naïve. In fact it was the RB211 crisis that condemned such signal failures of management to delegate. Do VW’s woes flow from a decision taken by a middle manager, or a blind eye turned, that escaped an inadequate system of governance? Perhaps a short term patch in anticipation of an ultimate solution?

Cardinal Newman’s contribution to governance theory

John Henry Newman learned about risk management the hard way. Newman was an English Anglican divine who converted to the Catholic Church in 1845. In 1850 Newman became involved in the controversy surrounding Giacinto Achilli, a priest expelled from the Catholic Church for rape and sexual assault but who was making a name from himself in England as a champion of the protestant evangelical cause. Conflict between Catholic and protestant was a significant feature of the nineteenth century English political landscape. Newman was minded to ensure that Achilli’s background was widely known. He took legal advice from counsel James Hope-Scott about the risks of a libel action from Achilli. Hope-Scott was reassuring and Newman published. The publication resulted in Newman’s prosecution and conviction for criminal libel.

Speculation about what legal advice VW have received as to their emissions strategy would be inappropriate. However, I trust that, if they imagined they were externalising any risk thereby, they checked the value of their legal advisors’ professional indemnity insurance.

Newman certainly seems to have learned his lesson and subsequently had much to teach the modern world about risk management and governance. After the Achilli trial Newman started work on his philosophical apologia, The Grammar of Assent. One argument in that book has had such an impact on modern thinking about evidence and probability that it was quoted in full by Bruno de Finetti in Volume 1 of his 1974 Theory of Probability.

Supposes a thesis (e.g. the guilt of an accused man) is supported by a great deal of circumstantial evidence of different forms, but in agreement with each other; then even if each piece of evidence is in itself insufficient to produce any strong belief, the thesis is decisively strengthened by their joint effect.

De Finetti set out the detailed mathematics and called this the Cardinal Newman principle. It is fundamental to the modern concept of borrowing strength.

The standard means of defeating governance are all well known to oligarchs, regulator capture, “stake-driving” – taking actions outside the oversight of governance that will not be undone without engaging the regulator in controversy, “whipsawing” – promising A that approval will be forthcoming from B while telling B that A has relied upon her anticipated, and surely “uncontroversial”, approval. There are plenty of others. Robert Caro’s biography The Power Broker: Robert Moses and the Fall of New York sets out the locus classicus.

Governance functions need to exploit the borrowing strength of diverse data sources to identify misreporting and misconduct. And continually improve how they do that. 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.

Things and actions are what they are and the consequences of them will be what they will be: why then should we desire to be deceived?

Bishop Joseph Butler

 

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

Toxic

Engine exhaust contrailsMuch in the UK press this week about alleged personal injuries from what has been described as “toxic air” in aircraft. Contamination of cabin air with, perhaps, organophosphates from the engines, either ambiently or during “fume events”, is alleged to cause ill health both in air crew and passengers. It seems that pre-action correspondence is being sent and litigation is afoot.

Of course, the issues, engineering, physiological and legal, are complex and await a proper forensic exploration. The courts are actually very good at this sort of thing as I shall go on to discuss below. However, the press coverage reminded me of one of the recurrent themes in this blog, trust in bureaucracy.

Trust

Part of the background to the litigation is found in the work of the Committee on Toxicity (“the CoT”). The CoT consists of working scientists who provide independent advice to the UK government. The CoT looked into the “toxic air” allegations. In their report, the CoT concede that the measurement systems for measuring cabin air quality are not entirely satisfactory. However, the CoT go on to arrive at the following conclusion as to ambient exposure;

For the types of aircraft studied, and in the absence of a major fume event, airborne concentrations of the pollutants that were measured in the study are likely to be very low (well below the levels that might cause symptoms) during most flights. The data do not rule out the possibility of higher concentrations on some flights … or of higher concentrations of other pollutants that were not measured.

— and for the “fume events”:

… the Committee considers that a toxic mechanism for the illness that has been reported in temporal relation to fume incidents is unlikely. Many different chemicals have been identified in the bleed air from aircraft engines, but to cause serious acute toxicity, they would have to occur at very much higher concentrations than have been found to date (although lower concentrations of some might cause an odour or minor irritation of the eyes or airways). Furthermore, the symptoms that have been reported following fume incidents have been wide-ranging (including headache, hot flushes, nausea, vomiting, chest pain, respiratory problems, dizziness and light-headedness), whereas toxic effects of chemicals tend to be more specific. However, uncertainties remain, and a toxic mechanism for symptoms cannot confidently be ruled out.

It’s not unusual for academics to be guarded if asked for an opinion and the CoT certainly don’t regard fume related injuries as impossible. However, having taken the matter as far as they are able with their resources, their honest opinion is that the reported symptoms were not caused by toxic fumes. I have not been able to find any fully argued study that says that they are. And yet, as the BBC points out, there are anecdotes that have to be considered against a background of data that, in itself, does not conclusively exclude the alleged symptoms. The matter is not quite closed but this turns out to be another issue beset with personal attitudes to evidence and risk.

Any lawyer has to be on the side of their client. However, when the BBC interviewed aviation lawyer Frank Cannon I think he went a little further than mere advocacy in his cause. He said:

If you look at the tobacco industry, the asbestos, contaminated blood issues, if you look at all that, the government say it’s perfectly safe, perfectly safe and then “wham”, they suddenly have to admit they got it wrong for so many years.

I am pretty sure that the UK government, at least, never advised that tobacco or asbestos was safe. William Cooke, the pathologist of Wigan infirmary, made arguably the first scientific report of lung disease caused by asbestos in 1924. There had been anecdotal evidence previously but Cooke’s was the first systematic analysis. Regulation and successful litigation soon followed. I am not aware of any serious body of scientific opinion ever saying that airborne asbestos exposure was safe after that point.

AsbestosCooke

As to smoking tobacco, the first statistical evidence associating smoking with cancer seems to have come in 1929 from Fritz Lickint. After Richard Doll’s work from the 1950s onwards I don’t think there was serious scientific dispute.

Of course, in the early years of the twentieth century life was comparatively unregulated. Though an absence of regulatory framework may now appear like a governmental endorsement that is to apply a very much post-World War II perspective. In any event, governments did respond with regulation, on both smoking and asbestos, even if its rigour is condemned by hindsight. The story of asbestos is a particularly tragic one. The story of contaminated blood is, I admit, more complex. I think it will make an edifying subject for a further blog.

The narrative of a callous, self-serving government bureaucracy only exposed by the heroic endeavours of maverick scientists is an attractive one to many people. Its prototype is Ibsen’s 1882 play An Enemy of the People. The twist in that drama is [spoiler alert!] that the population join the bureaucracy in turning against the scientist, whose credibility goes notably unchallenged by the author.

Attitudes to risk are entangled with emotional responses to broader cultural matters, as I blogged about here. That ecology of personal attitudes also feeds into how individuals react to the outputs of a bureaucracy, even one holding itself out as an exemplar of scientific objectivity, as I blogged about here. It is amid those conflicting cultural responses that forensic examination has a real part to play in resolving the conflicting doubts.

Forensics

Thereza Imanishi-Kari was a postdoctoral researcher in molecular biology at the Massachusetts Institute of Technology. In 1986 a co-worker raised inconsistencies in Imanishi-Kari’s earlier published work that led to allegations that she had fabricated results to validate publicly funded research. In his excellent 1998 book The Baltimore Case, Daniel Kevles details the growing intensity of the allegations against Imanishi-Kari over the following decade, involving the US Congress, the Office of Scientific Integrity and the FBI. Imanishi-Kari was ultimately exonerated by a departmental appeal board constituted of an eminent molecular biologist and two lawyers. The board allowed cross-examination of the relevant experts including those in statistics and document examination. It was that cross-examination that exposed the allegations as without foundation.

As eminent an engineer as George Stephenson found that he could not ask Parliament to approve the building of the Liverpool and Manchester Railway on the basis of faulty surveying that he had not properly supervised. After his cross-examination by Edward Hall Alderson he complained:

I was not long in the witness box before I began to wish for a hole to creep out at.

Certainly in England and Wales, expert evidence only provides guidelines within which the court makes its findings of fact. In the Canadian case of Reynolds v C.S.N. the learned judge, analysing whether a strike induced shut down at an aluminium facility had caused plant damage, disregarded the evidence of two statisticians, who could not agree how to calculate a Kaplan-Meier estimator, and preferred that of an engineer who had adopted a superficially less exact approach.

Process improvement

Though every branch of science has been advancing with sure and rapid strides, it is perhaps not too much to say that from the time of Lord Mansfield, and Folkes v Chadd, to the present; there has been a steady decrease in the credit awarded to the testimony of scientific witnesses.

Anonymous
“Expert testimony”
American Law Review (1870)

Throughout the nineteenth century the forensic evidence of scientific experts garnered a poor reputation. Robert Angus Smith, the discoverer of acid rain, refused to take expert work as he regarded it as corrupt beyond remedy and wished not to taint his reputation.

However, English law gradually drew the matter under supervision. The whole process by which English law adapted to embrace the conflicting evidence of specialists, woven through their respective esoteric expertise, is set out by Tal Golan in Chapter Three of his 2004 history of expert evidence, Laws of Men and Laws of Nature. Within the common law world, evaluation of expert evidence continues to evolve. The Australian courts have made important contributions with innovations such as hot tubbing. The common law courts have developed into a sophisticated forum for adjudicating on competing claims as to knowledge, not from an absolute standpoint, but from the pragmatic worldview of allocating resources. For practical people there has to be an end to every dispute.

The life of the law has not been logic; it has been experience… The law embodies the story of a nation’s development through many centuries, and it cannot be dealt with as if it contained only the axioms and corollaries of a book of mathematics.

Oliver Wendell Holmes
The Common Law (1881)

Do I have to be a scientist to assess food safety?

I saw this BBC item on the web before Christmas: Why are we more scared of raw egg than reheated rice? Just after Christmas seemed like a good time to blog about food safety. Actually, the link I followed asked Are some foods more dangerous that others? A question that has a really easy answer.

However, understanding the characteristic risks of various foods and how most safely to prepare them is less simple. Risk theorist John Adams draws a distinction between readily identified inherent and obvious risks, and risks that can only be perceived with the help of science. Food risks fall into the latter category. As far as I can see, “folk wisdom” is no reliable guide here, even partially. The BBC article refers to risks from rice, pasta and salad vegetables which are not obvious. At the same time, in the UK at least, the risk from raw eggs is very small.

Ironically, raw eggs are one food that springs readily to British people’s minds when food risk is raised, largely due to the folk memory of a high profile but ill thought out declaration by a government minister in the 1980s. This is an example of what Amos Tversky and Daniel Kahneman called an availability heuristic: If you can think of it, it must be important.

Food safety is an environment where an individual is best advised to follow the advice of scientists. We commonly receive this filtered, even if only for accessibility, through government agencies. That takes us back to the issue of trust in bureaucracy on which I have blogged before.

I wonder whether governments are in the best position to provide such advice. It is food suppliers who suffer from the public’s misallocated fears. The egg fiasco of the 1980s had a catastrophic effect on UK egg sales. All food suppliers have an interest in a market characterised by a perception that the products are safe. The food industry is also likely to be in the best position to know what is best practice, to improve such practice, to know how to communicate it to their customers, to tailor it to their products and to provide the effective behavioural “nudges” that promote safe handling. Consumers are likely to be cynical about governments, “one size fits all” advice and cycles of academic meta-analysis.

I think there are also lessons here for organisations. Some risks are assessed on the basis of scientific analysis. It is important that the prestige of that origin is communicated to all staff who will be involved in working with risk. The danger for any organisation is that an individual employee might make a reassessment based on local data and their own self-serving emotional response. As I have blogged before, some individuals have particular difficulty in aligning themselves with the wider organisation.

Of course, individuals must also be equipped with the means of detecting when the assumptions behind the science have been violated and initiating an agile escalation so that employee, customer and organisation can be protected while a reassessment is conducted. Social media provide new ways of sharing experience. I note from the BBC article that, in the UK at least, there is no real data on the origins of food poisoning outbreaks.

So the short answer to the question at the head of this blog still turns out to be “yes”. There are some things where we simply have to rely on science if we want to look after ourselves, our families and our employees.

But even scientists are limited by their own bounded rationality. Science is a work in progress. Using that science itself as a background against which to look for novel phenomena and neglected residual effects leverages that original risk analysis into a key tool in managing, improving and growing a business.

Richard Dawkins champions intelligent design (for business processes)

Richard Dawkins has recently had a couple of bad customer experiences. In each he was confronted with a system that seemed to him indifferent to his customer feedback. I sympathise with him on one matter but not the other. The two incidents do, in my mind, elucidate some important features of process discipline.

In the first, Dawkins spent a frustrating spell ordering a statement from his bank over the internet. He wanted to tell the bank about his experience and offer some suggestions for improvement, but he couldn’t find any means of channelling and communicating his feedback.

Embedding a business process in software will impose a rigid discipline on its operation. However, process discipline is not the same thing as process petrification. The design assumptions of any process include, or should include, the predicted range and variety of situations that the process is anticipated to encounter. We know that the bounded rationality of the designers will blind them to some of the situations that the process will subsequently confront in real world operation. There is no shame in that but the necessary adjunct is that, while the process is operated diligently as designed, data is accumulated on its performance and, in particular, on the customer’s experience. Once an economically opportune moment arrives (I have glossed over quote a bit there) the data can be reviewed, design assumptions challenged and redesign evaluated. Following redesign the process then embarks on another period of boring operation. The “boring” bit is essential to success. Perhaps I should say “mindful” rather than “boring” though I fear that does not really work with software.

Dawkins’ bank have missed an opportunity to listen to the voice of the customer. That weakens their competitive position. Ignorance cannot promote competitiveness. Any organisation that is not continually improving every process for planning, production and service (pace W Edwards Deming) faces the inevitable fact that its competitors will ultimately make such products and services obsolete. As Dawkins himself would appreciate, survival is not compulsory.

Dawkins’ second complaint was that security guards at a UK airport would not allow him to take a small jar of honey onto his flight because of a prohibition on liquids in the passenger cabin. Dawkins felt that the security guard should have displayed “common sense” and allowed it on board contrary to the black letter of the regulations. Dawkins protests against “rule-happy officials” and “bureaucratically imposed vexation”. Dawkins displays another failure of trust in bureaucracy. He simply would not believe that other people had studied the matter and come to a settled conclusion to protect his safety. It can hardly have been for the airport’s convenience. Dawkins was more persuaded by something he had read on the internet. He fell into the trap of thinking that What you see is all there is. I fear that Dawkins betrays his affinities with the cyclist on the railway crossing.

When we give somebody a process to operate we legitimately expect them to do so diligently and with self discipline. The risk of an operator departing from, adjusting or amending a process on the basis of novel local information is that, within the scope of the resources they have for taking that decision, there is no way of reliably incorporating the totality of assumptions and data on which the process design was predicated. Even were all the data available, when Dawkins talks of “common sense” he was demanding what Daniel Kahneman called System 2 thinking. Whenever we demand System 2 thinking ex tempore we are more likely to get System 1 and it is unlikely to perform effectively. The rationality of an individual operator in that moment is almost certainly more tightly bounded than that of the process designers.

In this particular case, any susceptibility of a security guard to depart from process would be exactly the behaviour that a terrorist might seek to exploit once aware of it.

Further, departures from process will have effects on the organisational system, upstream, downstream and collateral. Those related processes themselves rely on the operator’s predictable compliance. The consequence of ill discipline can be far reaching and unanticipated.

That is not to say that the security process was beyond improvement. In an effective process-oriented organisation, operating the process would be only one part of the security guard’s job. Part of the bargain for agreeing to the boring/ mindful diligent operation of the process is that part of work time is spent improving the process. That is something done offline, with colleagues, with the input of other parts of the organisation and with recognition of all the data including the voice of the customer.

Had he exercised the “common sense” Dawkins demanded, the security guard would have risked disciplinary action by his employers for serious misconduct. To some people, threats of sanctions appear at odds with engendering trust in an organisation’s process design and decision making. However, when we tell operators that something is important then fail to sanction others who ignore the process, we undermine the basis of the bond of trust with those that accepted our word and complied. Trust in the bureaucracy and sanctions for non-compliance are complementary elements of fostering process discipline. Both are essential.