How genuinely scientific is ‘scientific’ management?

As my last few posts have described (for example), viagra sale management researchers can harness positive perceptions of science to give their findings greater intellectual standing without adopting the requisite rigour.  In the same way, impotent the adjective ‘scientific’ is frequently prefixed to management as a signifier of merit – the right way to manage.   Scientific management has been around for over a century, its father being Frederick Winslow Taylor, who set up a consulting practice to spread his ideas about manufacturing efficiency in the last decade of the 19th Century.

Since Taylor’s time, the idea that scientific management is better than “gut instinct” decision-making has gained momentum1.   In The Lords of Strategy, Walter Kiechel describes this as the coming of “Greater Taylorism, the corporation’s application of sharp-pencilled analytics…to the totality of its functions and processes.” 2  With the most vocal proponents often being Kiechel’s “Lords of Strategy” – consultancies with much to gain from the implementation of what they believe scientific management practices to be.

Self-interested promotion, of itself, is not a basis for rejecting ideas.  But given how readily ‘science’ is cited as validation, and often incorrectly – typically by those with no appreciation of what the scientific approach actually entails – the purported superiority of scientific management does raise a couple of questions.  Firstly how genuinely scientific is scientific management?  And secondly how scientific is the justification for it?

Regarding the first question, the origins of scientific management do not provide an auspicious start for a positive response.  When Taylor was contracted to Bethlehem Steel Company, he conducted experiments to estimate how much iron could be loaded onto rail trucks by the predominantly Hungarian workforce.  The figure he landed upon was 47.5 pig tons per day.  But the biggest factor in calculating this target was the 40% ‘adjustment’ applied to the figure he had calculated by extrapolating a sample period of 14 minutes to a full work day.  Time obviously needed to be allowed for lavatory breaks, rests and meals, but the only justification he could provide, when asked, for the figure of 40% was his judgement and experience – exactly the sort of intuitions that scientific management was meant to replace.  As Matthew Stewart, author of The Management Myth, has argued:  “Why time a bunch of Hungarians down to the second if you’re going to daub the results with such a great blob of fudge?”3

Taylor wrote a complete book on the principles of scientific management and much of what he advocated is now standard rather than scientific practice.  In modern parlance, scientific management has come to mean fact-based or data-driven (algorithmic, even) decision making based on the information and performance measures culled from the enterprise systems a business has. But while evidence is obviously necessary to the scientific method, it is not sufficient.  In addition there needs to be the systematic creation of new hypotheses and their testing, the results of which add to an ever-increasing body of understanding.  But this test seldom seems to be applied with scientific management.

In part this omission stems from science and management having fundamentally different objectives – scientists seek to increase knowledge while managers seek to increase profits.  The two are not incompatible; increased knowledge often leads to increased profitability.  And if a business was focused on systematically increasing insight with the intention of translating this into higher revenues and higher profit margins – increased insight being the objective with increased profits being the outcome – the ‘scientific’ tag would be genuinely merited.

This may seem a minor distinction but it requires a fundamental change in attitude, particularly towards experimentation.  Experiments test what works and, more critically, what doesn’t.  When strictly applied, the scientific approach focuses on refutation on the basis it is easier to prove a negative than a positive.  In this way knowledge advances through the elimination of bad theories and ideas.  Such an attitude does not come naturally to most people – we are programmed to be confirmation-seeking rather than the opposite – particularly not to business people.

Experimentation requires doing something in a way that is not optimal according to our current understanding.  That does not sit well with a business ethos that is focused on short-term optimisation.  Also it requires accepting that current assumptions may be incorrect – never easy for people who have invested heavily in beliefs based on those assumptions.  Equally it will require treating people – staff, customers, suppliers – differently, so that a proposition can be tested with a sample population against a control group.  This contravenes our natural sense of fairness – some people will be treated worse than they might otherwise have been.  In advance we don’t know which group that will be (though a hypothesis should exist), but we do know that, by definition, some people will be disadvantaged relative to others.   And while it is easy to pay lip service to the idea that in the long term everyone should benefit from the knowledge gained, these benefits appear distant and abstract compared to the short term and concrete discomfort that comes from violating accepted norms.

Ultimately what is called scientific management is, though not cod-science, at least a low-calorie or diet version – science light, perhaps.  Which leads to the second question, how scientific is the basis for asserting the superiority of scientific management over intuition?  Have companies been assessed and split into two (or more) groups and their performance assessed?  If so, how have they been split?  How has relative performance been assessed – over what periods; as part as a live study or retrospectively?  There is no doubt that many companies that have been run on what would be described as a highly scientific basis have suffered a marked decline in fortunes (GM, indeed most of the US automotive industry springs to mind) or failed completely while some that have been run intuitively (Apple, for example) have been highly successful; how are these accounted for?  Is the failure of the first seen as poor execution of the scientific principle (rather than a reflection on the principle itself) while the latter are just lucky?

Studies that purport to measure the benefits of scientific management generally compare whether certain metrics are tracked and performance on those metrics.  To obtain a statistically significant sample, these studies are heavily reliant on self-assessment.  As outlined in the previous post on bias in management research, this introduces significant scope for distortion, calling the validity of any such findings into question.

The reason for such scepticism is that, by definition, it is not possible to be scientific about some of the decisions a business must make, specifically the long-term strategic ones.  With operational decisions, there is a wealth of relevant data and it is reasonable to assume that the period from which the data is collected accurately depicts the future period over which the decision’s impact will be felt.  In such a context, it is possible to make ‘fact-based’ decisions; and likely that those decisions will be superior to those that just rely on instinct and experience.

The problem is that there are no facts about the future, only predictions based on assumptions or intuitions.  These predictions may be dressed up in the finery of a complicated model and comport themselves as if they were facts, but ultimately they are just formalised intuitions.  Any decision about the medium to long term future, by definition, involves intuition.  The danger with scientific management is that this is not recognised, that the structured and systematic approaches used to make predictions and decisions based on those predictions ignores how fundamentally assumptive the foundations of the whole process are.

The result is that confidence is increased by more than accuracy – a confidence trick played on managers by themselves (abetted by their advisers) to justify what their intuitions suggest.   As to the damage this causes, study after study for the past thirty years has found that acquisitions destroy value for the acquiring company in the majority of cases (the most recent estimate I have seen being 70-90% of the time).

1 For example, in 2007 McKinsey published its report ‘Ten trends shaping the future corporate landscape’ and trend number nine was ‘management will go from art to science’.  See Scientific management is past its peak; by Roger Martin; Businessweek, 21 May 2007 for a gentle lampooning of this idea

2 The Lords of Strategy: The Secret Intellectual History of the New Corporate World; by Walter Kiechel, Harvard Business Press, 2010

3 The Management Myth, by Matthew Stewart, The Atlantic Magazine, June 2006

Elusive Growth: Why prevailing practices in strategy, marketing and management education are the problem, not the solution, by Jack Springman, will be published in Summer 2011

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About Jack Springman

I am a consultant with experience in business strategy and customer strategy development, customer management and customer service transformation.