Mind Metrics

Organisations have always measured things. Measures (or metrics) can tell businesses where they have come from, where they are now and where they might be going. They provide the ability to keep score, to warn of potential dangers and help scout out new opportunities.  The difficulty we can fall into is that we tend to think that once we have found value in metrics, then this continues as a straight line.  Surely if a measurement is a good thing, then more must lead to an abundance of positive outcomes?

This is not quite the case, largely because our measurement of the world is not neutral.  We like to think that measurement is a simple and objective means we use to track our environment.  But do we always stop to appreciate the way in which metrics are in danger of shaping the way we see the world?  And how they unintentionally shape the very thing we are trying to measure?  We need to understand the psychology of measurement to help us keep metrics in perspective.

Metrics shape the mind

To use an old phrase, when you carry a hammer, everything looks like a nail.  When we put metrics in place then the architects of the metrics will inevitably change the way they see the world.    Whilst this has always been the case to some degree, digital technology now means we are able to measure at greater scale (more people and situations) and scope (a much wider range of behaviours), this adage has much greater relevance.

Whilst this undoubtedly offers new insights, the problem this abundance brings is that we can easily think we have all the information we need in order to make business decisions.  However, decisions based on purely data-driven findings can fail to help us understand the real world, which is often ambiguous and ill-defined.

Psychologist Barry Schwartz talks about this [i] when he refers to ‘practical wisdom’: the way in which we use our humanity to judge what best to do in a situation. He uses the example of hospital janitors who, despite their job descriptions saying nothing about interactions with other people, often demonstrate great sensitivity to patients in the way they work.  It can be hard to generate KPIs that adequately reflect this sort of nuance.   Metrics are simply not always very good at picking up the very ‘human’ aspects of business which are often intangible, hard to define and even harder to measure.

Metrics are a starting point for managing a business rather than offering a dashboard with all we need to know.  This explains why so many senior business decision makers cite ‘gut feel’ as being so important.  In a recent study, 62% of senior executives say they often rely on gut feelings to make business decisions.  They understand that not everything can be captured and modelled from data to arrive at a decision.

Engineered behaviour

But there is another point about metrics we need to be wary of.  If we are being observed and measured then we change our behaviour.  For example, a study of Transport Security Administration (TSA) employees in the US examined their behaviour in an environment of significantly increased surveillance following the terrorist attack of 9/11. [ii] The TSA officers were reportedly acutely aware of being monitored which led them to engage in ‘invisibility practices’ to get some respite from these systems; they would go to the restroom much more frequently or take longer walking through unmonitored areas when in-between tasks.  But they also worked hard not to ‘stick out’ as individuals.  One officer said, ‘I would rather just do my job and go home, rather than be noticed a lot and…then maybe later get into trouble.’  This reflects the point that Philip K. Howard made when he argued that the overuse of metrics perpetuates a decline in trust so that ‘Officials no longer are allowed to act on their best judgement’ or to exercise discretion. [iii]

And as interactions and behaviours in work environments are increasingly technology led, then the temptation is ever stronger to limit the options available.  Brett Frisshmann and Evan Selinger discuss the way in which technology has increasingly engineered ‘techno-social’ environments so we are ‘nudged’ down certain paths without us fully exercising our judgement. [iv] The example they use is of the way in which we agree to contracts when we use a website. The techno-social environment is set up for us to simply click in agreement as it is too complex and difficult to do otherwise.  In their words, ‘the environment effectively programs human beings to behave like simple stimulus-response machines – perfectly rational, predictable and programmable.”

While this approach has obvious temptations, particularly in industries which have a history of poor decision making that had serious consequences.  Financial Services is the obvious example here where we are seeing ever more use of KPIs and technology to ‘engineer’ behaviours to try to manage risk.  The challenge of course, as we saw with Barry Schwartz’s hospital janitor example, is that employees need to operate in the real world, a world that is often ambiguous and ill-defined, with a context that will frequently change and as such, some level of autonomy and discretion is typically needed to ensure customers’ needs are best served.

In summary

There is no dispute that metrics help to facilitate the smooth running of any organisation.  The problem comes when the unintended psychological consequences of metrics are not considered. And whilst this is perhaps nothing new, the unprecedented degree to which digital technology can measure and engineer our work environments means that the psychological impacts of metrics now need to be given an equal weight to the measures themselves.


By Colin Strong

Want to read more?  Try the Tyranny of Metrics by Jerry Muller



[i] Schwartz, Barry, Practical Wisdom: The Right Way to Do the Right Thing, Riverhead Books, 2010.

[ii] Why Monitoring Your Employees’ Behavior Can Backfire: Anteby, Michel, Chan, Curtis K., Harvard Business Review, April 25th 2018

[iii] Howard, Philip K.: The Death of Common Sense: How Law Is Suffocating America. Random House, 2011

[iv] Frishmann, Brett & Selinger, Evan: Re-engineering Humanity, Cambridge University Press, 2018

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Colin Strong is Head of Behavioural Science at Ipsos. In his role he works with a wide range of brands and public sector organisations to combine market research with behavioural science, creating new and innovative solutions to long standing strategy and policy challenges. His career has been spent largely in market research, with much of it at GfK where he was MD of the UK Technology division. As such he has a focus on consulting on the way in which technology disrupts markets, creating new challenges and opportunities but also how customer data can be used to develop new techniques for consumer insights. Colin is author of Humanizing Big Data which sets out a new agenda for the way in which more value can be leveraged from the rapidly emerging data economy. Colin is a regular speaker and writer on the philosophy and practice of consumer insight.

Categories Big data, CX, Digital Transformation, Technology