By Martha Poon

It sounds like the beginning of a groan-inducing Dad joke – What do insurance salesmen, mortgage brokers and Amazon pickers have in common?

Answer: They all translate the results of data crunching into transactions.

A business can make lots of one-sided calculations, but it takes something more to get the world to respond to the messages construed by numbers. From targeted data-driven advertising to complex financial structuring, getting numbers to bear out in practice leaves many a professional head-scratching.

In her paper, ‘A ‘good, average man’‘, historical sociologist Liz McFall offers a compelling account of how and when calculation matters in consumer markets. McFall’s aim “is to show that mathematical argument, whether competent or incompetent, could never be sufficient by itself to foster […] markets”.

McFall demonstrates that for industrial insurance companies to establish mass consumer markets in the nineteenth century, actuaries had to do more than accurately predict population patterns. To transform the numbers into policies, old-fashioned actuarial science had to be supported by a fleet of field specialists.  This is why the insurance industry deployed those iconic men in hats and suits who only disappeared from the streets of Britain in 2001.

The job of the familiar man from the Prudential, McFall explains, was to mediate between the statistical predictions of nerdy actuaries and the passions of everyday working class folk who would have to consistently deliver a few pennies per week in premiums for the business to succeed. Door-to-door salesmen and premium collectors brought a statistical concept to life.  They personified the reliable ‘average man’ upon whom, by emulation, the insurance industry was built.

McFall’s case study has broad implications. She demonstrates that two-dimensional symbolic calculations do not instantly become lived economic realities.

(The shelvers and pickers who move goods in and out of Amazon’s distribution warehouse according to the instructions of optimization algorithms are another example of how labor must relentlessly assists helpless calculations, locked in machines, to control three-dimensional systems.)

Who would have thought the lessons from industrial insurance could be so germane today? For her attentiveness to methodological detail, theoretical robustness and beautiful writing McFall‘s paper was duly awarded The Sociological Review Prize this May. Alongside articles like Mackenzie’s ‘An equation in its world‘ (2003) or Callon and Muniesa’s ‘Economic markets as calculative collective devices‘ (2005), ‘A ’good, average man” (2011) is essential reading for social scientists interested in how calculation makes markets.

Acknowledgements

This article was originally posted on Socializing Finance.