Social science’s lessons for business

Big data is giving a soft science a hard edge, from which business can gain important insights — if those insights are properly put in context.

It isn’t often that I get to go to an “unconference,” where instead of formal sessions, participants pitch topics on the day of the event to come up with an agenda. And it isn’t often that I get to play rock, paper, scissors with psychologist and Nobel laureate Daniel Kahneman as a warm-up exercise. (I lost almost immediately.) But the most novel aspect of the Social Science Foo Camp, where all this took place, was the subject: the implications of data and social science for business and society.

I came to the camp to look at how some of the ideas in social science are already translating into business, and also to see what organizational changemakers can learn from the emerging community of big-data scientists and social science researchers.

Tim O’Reilly, the activist and writer who pioneered tech community gatherings such as the O’Reilly Open Source Software Conference (OSCON), in 1999, recognized the impact of the new discipline of computational social science early. This second Foo Camp (the name Foo comes from Friend of O’Reilly), hosted in February at Facebook’s headquarters in Menlo Park, Calif., is the result of a four-way collaboration between O’Reilly Media Inc., Sage Publications Inc., The Alfred P. Sloan Foundation, and Facebook.

As O’Reilly put it to me, “the social sciences are just waking up to be a really hard science,” and he has a point. This is partly to do with scale, something that computational data is transforming. But the takeaway from Social Science Foo is that hard data is only valid if placed in a highly human context: why we do what we do, and how social science can inform different kinds of decisions.

The takeaway from Social Science Foo is that hard data is only valid if placed in a highly human context.

Presentations and discussions ranged from the eye-opening — University of California, Berkeley, psychologist Alison Gopnik extolling the merits of mind-altering psychedelics — to the downright funny: The bodily functions of termites are hilariously disgusting, but their organizational skills are impressive and worthy of study.

I should not have been surprised that these social insects have something to teach us, as I spend a lot of my time researching bee behavior, specifically how the organizational design of hexagonal hives and the social signals developed by bees can inform better-managed companies. Writer Lisa Margonelli’s research, covered in her unlikely page-turner, Underbug: An Obsessive Tale of Termites and Technology, was revealing: It turns out that there is a cognitive system at work in microbial ecology, which could turn on its head the idea that these behaviors are programmed into individual organisms and genes. What this means is that the unbelievably productive activity of termites — their mounds are feats of structural engineering that dwarf what’s seen in any comparable human endeavor — can be considered less as a robotic enactment of genetic code and more as an actual purposeful system, that, as in bees, works for maximum efficiency for the most numbers. Architects and managers can and should learn much from their success.

The work of Jet Sanders, a fellow from the London School of Economics and Political Science, on behavioral risk as it relates to the working week, could have potentially useful insights for business. It turns out that risk tolerance decreases markedly from Monday to Thursday, before rising on Friday. Sanders’s research focuses on political risk in electorates, noting that “every U.K. election has taken place on a Thursday since 1935, the most cautious day of the week.” But the data also may help explain why “Blue Monday” has become recognized as the time on the calendar when workplace performance is depressed, and why Mondays turn out to have the highest incidence of missed medical appointments. These findings call for more research to see if there are potential links to business strategies and investment decisions in which knowing a psychological predisposition for certain choices might mitigate potential disasters or help avoid missed opportunities.

But the deepening relationship between the social sciences and big data is not just about behavioral insight, crucial though that is. It is about the sheer scale of the information that massive data sets can bring to understanding human behavior. Take, for example, Elizabeth Bruch of the University of Michigan, who wants to understand how humans fall in love, and specifically how and why it might differ depending on aspirations and geographic locations. Bruch and her coauthor, Mark Newman, use complex systems mapping of data sets from online dating companies, which she says opens a game-changing “window” into dating strategies. People, it seems, are mostly looking for mates that are considered more attractive than they are (based on a range of attributes, not just looks, ranked in a hierarchy of desirability), which often leads to disappointment. It’s not a stretch to think that the algorithm Bruch and Newman have developed in the course of their research might have insights for those looking for jobs, too.

Back to Kahneman. In The Undoing Project, author Michael Lewis described the significance of the psychologist’s work with Amos Tversky on how people make decisions and why they err in making “misjudgements that can be exploited for profit by others who ignored the experts and relied on data.” I would say that idea perfectly captures the tension inherent in a conference such as Social Science Foo, and why I would go again in a heartbeat.

Julia Hobsbawm

Julia Hobsbawm is an honorary visiting professor of workplace social health at London’s Cass Business School and the founder of the consultancy Social Health Expert. Her new book, The Simplicity Principle, will be published by Kogan Page in 2020.

 

 
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