By Gordon Hull
At the end of my time in high school, I worked part-time bagging groceries. There was some modest union influence on the job, and its scheduling was pretty predictable: the longer you’d been there, the better schedule you’d get. Your first few weeks, you knew you’d be working late into the evening, especially on Friday and Saturday. After a while, the late shifts would taper off as somebody newer than you would get slotted into them. You could depend on a pretty predictable schedule week-in and week-out. It was a service sector job with a factory-like scheduling.
I mention this because one of the more nefarious uses of big data got emphasized last week in the context of discussion Black Friday’s steady march backwards into Thanksgiving day. Last week’s news highlighted one way that data analytics can be used to introduce further precarity into the lives of low-wage workers. The transfer of risk and precarity to employees more generally is of course something neoliberalism does pretty well, but the process is even more intense for low-wage workers due to the introduction of scheduling software that produces unsteady, uneven, just-in-time scheduling, so that employers don’t have to pay for employees who aren’t absolutely necessary. Since a disproportionate number of those affected by these programs have children to care for, and since many of them are minorities, it’s also a case of disparate impact on poor, minority women. As stores open earlier and earlier for Black Friday, more and more workers – again, mostly women – are being put into the position of not knowing whether they’ll have Thanksgiving off until a day or two before. It’s a good example of the general problem.

