Organizations employ analytics to improve productivity. However, in measuring existing performance, analytics may be creating a less welcomed byproduct in the workplace – accountability.
Greater accountability, tends to make people nervous and this may be among the main reasons why some workplaces are hesitant to adopt analytics initiatives, according to Michael Schrage, a research fellow at the Massachusetts Institute of Technology Sloan School’s Centre for Digital Studies.
“The more data organizations gather from more sources and algorithmically analyze, the more individuals, managers and executives become accountable for any unpleasant surprises and/or inefficiencies that emerge,” he wrote in a bog post for the Harvard Business Review.
He calls the phenomenon “accountability creep.”
It’s an interesting point of view on the impact that big data and analytics on the modern workplace.
For example, he said, a supply chain manager might find that an inexpensive subassembly he purchased could lead to very expensive in-field repairs. Engineering design and test should be held accountable, Schrage said, but data driven analytics makes the employee responsible as well.
Schrage said in one global technology firm, salespeople were furious with a customer relations management system with an analytics feature that held them accountable for pricing and promotion practices which they thought undermined their relationship with their key clients. The real-time analytics feature held them more accountable but also gave them less flexibility.
Schrage argues that most serious obstacles to big data and analytics initiatives “tend to have less to do with real quantitative or technical competence than perceived professional vulnerability.”
Unfortunately, in some organizations, this leads to a two-tiered accountability environment, where executives employ analytics to impose analytics on employees but not on themselves, said Schrage.