In his recent article, David Green offers a simple, yet easily neglected reminder to those of us practicing people analytics: “Don’t forget the ‘H’ in HR”. In the article, Green addresses an ever-present issue in the world of people analytics – ethics. Surprisingly, Green cites that issues related to ethics and privacy puts 4 out of every 5 people analytics projects at risk. Green highlights several sources of potential challenges to ethical people analytics practices: legislative challenges, such as needing to comply with GDPR and other restrictions; technological challenges, such as rapid technological advancements that make data collection more widespread and unbeknownst to employees; and cultural challenges, such as effective use of data that maintains employee trust.
One important tension that Green raises, and which I believe is all too often overlooked, is how rapid technological advancement is changing the conversation around ethics. Green uses the infamous example of Amazon collecting employee data through “wearables”. Though Amazon claimed that the purpose of the wearables would be to collect data to improve well-being and productivity, the response by many was critical, raising concerns over “big brother” management. As technology outpaces our understanding of the implications of its use, we are faced with questions about whether the potential benefit is worth the risks. Similar questions are being asked in medicine and even warfare. Just because we can genetically modify an embryo, should we? Just because we can build and use nuclear weapons, should we? Though arguably these questions seem much more immediate and serious than those posed by the use of data in HR, people analytics involves people’s lives to no lesser an extent. Just because we are able to track every employees’ movement, should we? I think these questions are fundamentally about making a convincing case for the tangible insights and meaningful steps that can be gleaned from the collection and use of data.
Intrinsically linked with challenges involving data are those of culture. Employees have always been to some extent de-humanized. As Marx (1844/1964) said, “The devaluation of the world of men is in direct proportion to the increasing value of the world of things. Labor produces not only commodities; it produces itself and the worker as a commodity.” Being able to collect massive amounts of data on employees threatens any hope employees had of separating themselves from the machines that they fear will soon take over their jobs. That is, in the age of people analytics employees may become only data points, monitored and reprogrammed to maximize productivity and efficiency. Obviously, this raises concern and erodes trust. Employees need to be assured that their data is being used first and foremost to help them. This can be conveyed through messaging, as well as employees’ involvement in the process of data collection. Transparency and autonomy are key.
Green offers helpful recommendations for how to HR on how to maintain ethical people analytics practices. I think the most original recommendation is that of being open. Rather than people analytics remaining small and siloed, only for the benefit of few, it needs to be put in the hands of every employee. That is, employees need to be taught about their data footprint and have access to their own data. While to some this may seem like a radical approach, I think it is the only way to ensure an ethical and moral approach to people analytics. Organizations should not own the data that employees produce. If people analytics practices are truly for the benefit of employees, withholding their data from them is antithetical to this notion. Rather, generating insights should be an endeavor that employees have just as much stake in as those working in people analytics.