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6 steps to ethically sound people analytics

Source | | Dirk Petersen

In late July 2017, a Who’s Who of Silicon Valley people analytics leaders came together at Intel. No one foresaw that Cambridge Analytica would soon raise the profile of data ethics to a new level of urgency. In fact, the leaders that day confirmed what similar groups had found at meetings earlier that month in London (hosted by Cisco), Amsterdam (ABN AMRO), and New York (Pfizer): people data ethics is important, but it’s not urgent.

At that Intel meeting, the people analytics leaders from 55 companies came to the realisation that people data ethics is important, because of its foundational impact on people analytics success. No organisation can build a sustainable, successful people analytics function without clear understanding of what it should and shouldn’t do. Data ethics, participants realised, is the compass for all analytics work.

An Insight222 survey with 57 companies* shows the extent of the challenge: 81% of companies report that their workforce analytics projects were sometimes or often jeopardised by data ethics/privacy concerns.

Even the most sophisticated companies face challenges in this area: project delays because of uncertainty whether the data gathered complies with GDPR; projects cancelled because works councils are not on board; analyses weakened because of lack of alignment among company leadership on whether ‘it’s ok’ to run certain algorithms. Those who’ve worked for some time in this field will recognise (and have likely faced) all these issues.

No Data Ethics, No Sustainable Analytics Value

Data ethics uncertainty partly explains why so many companies struggle to show tangible value from their data analytics work. In our conversations with well over 100 of the Fortune 500 companies, a consistent feature was the difficulty people analytics leaders face in showing real value.

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