Putting Dignity at the Core of Employee Data Use

When companies manage employee data responsibly, they’re better able to grow trust while gaining insights.

Reading Time: 10 min 

Topics

Developing an Ethical Technology Mindset

The demands of a digitized workforce put transparency, ethics, and fairness at the top of executive agendas. This MIT SMR Executive Guide explores how managers and organizations can apply principles of ethical and trustworthy technology in engaging with customers, employees, and other stakeholders.

Brought to you by

Deloitte
More in this series
Buy
Already a member?
Not a member?
Sign up today
Member
Free

5 free articles per month, $6.95/article thereafter, free newsletter.

Subscribe
$75/Year

Unlimited digital content, quarterly magazine, free newsletter, entire archive.

Sign me up

Image courtesy of Laura Wentzel

We suspect that few leaders appreciate the diversity and volume of data about employees that their organizations are amassing from sources ranging from digital collaboration platforms to workforce wearables and mobile devices. Even throughout the pandemic, the scope and nature of employee data has expanded rapidly to include vaccination status, the results from frequent health checks, virtual meeting behaviors, and work-life survey results.

At most large global firms, people and workforce analytics are mainstream initiatives led by HR leaders. But increasingly, employee data is being used in new ways, beyond HR, to produce lucrative results. For example, one organization analyzed employee activity and building characteristics to generate insights about occupancy in its facilities, which ultimately saved the organization millions of dollars in reduced heating and cooling costs.

At the MIT Center for Information Systems Research (CISR), we recently studied how innovative uses of employee data by organizations can both support and threaten the security of employee dignity.1 Particularly in digital transformation contexts, employee behaviors and knowledge are key to understanding how an organization has historically operated. This understanding can expose opportunities for improvement and lead to unanticipated outcomes when the organization decides to radically alter or eradicate certain work tasks. Such uses of the data can cause tensions and be fraught with complex ethical concerns.

Organizations may be tempted to govern employee data by relying on regulations rooted in personal data privacy and protection, such as the European Union’s General Data Protection Regulation and the Health Insurance Portability and Accountability Act in the U.S. But such laws fall short when it comes to the ethical oversight of employee data use. For one thing, employee data that informs and improves a company’s core operations can be exempt from regulatory constraints. Also, MIT CISR research has shown that a regulatory-based perspective is not broad or deep enough to comprehensively oversee the internal and external use of people data; companies need a capability known as acceptable data use (ADU) that includes legal, regulatory, and ethical oversight practices.2 ADU moves beyond regulation to offer ethical oversight by considering the expectations and desires of the organization and key stakeholders, including employees.

A regulatory-based perspective is not broad or deep enough to comprehensively oversee the internal and external use of people data.

Read the Full Article

Topics

Developing an Ethical Technology Mindset

The demands of a digitized workforce put transparency, ethics, and fairness at the top of executive agendas. This MIT SMR Executive Guide explores how managers and organizations can apply principles of ethical and trustworthy technology in engaging with customers, employees, and other stakeholders.

Brought to you by

Deloitte
More in this series

References

1. In 2019-2020, MIT CISR researchers conducted 100 interviews with the participants of 52 distinct AI projects at 48 companies. In 2021, the authors reviewed 22 of the projects that demonstrated significant use of employee data and analyzed them using a lens of human dignity.

2. B.H. Wixom and M.L. Markus, “To Develop Acceptable Data Use, Build Company Norms,” MIT Sloan CISR Research Briefing XVII-4, April 2017, https://cisr.mit.edu.

3. D.E. Leidner and O. Tona, “The CARE Theory of Dignity and Personal Data Digitalization,” MIS Quarterly 45, no. 1 (March 2021): 343-370.

4. B.H. Wixom, I.A. Someh, and C.M. Beath, “GE’s Environment, Health, and Safety Team Creates Value Using Machine Learning,” working paper 448, MIT Sloan CISR, Cambridge, Massachusetts, November 2020.

5. Leidner and Tona, “The CARE Theory.”

Reprint #:

63215

More Like This

Add a comment

You must to post a comment.

First time here? Sign up for a free account: Comment on articles and get access to many more articles.