Diversity & Inclusion

DEI for All: How Big Data Is Eliminating Bias in the Workplace

The term “shecession” started trending in April of this year because a majority of the jobs lost from the onset of the COVID-19 pandemic were held by women, and it was coined by C. Nicole Mason of the Institute for Women’s Policy Research (IWPR).


The phenomenon raises the question “Is there a bias in COVID-19 layoffs?” Market research shows the shecession is real; women have lost more jobs than men. The research further reveals that other minority segments of the workforce have also seen a greater impact. As the nation is focused on ensuring equity and driving out all forms of discrimination, the workplace must heed this call to action.

There is potential for perceived discrimination, which underscores the need for workforce reductions to be performed via unbiased, data-driven, performance-based analysis. However, most companies have zero visibility into the granular data around actual work performed by employees, rendering them vulnerable.

Workforce analytics are changing this paradigm by capturing actual work data. Such analytics help businesses make data-driven and unbiased workforce decisions to engender an inclusive culture and a progressive workplace.

COVID-19 Job Loss Impact Hits Harder for Some

According to the Pew Research Center in June, more women than men lost their jobs from February to May 2020—11.5 million vs. 9.0 million. The article went on to say, “… the COVID-19 downturn is the first of eight downturns in the past five decades in which women have lost more jobs than men.” The article also reports that Hispanic women, immigrants, young adults, and those with less education have been hardest hit by COVID-19 job losses.

What should organizations be doing to support their commitment to diversity and inclusion? In its repost “Women Matter: Ten years of insights on gender diversity,” McKinsey & Company cites a number of attributes key to forging an inclusive organization; these include:

  • Policies, rules, norms, and practices are constantly challenged to take into account the needs of all, not just one dominant group.
  • Meritocratic and fair. Processes are fair, and everyone is treated equally in settings free of bias.
  • The organization enables work/life balance, which means no more long hours and an understanding that performance is not linked to physical presence and time commitment.

Ushering in Unbiased Decision-Making and Uncovering Unintentional Bias in the Workplace

Action trumps philosophy. What is needed to drive bias out of the employee performance equation is the ability for companies to access data-driven insights that are completely removed from race, gender, age, etc. That is, companies need to deploy evidence-based talent-management strategies. Not only would this provide a sort of insurance plan for companies to defend against discrimination lawsuits, but  it would also ensure organizations’ people paradigm is 100% focused on unbiased, data-driven employee performance.

Many organizations have commitments to diversified and inclusive workplaces but unknowingly have work practices in place that impede the progress of these initiatives and undermine these commitments. Quantifying workforce data can uncover processes that foster unintentional biases.

For example, one major financial services company experienced a phenomenon whereby female employees in its trade reconciliation group were leaving their positions at significantly higher-than-average rates. Using workforce analytics, company management uncovered crucial data and identified work patterns showing that, while employees were expected to be in the office during typical hours, Monday through Friday, the nature of the work of reconciliation forced employees to work throughout the weekends. This imposed a work schedule that made it difficult to have any semblance of family life.

The insight the data revealed inspired the company’s leadership to rethink its rules of work engagement and to institute a new work schedule, with flex time and work-from-home options. As a result, the company was able to significantly lower the attrition rate of female employees in the group from 90% down to 3%. Workforce analytics insights helped uncover the root cause of why women were frustrated and fleeing; with these insights, the company was able to make changes to offer greater flexibility to reduce this frustration and retain this talent. 

Improving the Employee Experience and Identifying Employees at Risk

Promoting transparency of work patterns can aid organizations in becoming more progressive in making it fair for all to achieve. Workforce analytics can help companies put real substance behind their corporate objectives, including diversity and inclusion initiatives.

The technology also supports a greater understanding around the employee experience and key considerations around employee engagement and satisfaction by providing insights into when and where people are overwhelmed, frustrated, or dissatisfied with their work.

It can also reveal areas where employees are lacking training and coaching. In this regard, workforce analytics can provide vital data to help inform, direct, and bring about change in the organization to align work with employee needs. As data insights reveal trends of concern, companies can take action, intervening proactively to retain employees at risk.

Data are a powerful force to fuel business strategies. Now and in the post-COVID-19 landscape, organizations have a big opportunity to harness these data to give diversity and inclusion initiatives more substance and receive guidance to drive new progressive workforce strategies and/or make workforce reductions that are fair for all involved.

Brad Killinger is the CEO of Sapience Analytics, a vendor of knowledge workforce analytics solutions. Sapience Analytics’ technology is used by more than 200,000 users in over 90 enterprises across 18 countries to move the needle on employee engagement, organizational productivity, and business profitability.