Despite leading companies making substantial progress, in the aggregate, women continue to face significant barriers at work, with far fewer women than men in senior positions, pay that continues to lag men’s, and evidence that, far from getting better, the economic gender gap is actually getting worse.

Despite these challenges, organizations have at their disposal a powerful tool for accelerating women’s progress – data and analytics.

Every organization with a human resource information system (HRIS) has the ability to analyze how its people move into, through and out of the organization over time. There is a wealth of information contained in these systems that track the running record of experiences that all employees – the internal labor market of both women and men – go through, and the career outcomes they realize (or not). This makes it possible to uncover root causes, the stumbling blocks that are hindering women’s progress in that particular organization.

An analytical approach can also identify accelerators of advancement, such as key roles and sequences of assignments that are gateways to the fast lane. Analytics is also the key to identifying and moving women into the jobs of the future. As organizations are looking to workforce data to help hedge against disruption and prepare for future jobs that may not yet exist today, it is particularly critical to look that the right female talent is not left behind.”

So how can employers harness the power of data and analytics to accelerate women’s careers?

1. Start now

Don’t wait for “perfect” data about your employees. Work with what you have – and with experts as needed – to navigate any gaps and size their impact. Then you can formulate a plan for what’s possible now versus what should be part of your future road map.

2. Find out what drives career advancement in your organization

Analyzing workforce data and applying predictive modeling can help organizations learn which career experiences are most important to advancement – and ensure that women and key minority groups have equal access to those experiences.

For example, we worked with an organization that wanted to identify and address the blockages preventing women and minorities from progressing upwards more quickly. By applying statistical modeling to their workforce data, we discovered that holding a team leader position was one of the top predictors of near-term upward advancement – and found that women were far less likely than men to hold these roles. We also found that although women tended to receive higher “leadership potential” ratings than men, they were still less likely to be promoted than men were.

Armed with these insights, the company took swift action to replace its biased performance management and leadership evaluation system. It also began better tracking the flow of different workforce demographics into key positions like the team leader role. These actions enabled the company to double the percentage of women in director and above roles over a five-year period.

3. Prepare for job disruption by uncovering alternate career pathways

The Fourth Industrial Revolution is bringing new technologies that will eliminate or transform some jobs while creating others. This disruption is predicted to have a disproportionate impact on women, potentially reversing their progress in the workplace.

Analytics can help organizations size the likely impact of emerging technologies on their workforce and recalculate career pathways so that women and others can be optimally redeployed. For example, in analyzing a global hardware company’s workforce data, we found that women not only made up a mere fifth of its sales operation, but also were three times more likely than men to hold positions – like administrative assistant and market intelligence worker – at high risk of automation or computerization. Unless the company figured out how to reskill and redeploy the people in these jobs, female representation would likely fall further.

By linking the company’s workforce data to an extensive and external skills database, we were able to assess how similar jobs were to one another. This helped us identify pathways to alternate positions – even those in different job families – that require similar skills as those most likely to be eliminated.

4. Identify reskilling opportunities

Even when companies identify alternate jobs requiring similar skills, there will most certainly be some differences in the skills required. Analytics can help organizations quickly identify those differences so they can efficiently reskill and redeploy. This is a critical step to countering the headwinds that may work against the progress of increasing representation of women in organizations, as the impact of technology is likely to displace jobs where women have higher representation (see

After identifying alternate positions for the global hardware company described above, we quantified the skills required for the current position and for potential alternate positions across 20 broad dimensions. This made it easy to pinpoint skill gaps and the type of developmental support that would be required for individuals making these moves.

Companies that create a culture of continuous learning and foster learning agility among their workers will be more readily able to reskill and redeploy female (and male) talent.

By making an investment in leveraging its own workforce data and advanced analytics, any organization can make meaningful and measurable progress on advancing women. The result will be an organization better able to realize the value of its female workforce and better prepared for the future – a powerful combination.