4 Ways HR Analytics Must Evolve for the Current Landscape

Image credit: iStockphoto/MARHARYTA MARKO

The COVID-19 pandemic and two years of disruptions that it has wrought have revealed the need to better leverage talent data and insights for cost-effective and high-impact management decisions and interventions. But an additional, largely unanticipated consideration in the use of that talent data is the degree to which traditional measures of the workforce’s health, engagement, and productivity are insufficient to make those sound, data-driven decisions. Because employees felt the disruptions of 2020 in highly differentiated ways, leaders who make decisions based on enterprise-wide averages are deploying blunt instruments against an extremely nuanced set of needs and priorities.

HR analytics leaders have a role to play in shaping leaders’ understanding of the employee landscape to enable incisive calls to action that support employees during times of uncertainty and in the future of work. Progressive HR analytics leaders are looking beyond the averages in four critical ways.

1. Find the Thrivers

Because disruption creates change, processes and environments that were optimized toward one group of employees will, by definition, be upended. But often lost in the concern for negatively impacted employees is the realization that the change may have resulted in an improvement for others. The upheaval of change and disruption does not create uniform losses, and the most progressive organizations seek to identify, understand and support those who are thriving in addition to those who are struggling.

2. Measure Change, Not Just a Point in Time

Our research has found that not only does disruption impact everyone differently but assumptions about who is coping well and who is struggling are often incorrect. Employees with the highest levels of workforce health (as measured by 16 indicators of individuals’ health, relationships and work environment) before the pandemic aren’t necessarily the ones who thrived or successfully coped with the disruption. So point-in-time data will tell you where people are now, but it will not tell you whether they have declined or improved against the metric as a result of disruption.

One of the most powerful approaches we have seen to better understand employee well-being is conducting longitudinal surveys: connecting predisruption data to postdisruption data and measuring the change to better understand the negative and positive impacts. Because it’s hard to know and design a survey before a disruption, these organizations use existing, predisruption data as the springboard for designing postdisruption surveys and metrics that can be retroactively aligned at the individual or team level. This allows an ad-hoc measure of change and obtains a much more insightful picture of the disruption’s impacts.

Tracking individual employees over time, which can be difficult, is not necessary to obtain this insight. Team-level longitudinal data can also provide a clear picture of changes in workforce health over time, even as teams change.

3. Get Curious About Team Resilience

Focusing on teams has other benefits as well. Traditional approaches to workforce resilience have emphasized building individual resilience or grit, but progressive leaders are seeing that individual solutions that depend on a person having a different “attitude” are expensive, riddled with exogenous factors, and ultimately ineffective.

Team-level resilience, by contrast, offers a much stronger path forward. HR analytics can help chart this course by identifying statistically significant team-level differentiators of resilience. These insights can aid in directing scalable investments and interventions that rely less on every employee being independently resilient and focus more on the team sharing the burden of organizational stressors. Additionally, a “team resilience” approach can spur solutions that enable team cohesion and unearth innovative ways of working in the new paradigm.

4. Be Sensitive to Signal Value

Time and again in our research, we find the impact of policies and decisions on workforce health has as much to do with their signal value to employees as with their direct impact on employees’ day-to-day work. For example, workforce health increases when an organization offers thoughtful and clearly defined benefits, even among employees who haven’t used those benefits. The signal value of an employee having the option to use a benefit is sometimes as powerful as availing oneself of it.

We see a similar effect in change communications: Even if employees disagree with a change the organization has made, if their voices have been heard in the decision making process, they are more accepting of it. The signal that leadership has taken their needs into account is meaningful, regardless of whether any given employee is happy with the outcome.

What this means for talent analytics is that as you collect and analyze data and relay your insights to leaders, it is important to recognize the signal that a data-driven decision may convey to employees. The data may imply one decision is right, but the signal value may be, in practice, all wrong.

For example, imagine that utilization data shows your organization is offering several voluntary benefits employees just aren’t using. The data suggests the organization could save some money by cutting these benefits, and only a few employees would miss them. However, cutting benefits amid disruption would send a negative message to employees about the organization’s financial health or its commitment to their well-being. The potential impact of that signal on workforce health, employee engagement, and retention, which the data didn’t capture, could potentially outweigh the savings. The organization might still make the change, but considering the signal value can help leaders time and communicate it more effectively to mitigate the potential downsides.

The context of the insight is as critical as the finding itself, and in times of disruption, employees are particularly sensitive to those signals. HR analytics leaders should be sensitive to them as well.

The original article is by Molly Tipps, Gartner's senior director for advisory. This article originally appeared in HR Leaders Monthly in Q3 2021. Download the full issue here.

The views and opinions expressed in this article are those of the author and do not necessarily reflect those of DigitalWorkforceTrends. Image credit: iStockphoto/MARHARYTA MARKO