Issue No. 02 | The People Analytics Capability Gap: Why Tools and Data Aren’t Enough
Organizational leaders have invested significantly in human resources technology, data platforms, dashboards, and increasingly sophisticated analytical tools. The promise is compelling: better workforce data should lead to better insights, better decisions, and ultimately better organizational outcomes.
But there is an important distinction between having people analytics resources and possessing a true people analytics capability.
An organization can have sophisticated technology, large volumes of workforce data, talented analysts, and polished dashboards, and yet still struggle to translate analytics into meaningful business value.
That gap raises an important question:
“What does an organization actually need to do people analytics well?”
Looking Beyond the Technology
People analytics is sometimes approached primarily as a technology or data challenge. Organizational leaders ask whether they have the right HR platform, visualization tools, artificial intelligence capabilities, or access to sufficient data.
Those questions matter. But they may be incomplete.
Technology can make analysis possible. Data can make analysis informative. However, neither guarantees that an organization will ask the right questions, interpret the results appropriately, or use those insights to improve organizational decisions.
A more useful way to think about people analytics may therefore be as an organizational capability; one that depends on multiple resources and competencies working together.
In an independent research study conducted by Demetrius R. Allen, PhD, President and Principal Consultant of Blue Psynergy Consulting, and Katherine Kimiko Davis, PhD of Kanji Consulting, we examined several dimensions that may contribute to an organization’s people analytics capability.
These included:
- Analytical Skills. The ability to conduct, interpret, and apply analytical methods to workforce questions.
- People/HR Data Quality. The accuracy, completeness, consistency, and timeliness of workforce data used for analysis and decision-making.
- Domain Knowledge. Understanding the organizational, workforce, and business context needed to interpret analytics meaningfully.
- Data Bigness. The volume, variety, and breadth of workforce-related data available for analysis.
- Tool Sophistication. The breadth and depth of analytical platforms, visualization systems, and advanced analytical technologies available to support workforce decision-making.
The initial study also examined Decision Quality and Decision Efficiency as dimensions of the broader people analytics capability construct.
Taken together, these dimensions suggest something important: people analytics may be less about any single resource and more about the organization’s ability to coordinate multiple resources effectively.
The Capability Gap
Consider an organization where leaders have invested heavily in analytics technology but continue to struggle with inconsistent workforce data.
Or an organization with high-quality data and technically sophisticated analysts who lack sufficient understanding of the business context behind the questions they are attempting to answer.
Or perhaps an organization where analysts produce strong analytics, but those insights rarely influence consequential decisions.
In each case, leaders can legitimately say that their organization “does people analytics.”
Yet the ability to create value from those analytics may remain limited.
This is what we describe as the people analytics capability gap: the distance between possessing analytics resources and developing the organizational capability to convert those resources into useful insight and better decisions.
That distinction becomes increasingly important as organizations invest in artificial intelligence and other advanced analytical technologies.
More sophisticated tools can increase what an organization is capable of analyzing. But technological capability should not be confused with organizational capability.
An advanced analytical model operating on unreliable data does not become useful simply because the model is sophisticated. Likewise, an accurate analysis that never meaningfully influences an organizational decision creates limited strategic value.
What Our Initial Research Suggests
Our exploratory study examined relationships between seven dimensions of People Analytics Capabilities and multidimensional organizational performance among professionals actively engaged in people analytics work.
The findings should be interpreted cautiously.
The final study sample was relatively small (N = 40), the research used a cross-sectional design, and the findings have not undergone peer review. They should therefore be viewed as preliminary empirical evidence rather than definitive or causal conclusions.
Even with those limitations, the pattern of findings was noteworthy.
Six of the seven people analytics capability dimensions demonstrated statistically significant positive relationships with overall organizational performance when examined individually. Tool Sophistication was the exception.
The dimensions were also substantially related to one another, suggesting considerable overlap among the capabilities.
When all seven dimensions were examined together, the overall model significantly predicted organizational performance. However, only two dimensions – Data Bigness and Decision Efficiency – emerged as statistically significant unique predictors within the full model.
These findings do not establish that technology is unimportant, nor do they identify a single capability that organizations should prioritize above all others.
Instead, these findings raise a potentially more consequential possibility:
The value of people analytics may emerge from the coordinated use of multiple, overlapping capabilities rather than from isolated investments in any one of them.
From Resources to Capability
That possibility has practical implications. Organizational leaders assessing the maturity or effectiveness of their people analytics functions may need to look beyond inventories of software, dashboards, data assets, and technical skills.
The more useful assessment may be whether the broader analytics system is working.
Are the data trustworthy?
Do analysts possess the necessary technical capabilities?
Do analysts understand the organizational context behind the questions?
Can available technologies support the analyses organizational leaders need?
Are analytical insights incorporated into organizational decision-making?
And ultimately, are the organizational leaders becoming better at using workforce evidence to make consequential decisions?
These questions move people analytics away from being primarily a reporting or technology function and toward something more strategically consequential: an organizational capability for converting workforce information into better decisions.
The question isn’t simply whether your organization has people analytics. The question is whether it has developed the capabilities necessary to make people analytics valuable.
In the next Intelligence Brief, we’ll examine what our preliminary findings may tell us about how these capabilities work together, and why organizational decision-making could represent a critical link between people analytics and organizational performance.