Get the Human Back in HR Data

Why Leadership Development Needs More Than Metrics

In today’s increasingly data-driven business world, human resources (HR) departments have become flush with metrics. Engagement scores, turnover ratios, time-to-hire, absenteeism rates, 360-degree feedback dashboards, and sentiment analyses all claim to offer insights into organizational health and leadership effectiveness. With powerful software tools and AI-driven analytics platforms, companies can now extract detailed reports and heat-maps pinpointing engagement patterns, culture trends, and competency gaps across teams.

Yet despite this wealth of quantitative data, many organizations still find themselves blindsided by leadership failures. It's not uncommon for engagement surveys to return glowing results, while underneath, significant cultural or interpersonal problems are festering. Leaders who score high on digital dashboards may be misaligned with the values of the organization, undercutting trust, or subtly stifling engagement and innovation through their style or behavior.

This calls for a fundamental rethink: it’s time to get the human back in HR data.

The Illusion of Insight: When Data Isn’t Enough

Imagine a manager who consistently receives high engagement scores from their team. On paper, this leader is succeeding, hitting all set goals. However, exit interviews and one-on-one coaching sessions reveal a different story: team members felt pressured to conform, experienced psychological safety issues, and avoided offering critical feedback. The manager’s style created a performance-through-fear culture masked by short-term compliance and surface-level positivity.

This is not a rare case. Take, for example, the case of Wells Fargo in the mid-2010s. Employees consistently reported high engagement and performance metrics, but only later did it emerge that many were pressured into unethical practices to meet targets. The leadership style that encouraged over-performance created a toxic culture hidden beneath the data. (Source: The New York Times)

HR departments are increasingly discovering that traditional tools—especially standardized surveys and pulse checks—can be gamed or misunderstood, or simply put paint a biased picture of the reality. Employees may respond positively out of fear, apathy, or social desirability bias. Leadership assessments that rely solely on this data create an illusion of clarity about what's really going on in their organization. Moreover, many automated tools and dashboards aggregate data to the team or organizational level, which can wash out critical individual insights.

Averages hide outliers. Trends mask personal impact.

When a leader is underperforming in ways that affect morale, innovation, or collaboration, those effects may be subtle, invisible to dashboards, and only detectable through observation of the human interactions.

The Limits of Automated HR Insights

Modern HR technology has grown exponentially in sophistication. Tools like Workday, SAP SuccessFactors, Culture Amp, Glint, and Peakon offer integrations with performance management, engagement surveys, and even passive sentiment analysis through emails and chat logs. AI models analyze patterns and offer predictive analytics on retention risk, burnout, or DEI gaps.

However, these tools have critical limitations:

1. Contextual Blindness: Automated systems often miss the nuanced context behind behaviors. For example, a drop in engagement might be flagged as a red flag without understanding that the team is going through a strategic pivot or that there's a new leader adjusting to the role.

2. Self-Reported Data Bias: Most surveys rely on self-reporting. Employees might not be comfortable expressing dissatisfaction, especially if anonymity is in question.

3. Aggregated Reporting: Many platforms provide insights at the department or team level, making it difficult to pinpoint individual leadership styles that deviate from the norm.

4. Static Assessments: Annual or quarterly surveys fail to capture the evolving dynamics of teams and leadership behaviors.

   
   

Consider the example of Uber in 2017. The company had access to extensive HR data, yet it took a high-profile blog post from former engineer Susan Fowler to expose the extent of the toxic culture and leadership failures. The aggregated data failed to reflect the real lived experiences of many employees. (Source: Susan Fowler Blog)

These limitations leave organizations with a dangerous blind spot: an inability to accurately diagnose leadership gaps at the individual level before they become systemic issues.

Why Behavioral Data and Qualitative Feedback Matter

Leadership is not just about hitting performance goals or driving results. It’s about how those results are achieved—through collaboration, inspiration, inclusion, and trust. These qualities are behavioral, relational, and often invisible to dashboards.

Behavioral data, gathered through structured observations, leadership simulations, or consistent feedback loops, provides a richer, more accurate picture of a leader’s impact. For instance:

• Does a leader regularly interrupt in meetings?

• Do they foster diverse opinions, or do they unconsciously favor similar viewpoints?

• Are they coaching their team members or micromanaging?

• Are they developing future leaders or creating dependency?

In a Deloitte Human Capital Trends report, 81% of respondents said that leaders need to be more people-focused, yet only 29% said their organizations were effective at developing these skills. The gap between expectation and reality highlights the need for deeper, behavior-based assessments.

Such insights can only emerge through a combination of methods: peer feedback, coaching conversations, one-on-one interviews, and real-time behavioral assessments. This qualitative layer adds depth and texture to the quantitative data, allowing organizations to move from surface-level insights to genuine understanding.

Coaching as a Diagnostic and Developmental Tool

One of the most effective ways to uncover leadership blind spots is through coaching. Skilled coaches create a safe space where leaders can reflect on their impact, examine feedback, and become aware of behaviors that might be holding them back.

Unlike standardized assessments, coaching is dynamic. It adjusts to the individual, explores underlying motivations and assumptions, and can confront uncomfortable truths that data alone cannot reveal.

For example, Microsoft CEO Satya Nadella transformed the company culture by encouraging leaders to shift from a "know-it-all" to a "learn-it-all" mindset. Through leadership coaching and development programs, managers were supported to embrace humility, curiosity, and collaboration—qualities that are hard to quantify but critical to performance. (Source: Harvard Business Review)

Organizations that embed coaching into their leadership development process not only improve individual performance but also gain a more realistic view of their talent landscape. Coaching bridges the gap between data and development.

The Case for Individual Blind Spot Identification

Every leader has blind spots. These are not weaknesses in the traditional sense but areas where their intent and impact are misaligned. A leader might think they are empowering their team by delegating, while the team feels abandoned and unsupported.

Identifying these blind spots requires more than data. It requires triangulating multiple sources:

• Quantitative data (e.g., engagement scores, 360 feedback)

• Behavioral observation data

• Qualitative interviews

• Coaching reflections

• Historical performance trends

A good example is Google’s Project Oxygen, which initially tried to prove that managers didn’t matter. The opposite turned out to be true. Through a combination of data and behavioral interviews, Google identified key leadership behaviors that differentiated high-performing managers. The result was a framework that emphasized emotional intelligence, psychological safety, and active coaching—none of which surfaced in early quantitative analyses alone. (Source: Google Re:Work)

Combining these sources helps build a holistic picture. It allows HR teams and leadership development experts to offer tailored interventions that address root causes rather than symptoms.

Targeted Support: The Future of Leadership Development

Once blind spots are identified, the next step is targeted support. Instead of generic leadership training programs, companies should offer personalized development journeys:

• If a leader struggles with inclusive communication, assign a DEI-focused coach.

• If another lacks strategic thinking skills, offer simulation-based decision-making training.

• For leaders who struggle with feedback, design peer-learning sessions around candor and active listening.

  
  

Unilever, for example, has implemented targeted leadership development through their Connected 4 Growth initiative. Leaders were supported with tailored coaching and behavioral insights, leading to faster transformation across business units. (Source: McKinsey & Company) This precision approach not only accelerates development but also increases ROI on learning investments. Leaders feel seen, supported, and challenged in the right ways.

The Power of Pre-Existing Data

Imagine starting a coaching engagement with a clear, data-informed picture of a leader’s strengths, risks, and blind spots. Pre-existing data—when collected responsibly and interpreted with nuance—can be a powerful accelerator.

Rather than spending weeks diagnosing, coaches and HR partners can dive straight into development. Pre-existing insights from engagement surveys, team health checks, and behavioral data allow for:

• Faster alignment on development goals

• Quicker impact through focused interventions

• Higher engagement from leaders who feel their time is respected

  
  

However, this only works when data is integrated meaningfully, not dumped in raw form. It must be curated, contextualized, and supplemented with human insight.

Conclusion: Bring Humanity Back to the Center

The promise of data in HR is real—but so are its limitations. As organizations race to quantify everything, they risk losing sight of the very element that makes leadership effective: the human element.

To develop better leaders, companies must move beyond dashboards and embrace a more holistic, human-centered approach. That means:

• Triangulating data with qualitative insights

• Embedding coaching into development strategies

• Prioritizing behavioral data and real-world observations

• Designing targeted interventions based on individual blind spots

  
  

Ultimately, the goal isn’t to choose between data and human judgment. It’s to integrate them. Only then can we unlock the full potential of our leaders—and of our organizations.

In a world awash with HR data, it’s time to remember:

Numbers don’t lead people. People do.