Exploring people analytics: Insights from global industry analyst Kathi Enderes

Meet Kathi Enderes, a senior Vice President and global industry analyst at The Josh Bersin Company. Kathi has extensive global experience in human capital, talent and performance management, and change management from consulting with IBM, PwC, EY, and Deloitte and industry with McKesson and Kaiser Permanente.

In this interview, we discuss various aspects of people analytics, including its definition and scope, placement within organizations, role in talent acquisition, retention, and employee engagement, key metrics and KPIs, data sources used, future role, and workforce forecasting.

People analytics is the practice and function of collecting, analyzing, interpreting, and making actionable insights about people and talent to make better business decisions. The insights can come from:

• Quantitative data: (e.g., headcount, turnover, performance ratings, labor cost, engagement survey results, sales numbers, and customer satisfaction results)
• Qualitative data: (e.g., resumes, skills, survey comments, performance evaluations, comments on social media).

Effective people analytics departments can sit in various places in the organization. The function can most effectively sit directly under the CHRO, but sometimes it will be moved under the HR Tech team, HR Services, or Talent Management. Organizational structures don’t make or break the success of people analytics departments — how well they are connected to the business and can integrate across the organization makes them successful.

Recruiting analytics are one of the first use cases for people analytics because hiring and recruiting is the most data-heavy domain of HR (after all, there are often millions of people to consider with billions of skills for any given job). Traditional people analytics might look at efficiency measures in recruitment:

• Time to fill
• Cost to hire.

Effectiveness metrics:

• Quality of hire
• New hire turnover.

Still, next-generation people analytics also includes talent intelligence:

• Looking at skills needed
• Comparing to skills in the organization
• Benchmarking skills of competitors
• Determining a skills-based workforce plan.

This plan includes what we call “systemic HR”:

• Recruiting for skills
• Retaining the right skills in the organization
• Reskilling the workforce to fill workforce gaps
• Redesigning the work to reduce the need for hard-to-fill skills.

Retention is another evergreen use case of people analytics.

For example

Some companies have given managers nudges and clues that an employee is a high retention risk, and the manager then turned to the employee, asking them why they planned to leave. Retention modeling is complex, and addressing retention risks is not as simple as having a “stay interview.”

Employee engagement often correlates with retention, but its impact is much bigger. Even if an employee may not leave the organization (because of high salary, unfavorable market conditions, or other reasons), disengagement and a lackluster employee experience will impact customer satisfaction, financial performance, and innovation outcomes.

Among the practices for employee engagement are the right resources to do the work well, a team that supports them, health and wellbeing support, learning and development that helps them grow skills, an effective digital, cultural, and physical workplace, and trust in the organization. (More about the broad-based employee experience study you can find here).

There are many measures and metrics in people analytics. I’d classified them into four distinct groups:

• Efficiency measures (time to fill, cost to hire, training cost, hours spent in training, HR service delivery costs, etc.)
• Effectiveness measures (quality of hire, training effectiveness measures, retention, succession bench, etc.)
• Engagement measures (engagement, inclusion, NPS, etc.)
• Business success measures (innovation, productivity, financial performance, customer delight, change agility, etc.)

Data sources for people analytics can be categorized into several key groups:

• Transactional systems: HCM, ATS, LMS, etc.
• Employee feedback measurement: annual and pulse surveys, always-on mechanisms, etc.
• Network analytics: Organizational Network Analysis, etc.
• Communication and EX platforms.
• Skills and talent intelligence: talent marketplaces, skills-based recruiting systems, etc.
• Business systems: financial performance, customer satisfaction, innovation, etc.

People analytics plays a massive role in up-leveling HR’s future role and bringing dynamic, future-focused insights to HR and leadership.

However, with current progress and capabilities, this vision is still not in the foreseeable future.