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Published: 27 June 2024
Contributor: Keith O'Brien, Amanda Downie

What is people analytics?

People analytics is the act of collecting and analyzing human resources (HR) data to better understand how employees are performing in the work environment. Analyzing the collected data points is a key component of an organization’s data-driven decision-making and employee experience strategy.

People analytics helps organizations better understand employee performance and allocate resources to maximize people management. People analytics, which typically incorporates HR analytics, talent analytics or workforce analytics, is a cornerstone of workforce planning.

Organizations are using workforce data analytics more frequently to plot business goals and help understand the future of work in their organization. The ultimate goal of this data-driven approach is to create the right initiatives to improve business outcomes.

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People analytics versus other employee analytics

Many organizations use people analytics to refer to the holistic approach of using data and analytics to study everything that impacts their employees. Two other categories of analytics that fit under the topic of employee management are:

  • HR analytics: This analytics is primarily associated with HR duties, like hiring, training and retaining full-time employees. It is also called talent analytics.
  • Workforce analytics: This analytics program refers to managing all members of the workforce, whether they are full-time, part-time, freelance or consultants.
What are the types of people analytics?

There are several types of people analytics that organizations can use to either review previous situations or predict future occurrences.

Historic analytics

These analytics involve analyzing past events and data to understand the current state of affairs. For example, organizations can look at current and historic time-to-hire rates to see whether new initiatives have improved their processes.

Predictive analytics

These analytics involve modeling what might happen in the future based on historical and industry data. Predictive analytics helps anticipate future issues, like increased employee turnover, if certain criteria were to occur. For example, decreased attendance at meetings or work events might imply that employees are disengaged and at risk of leaving the company.

Prescriptive analytics

These analytics measure potential future outcomes and provide solutions that aim to maximize results. For example, lower efficiency can mean there’s a skills gap, and the organization’s leaders can fix this with extra employee training.

Types of data collected with people analytics

Organizations tap into several different types of latent and real-time data, some of which they can access on HR data dashboards.

Many organizations use people analytics platforms like human resources information systems (HRIS), or HCM software, to track analytics and establish key performance indicators (KPIs). This application incorporates talent planning, management and analytics in a single system. The software provides human capital management solutions at scale, especially when powered with AI. Organizations can also use data visualization tools to make sense of it the data collected by HR systems.

  • Diversity equity and inclusion data: Organizations are increasingly committing to hiring a wide variety of people from different backgrounds to achieve DEI goals. To keep on track with these goals, HR needs to track the data of existing employees, future employees and prospects.
  • Employee preference data: Understanding what motivates employees and what perks they most appreciate helps business leaders to more efficiently allocate resources to support employee needs. Data from employee surveys and ad hoc check-ins help leaders to better understand which perks and benefits are popular, and which ones go underutilize.
  • Employee engagement score: Tracking this score over time can alert an organization if employees are unhappy and, therefore, a turnover risk. Similar to employee preference data, this score helps organizations keep a baseline on their teams and assess the health of retention and talent pipeline strategies.
  • Time-to-hire rates: Recruiting and hiring employees can cost a lot of money and drain resources from other activities. It is especially taxing if an organization takes longer to identify and sign those prospective employees. Monitoring the time it takes to manage recruitment helps organizations.
  • Benefits usage: Collecting benefits usage helps leaders simplify the complex task of managing workforce benefits. With data to support the benefits system, planning and decision-making becomes easier for your employees, driving enrollment and deductions throughout the system.
People analytics professionals

There are various stakeholders whose collective actions contribute to people analytics. Some organizations build specific people analytics capabilities, led by executives. Others approach it more collaboratively.

  • Business leaders: Organizational leadership needs to prioritize people analytics as a key component of their business strategy. They need to invest in the resources required to mine their internal data and authorize the purchase of the right analytics solutions. Executives must communicate to their HR leaders that people analytics is a priority, pointing to the potential correlations between strong people analytics and positive business results.
  • HR professionals: The HR department is integrally involved with setting the company's people analytics strategy. HR professionals are the front line in managing the collection of HR metrics related to employee data, employee reviews and feedback, and calculating employee satisfaction statistics. In addition, they help with the data collection to better understand which employees need to upskill or reskill to maximize an organization’s chance of succeeding.
  • IT department: The IT team needs to understand what tools the organization has for people analytics, and whether there is a need to license different tools or build the tools themselves. IT professionals will have perspective on how artificial intelligence, machine learning and other technologies and infrastructure can improve data collection and analysis.
  • Legal teams: Organizations must take care to keep data, particularly private personal information, secure. Legal teams should work with IT and security teams to understand the system for collecting, analyzing and storing data, in order to better protect the organization from leaks or potential compliance issues.
  • Employees: It benefits an organization to have employees understand and appreciate how people analytics helps them perform their jobs better and be more satisfied at work. Employees should understand what data the organization collects, how the data is used and how it benefits them.
People analytics strategic approach

Different organizations take varying approaches to their people analytics strategy, but most follow a straightforward pathway.

  • Establish your business objectives: All successful people analytics approaches should align to business goals. Setting forth those goals at the beginning makes the rest of the process smoother.
  • Select people, HR and workforce goals: Next, the organization should identify what major goals they have for their workforce function, such as improving how long it takes to hire, decreasing turnover or improving employee training sessions.
  • Identify the right key performance indicators (KPIs): Once the organization knows its business and workforce goals, it should identify the best way to track those initiatives and set clear KPIs.
  • Find the right tools: Organizations should identify which tools are right for their particular business to collect data and produce insights in accordance with any legal regulations, IT constraints and other organizational guardrails. 
Benefits of people analytics

There are many important benefits to incorporating the data from people analytics into an organization’s strategy. 

  • Aligns HR strategy with business goals: Organizations that use evidence-based human resources are likely to have important information that can improve their overall business strategy. For example, knowing that employees are engaged and time-to-hire rates are dropping; the organization can potentially reallocate some recruitment budget to other more needed areas.
  • Improves diversity figures: A McKinsey study found that 54% of respondents1 (link resides outside ibm.com) said DE&I was among the top three areas where people analytics drove the most value. Knowing where an organization is to its diversity goals is increasingly important.
  • Improves employee engagement: Understanding what motivates employees and what does not helps leaders more efficiently plan employee engagement strategies. Tracking how the organization interacts with employees and how it monitors their well-being creates a more positive environment.
  • Identifies high performers: People analytics helps organizations compile actionable insights on both macro and micro levels. Organizations that prioritize the latter can better target excellent employees for career advancements.
  • Enhances performance management: Performance and goal tools can measure team productivity and provide course corrections when the data exposes inefficiencies. For example, SAP SuccessFactors is a cloud-based system for human capital management (HCM). It can track analytics around onboarding, recruitment and retention issues, compensation management, payroll and benefits administration and time and attendance.
  • Maintains compliance: Pursuing any data analytics means that an organization is collecting significant amounts lot of data. They need to safeguard that information to avoid privacy issues and maintain compliance with local, federal and national laws.
  • Reduces attrition: Employees want to know how they are doing in the eyes of the organization and among their peers. To increase employee retention, organizations need to better share information with them about their progress and opportunities for growth. This can help reduce turnover rates and improve employee satisfaction.
How AI can supercharge people analytics

AI is revolutionizing HR in several ways, including people analytics.

  • AI-enabled HR work: HR professionals can use generative AI to draft job descriptions, serve as a co-pilot on interviews and run employee onboarding. AI can help supercharge talent acquisition and talent management as well as analyze the data that comes from those HR processes.
  • HR automation: Organizations can use software to aid HR professionals by removing repetitive manual tasks and supercharging the HR processes humans still need to handle. Automation tools help manage many parts of the HR teams’ recruitment process, from identifying new hires to sending acceptance or rejection letters based on internal criteria. Automation can quickly crunch recruitment statistics to produce actionable insights, leading to faster decisions.
  • Machine learning parsing big data: People analytics produces numerous data points that require either many human-power hours or the right technology to turn into actionable insights. Machine learning can cut down the hours HR professionals spend on those activities so they can focus on higher-level work.
  • Sentiment analysis: Organizations can train AI to ingest emails, social media discussions, documents and call transcripts to unearth actionable insights. For example, it can identify commonalities in interviews with candidates who accept positions, helping interviewers tighten up their call scripts.
  • More efficient data analysis: Using generative AI-augmented process mining can identify bottlenecks and inefficiencies and make recommendations to fix them.
  • Onboarding process: Automating the onboarding process by using intelligent systems makes it quicker to get new hires generating value for the business. These analytics also produce data that can help continually improve the onboarding process.
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1. Talent at a turning point: How people analytics can help (link resides outside ibm.com), McKinsey, 24, February 2022