People analytics is the application of math, statistics and modeling to worker-related data to see and predict patterns. In particular, people analytics, also known as HR analytics and talent analytics, is analysis used to make better decisions about all aspects of HR strategy with the goal of improving business performance.
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People analytics is a broad area that encompasses all aspects of acquiring and managing employees, and it has largely come to replace its predecessor term, HR analytics, though that term is still in use. Besides HR analytics, talent analytics and, in some cases, workforce analytics may be used synonymously with people analytics.
HR analytics vs. people analytics
HR analytics was the initial term used to describe the measurement of HR programs and their effectiveness, and it was done in HR data warehouses, which were primarily the realm of technologists. HR analytics has its origins in industrial psychology, studies to optimize production and thought leadership such as that represented in the 1984 book How to Measure Human Resources Management. The term HR analytics came into wider use as software providers increasingly offered what they called HR analytics tools.
However, other terms also came into use -- especially people analytics, talent analytics and workforce analytics -- and were often still used synonymously, although HR analytics remained dominant as the catch-all term until recent years.
In terms of meaning, talent analytics has been almost indistinguishable from the other terms, touching on everything from recruitment to workforce planning.
Workforce analytics tends to refer both to the macro elements of HR strategy -- for example, the effect of changing demographics or issues surrounding skill gaps -- and more narrowly focused workforce planning issues, such as the staffing needed for a particular region or labor costs and productivity.
People analytics has largely become the dominant term, according to many thought leaders, since all aspects of HR strategy, at their core, relate to people. Understanding talent pipeline issues and assessing which wellness and learning programs are working, for example, are all about people.
In addition, the term HR analytics suffers for its original connotation as analytics exclusively for and by the HR department, whereas today, analytics is increasingly being used to improve all aspects of employee experience by managers and others across the company. Moreover, the actual administration of the analytics tools typically needs expertise outside the HR department and requires the help of data analysts and IT.
Some typical uses of people analytics
People analytics is beginning to help more companies in their recruiting, performance measurement, compensation and retention efforts. People analytics can help organizations to understand which candidates to hire, which employees are doing well, who's receiving adequate compensation and how employee retention can be improved. Ideally, people analytics can improve on instinct and gut feeling; for example, showing that, in some cases, a community college certificate makes for a better employee than a four-year degree.
However, a groundswell of interest in people analytics points to its expansion into new territories, especially with the use of predictive analytics, and that its use is moving beyond HR into the business as a whole. Two examples are using people analytics to predict and address low-performing salespeople and hospitals that use analytics to understand the employee factors in patient outcomes. Creating new opportunities for revenue by looking at both customer and labor data and enabling profit growth by analyzing workforce spending are two others.
In addition, tools are being developed to expand the use of analytics. Increasingly, companies are looking to vendors rather than building their own tools as analytics models become more widespread. As just one example, some ERP vendors are including people analytics dashboards meant to help senior executives understand attrition rates, employee costs and employee engagement profiles for specific segments and managers.
People analytics are also increasingly expected to analyze teamwork and organizational relationships, which may take on heightened importance as companies replace hierarchical models with more collaborative ones.
A few areas of concern
HR data management is still a major concern. HR data continues to be siloed, incorrect, out of date or inconsistent. Understanding the number of contract vs. salaried employees or changing the options in a system of record are just two examples of the data-related issues that can plague companies.
In addition, helping HR staff and other business users understand how to work with and accept analytics can be problematic. Further, understanding what questions to ask of data and how to ask them is an ongoing challenge.
HR metrics vs. HR analytics
One point of confusion may be the difference between HR metrics and HR analytics. In essence, metrics describe concrete measures of past performance, while analytics uses data to gain insights or predict future patterns. Metrics typically describe basic information, like how many candidates applied, how many employees left the company and other descriptive measures, while analytics looks at answering questions such as what educational background best helps indicate future high performers or why top performers are leaving.