A complete guide to HR people analytics use cases – benefits, implementation tips

People analytics is no longer a privilege of large companies with access to cutting-edge technologies and the brightest tech minds as a part of their in-house teams. In fact, it’s a necessity for any kind of sustainable business: from small and medium enterprises to large enterprises.

Here at HRForecast, we advocate for data-driven, facts-based HR where people analytics is in the cornerstone.

In this guide, we gathered all our insights to uncover people analytics definition, tools, benefits, and other tips:

1. What is people analytics?
2. Use cases of people analytics
3. Benefits of people analytics for an organization and its employees
4. Key challenges of people analytics implementation
5. How to implement people analytics at your organization
6. Useful resources and certifications to boost the expertise of your HR department

People analytics (also known as HR analytics) isn’t a novelty or a fancy HR buzzword. In fact, it’s been around for a while. David Green, one of the trailblazers and leaders in the people analytics field, traces the first mentions and use cases of people analytics back to 1911 in Frederick Taylor’s book “The principles of scientific management.” In this book, Frederic Taylor describes the idea of business optimization through precise analytics of employees’ performance and productivity levels.

Other significant changes that pushed the adoption of people analytics include industrialization, the 80-s shift in an HR paradigm from administration to appraisal and people development, and a so-called “The Age of Realization” during 2010-2015.

People analytics provides insights for practically any area of business and HR. Here are a few typical use cases of people analytics:

Skill gaps. HR analytics can also reveal skill and talent gaps that need further improvement.

Strategic workforce planning. People analytics helps businesses audit the current workforce situation and derive insights for talent management, hiring, and long-term resource planning.

Learning and development. Analyze training needs, the correlation between training and performance indicators, the connection between training efficiency and methods of presenting information, etc. 

Succession planning. Identify talents for key positions and align your succession planning strategy with a long-term hiring plan.

Employee retention, engagement, and motivation. With the actionable data at hand, you can identify employee engagement rates, analyze top performers, build predictive models that warn of declining productivity, and more. For example, Hewlett-Packard has been employing predictive analysis since 2011 to evaluate employee burnout rates and figure out reasons for leaving the company.

Recruiting. People analytics provide insights on challenging vacancies, recruiting team performance, sourcing strategies, hiring time and cost, candidate loyalty, and more. Google was one of the first companies that implemented people analytics in their recruiting process. They analyzed thousands of technical interviews and found out that some of the questions wouldn’t predict candidates’ performance and career success. As a result, Google started to develop its people analytics expertise to forecast employee success rates and the likelihood of their leaving the company.

Budgeting. People analytics helps analyze budget-related factors like dynamics and structure of payroll, calculation of the employee’s break-even point, and disability costs.

Employee impact on business. People analytics in HR can help figure out the ways to increase your sales performance. You may find that specific talent helps employees perform better or that certain training programs provide immediate return on investment.

Health and safety in the workplace. For example, HR analytics helps identify roles, workplaces, and other areas with the highest accident rates.

Sales and customer experience. Happy employees result in satisfied customers. The Coca-Cola company embraced this concept in 2010 to build a predictive model that correlated internal employee communications and business results.

HR departments are significant generators of data. Naturally, organizations that have harnessed HR analytics outperform their competitors in quality of hire, employee retention, skills development, and other HR-related and even business aspects.

One of the most incredible benefits of people analytics is that it allows you to identify a root cause of a problem area and come up with an action plan. It helps you step away from a “what happened metrics” mindset (for example, Our turnover is 12%) and begin gathering the call “why metrics” (like 85% left because of inefficient management). Analytics prevents decisions based on gut feeling and stands for logical data reasoning. It connects dots in a complete picture and comprehends the main driver for any issue.

Now let’s study a list of people analytics benefits you could reap:

Everyone’s talking about boosting employee productivity, but we rarely get to talk about the root cause of negative performance indicators and failed KPIs. People analytics reveals untapped opportunities in the workforce, such as extra skills that employees haven’t listed on their CVs and job profiles.

Also, people analytics in HR helps improve employee performance by eliminating a human error in decision-making, allocating resources to distribute the workload among departments, and more.

Let’s admit it: HR decisions still involve a small amount of gut feeling. For example, hiring and interviewing depend on personal contact and rapport between a recruiter and a candidate. People analytics helps eliminate this bad HR practice with a precise analysis of candidates’ efficiency in real-life situations, candidate’s loyalty, interviewing process and its steps, and more.

Also, injustice in the workplace, like the gender pay gap, can’t get unnoticed with the evidence (like distribution of wages across different demographic characteristics) at hand.

The labor market tends to behave differently in each niche. Thus, an HR approach applicable to one industry should be adjusted to another field.

Usage of Big Data increases hiring and recruiting efficiency, like speed, capacity, and hire experience. It also identifies the sources that produce the highest quality of hires (for example, referrals from top-performing employees) and which interview questions don’t predict new hire success (like brainteaser questions).

People analytics in HR helps organizations measure, evaluate, and then devise action plans to increase their business outcomes. For example, by designing more effective recruiting, employee retention, and reward systems, HR can directly increase the revenue of the sales group. People analytics helps to understand the most pressing challenges within the organization as well.

Analytics enables accurate allocation of the HR budget, human resources, and time investments with the maximum impact. Data can also help identify the jobs, teams, and business units that have the highest impact on corporate goals when provided with top talent.

HR analytics is more than just analyzing; it should help you with long-term workforce planning and translating business requirements to a business strategy.

With its ROI ratios, HR can also compare the effectiveness of its programs against competing functions like finance, marketing, and IT. Under the analytics model, HR will also require all new talent programs to utilize data-driven decision-making and to include performance metrics and current and predictive analytics. Then, people analytics will contribute to the development of new work models.

HR analytics provides insights on better engaging employees with measurable factors like recruitment, performance, pay, and benefits. Thus, HR analytics enables the HR department to investigate changes to improve employee productivity. Feedback during an appraisal can also provide relevant insights to improve company culture and create a better working environment.

People analytics functions at the nexus of various fields: HR and IT (data mining, analytics, interpretation, visualization, etc). Thus, you should expect certain challenges and resistance to implementing changes from top management and your employees.

Let’s review people analytics tools and essential steps to implementing this process.

It all starts with business goals: whether you aim to decrease employee turnover rates, improve employee retention, or enhance diversity.

Let’s say you need to evaluate the performance of your HR department. In that case, you’d need to identify actionable metrics that help assess efficiency, performance, and impact of HR like layoff rate, average recruitment time, turnover rate, etc.

Once you’ve mapped out the business goals, it’s vital to determine the data you’ll analyze. That’s when workforce intelligence steps in.

Simply put, workforce intelligence is a process of discovering employee data, behavior, and patterns for further analysis, hypothesis, and running feedback loops.

Workforce intelligence employs data analytics and visualization to transform the data piles into manageable and structured data sets ready for further interpretation.

People analytics implies tight collaboration of HR and IT departments as the process includes complex operations like data mining and specific skills like data analytics. A significant part of the HR-IT collaboration is the ETL implementation, so even non-technical staff could extract the required data from pre-defined sources, transform it into a consistent format, and run hypothesis and feedback loops.

Let’s say your concern is diversity in the workplace. Then, you might want to analyze your hiring process like sourcing strategy to discover bottlenecks. Eventually, you find it: it’s a lack of incoming CVs from ethnic minorities. This discovery helps you fix a real problem instead of dispersing your efforts on not-so-significant areas.

That’s a quick recap of the final step in people analytics implementation: build hypothesis – run tests – analyze results – repeat. A rule of thumb is to maintain a consistent HR analytics process. Otherwise, your data might quickly become obsolete and irrelevant.