“I am convinced that nothing we do is more important than hiring and developing people. At the end of the day, you bet on people, not on strategies.”
— Lawrence Bossidy, American author and businessman
People analytics is the process of collecting, analyzing, and interpreting HR and people data that can be used for better HR decision-making resulting in increased business outcomes. It equips People and Culture leaders with data-driven insights to serve a variety of processes such as hiring the right talent, predicting and resolving employee issues in time, and providing a better overall employee experience.
Take Sysco, the Fortune 100 global food service company, for example. They ran a workforce analysis to determine that operating units with highly satisfied employees ran lower operating costs and generated much higher revenue as opposed to the other operating units. What more? This drastic improvement in employee satisfaction brought up their employee retention rate from 65% to 85%. And retaining their best talent saved them nearly $50 million in hiring and training costs!
It is estimated that in 2023, 60% of the Global 2000 companies will leverage AI and machine learning platforms to support the entire employee lifecycle from onboarding to retirement. And with AI continuing to revolutionize the HR sector, investments are bound to increase accordingly. Recent Gartner research shows that around 47% of HR leaders plan to increase their AI investments in the near future.
The 3 Types of People Analytics & The Purpose of Each
To enable People and Culture leaders with the right data, people analytics makes use of raw data pulled from your organization. It then applies algorithms to this data to create comprehensive charts and visualizations they can use to facilitate better decisions. For this, it leverages AI-based machine learning models.
There are 3 types of people analytics that each serve a specific purpose in HR. They are descriptive, predictive, and prescriptive analytics. Here’s how each contributes to the overall people analytics process:
1. Descriptive Analytics
This type of analysis looks backward and “describes” historical info. Descriptive analytics is the process of collecting raw data and converting it into useful information. Raw data is of little help when it comes to describing how and why things happen. That’s why we need descriptive analytics to do it for us. This is the most common type of people analytics that most People & Culture leaders are familiar with.
Examples of descriptive analytics would be the attrition rate of an organization over the past quarter, the time it takes to fill certain roles, the workforce strength over the past three quarters, etc. Analyzing these metrics can provide the company with insights into their causes and help identify areas where improvements can be made.
2. Predictive Analytics
This type of analytics looks forward and “predicts” what is likely to happen in the future. For this, it uses the data from descriptive analytics and makes statistical models and forecasts based on this data. While descriptive analytics tends to tell you what has already happened, predictive analytics tells you what’s going to happen.
This is especially helpful in the case of talent acquisition where it can predict a potential candidate’s cultural fit or even the term of employment with the company. If descriptive analytics can tell you the attrition rate over the past three quarters, predictive analytics can tell you the expected attrition rate for the next quarter.
3. Prescriptive Analytics
Now that predictive analytics has predicted what is likely to happen, we need someone to tell us what to do with the prediction. That’s where prescriptive analytics comes in. It prescribes courses of action that need to be taken to achieve a specific business outcome.
For example, if predictive analytics forecasts a surge in sales over the next quarter in the AMEA region specifically, more salespeople might need to be prepared to deal with businesses in the region to leverage the surge. Or if predictive analytics predicts that the attrition rate is likely to go up in the next quarter, prescriptive analytics may recommend providing employees with more opportunities for career advancement or other similar initiatives, depending on the situation.
The problem with people analytics in general is that organizations tend to focus on descriptive analytics while leaving out predictive and prescriptive analytics, both of which are just as, if not more important than descriptive analytics. This is because descriptive analytics is just that—descriptive. It doesn’t tell you what exactly to do with the information. You need predictive and prescriptive analytics for that purpose.
The Core Benefits of People Analytics
- It strengthens your decision-making with data-driven insights. People analytics uses historical data to make predictions and recommend courses of action. This kind of data analytics provides precise insights that People & Culture leaders can use to make well-informed decisions rather than subjective guesses.
- It improves performance and productivity. Employee engagement surveys are a great way to help People & Culture leaders understand what keeps people engaged or what issues they might face. People analytics has also doubled employee performance and output in certain cases. It provides insights to help keep employees engaged and satisfied at work.
- Its predictions keeps organizational costs in check. The analytical nature of people analytics is immensely useful in predicting which areas within the organization are likely to drain finances. For example, it can predict which employees are likely to quit well before they turn in their resignation letter. This information can be used by organizations to understand which positions might need filling soon and consequently, make the necessary talent sourcing efforts.
- It bridges skill gaps. Your people are equipped with specific skills that serve a specific purpose to your organization today. However, you might require different skills from them in the future as your business needs change. People analytics can predict this skill gap and guide you to equip the right people with the right skills at the right time.
- It improves retention rates. As mentioned earlier, people analytics can improve performance and productivity. This can in turn, improve employee retention rates. People analytics enables People & Culture leaders to determine what the people want, giving them a blueprint in creating a better overall employee experience.
The 7 Pillars of People Analytics
People analytics encompasses seven branches or “pillars” of HR analytics. These pillars create a framework for People & Culture leaders to build a future-proof workforce that successfully meets the needs of the business.
1. Workforce Planning Analytics - Workforce planning is in simple words, leveraging the best of your existing workforce with the right planning. It works by analyzing existing workforce data and predicting future trends to plan an optimal workforce strategy.
2. Talent Sourcing Analytics - Talent sourcing is the process of identifying and connecting with talented individuals to convert them into applicants at your organization. Great talent is difficult to come by and the war for talent is in full swing in today’s economy.
3. Recruitment Analytics - Recruitment is the next start after talent sourcing. In recruitment analytics, data is used to interpret insightful patterns in sourcing, qualifying, and hiring in an organization. For example, a heavy attrition rate for a particular position could indicate a mismatch between the job description and the actual role or a poor onboarding process.
4. Engagement Analytics - This is the branch of people analytics that aims to create a happy and engaging workplace. In engagement analytics, data is derived from various sources to identify the causes of employee attrition and employee satisfaction within the organization.
5. Employee Value and Performance Management Analytics - This helps in creating a system of support and recognition. It helps People and Culture leaders better understand what kind of support is required to improve productivity and performance across the organization. It detects issues such as poor communication, poor training opportunities, lack of recognition, etc., that may cause poor productivity.
6. Retention Analytics - As the name suggests, retention analytics is the process of analyzing data to understand why your people leave an organization. Hiring and onboarding people can be expensive. Meanwhile, it’s even more expensive to let go of an employee in terms of money, energy, and lost productivity.
7. Employee Well-Being Analytics- 6 in ten job seekers rate wellness initiatives as a top priority, especially among the Gen Z demographic. Employee wellness analytics aims to redesign the way employees work by providing better wellness programs, meeting their expectations, and paying attention to the overall health and happiness of your workforce. It helps People and Culture leaders understand where the organization might be lacking in terms of employee well-being and what measures need to be taken in this regard.
The Future of People Analytics
People Analytics can serve a variety of HR purposes from employee retention, calculating and predicting attrition, employee engagement, learning analytics, and recruitment analytics. According to recent research by Gartner, the key areas where organizations plan to implement AI in the coming years include workforce planning (52%), learning and development (51%), skill management (48%), and performance management (44%).
As machine learning and AI technology continue to grow, so will the field of people analytics. And development in people analytics will bring more accurate predictions, better decision-making, and a highly people-focused digital transformation strategy. This means an overall reduced workload for People & Culture leaders while simultaneously driving better business outcomes.
“Train people well enough so they can leave. Treat them well enough so they don’t want to.”
— Sir Richard Branson, British billionaire and entrepreneur