What is HR Analytics? Definition, Types, Objectives & Process

People are at the heart of any company, and people management is the need of the hour. The return on any kind of investment bears fruit when people contribute. For this reason, decision makers may want to know how productive and engaged the workforce is. HR needs to be empowered by data, to explain itself better to decision makers and enable the decisions it takes on behalf of the organization. This is why HR analytics is in the spotlight today.

Alp Consulting, an expert in people and talent management is eager to help organizations unleash the power of HR analytics.

What is HR Analytics?

Before we go any further, let us look at what HR analytics is. The process of collecting, verifying and analyzing HR data to achieve organizational goals is called HR analytics. It involves applying analytical methods to HR or people management processes to improve such parameters as employee productivity, profit per employee and employee retention and experience.

It has the power to transform any organization’s efficiency and improve its work culture tremendously. Modern advancements in data analytics have greatly increased the applicability and forecasting prowess of HR analytics in organizations.

Evolution of HR Analytics

HR analytics has been in existence since Frederick Winslow Taylor’s classic The Principles of Scientific Management in 1911, where he used statistical methods to manage people. It evolved over the years, with great advancements starting in the year 2008, when it reached a position of importance and big corporations such as Google and Microsoft started using it very widely.

Modern advancements in prescriptive analytics have further widened its scope and it now encompasses almost every aspect of HR and even small and medium sized businesses stand to benefit from it.

What is the Importance of HR Analytics?

The importance of HR analytics for organizations in the present year is in three different cases:

1. It can help manage talent in smaller and medium sized businesses so that they can boost productivity by retaining the gifted and productive employees during a time of crisis.
2. It can assess the difference in productivity between remote, hybrid and onsite work environments and suggest suitable changes to workplaces.
3. The importance of diversity to millennials needs no mention. HR Analytics will help companies satisfy their diversity and inclusion criteria better and more effectively.

What is the Objective of HR Analytics?

The main objective of HR analytics is to gain valuable insights from data about the people who work for you, how to increase their effectiveness through decision-making based on these insights, and what realistic goals may be set for them.

What are the Different Types of HR Analytics?

HR analytics can be classified into four types based on what they help accomplish and what methods they use to get it done. The four types of HR analytics are:

Descriptive HR analytics – What happened?

Using statistical data, it explains and summarizes what has happened already. It does not make any predictions for the future. A couple of examples of descriptive analytics in action in HR are:

1. Analysing average number of paid time offs availed by employees in a year.
2. Comparing attrition levels of employees over the past 5 years.

Diagnostic HR analytics – Why did it happen?

Diagnostic analytics is based on the same data as descriptive analytics but goes one step further and gives reasons for what happened. It identifies the patterns and anomalies within the data, and then study them further to understand what factors could be contributed to them. Applying diagnostic analysis to the same two processes described earlier, we can:

1. Why employees in a certain demographic have availed more paid time-offs?
2. Why has there been an increase in attrition over the past two years?

Predictive HR Analytics – What will happen?

It categorizes past and present data to isolate patterns and anomalies in them and develop a model to predict the future based on them. In the process, the analytical model that is built to predict the future is then evaluated by applying new data to it. Let us look at two examples of predictive analytics in HR:

1. Predict the average absenteeism of employees in the next month based on inputs for the that month over the past five years.

2. Predict what channels and what locations must be targeted in recruiting candidates with a particular skill.

Prescriptive HR Analytics – How can we make it happen?

Prescriptive analytics takes predictive analytics further and analyses why something happened and what corrective measures to take to improve it further, hence the name “prescriptive”. Let us revisit the same two examples for predictive analytics and see how prescriptive analytics will modify them.

1. Predict the average absenteeism of employees in the next month based on inputs for the given month over the past five years, why it is so, and how to reduce absenteeism by 25% in the next month.

2. Predict what channels and what locations will provide candidates with a particular skill, why they do so, and how the messaging can be tweaked to improve the recruitment in these zones?

What is the HR Analytics Implementation Process?

The HR analytics process in a company does not follow a certain process only. The process of collecting data and deriving insights from it is based on the type of data analytics method that is applied. Let us now look at the 9 steps in HR Analytics implementation process:

Step 1: Specify objectives

What and where are the problems you are trying to solve with HR analytics and how will you apply HR analytics to solve these problems? By specifying these objectives, you will have a better idea of how to use HR analytics to achieve your business goals.

Step 2: Identify data sources

What systems are you going to use to collect the data and what is the level of confidence you have in the data and the sources you are obtaining the data from? This will affect the final research outcomes when you use HR Analytics tools.

Step 3: Develop HR analytics models

HR analytics models and metrics that align with the business goals must be developed. The models and metrics are developed to address common issues such as employee turnover, performance and engagement.

Step 4: Organizing collected data

This is a very important step in the HR analytics process. By organizing the data using data labels and by assigning a data steward to take care of the data and manage it, you are now only a few smaller steps away from a good decision.

Step 5: Analyse the data

Statistical analysis and data visualization tools are then used to help identify trends and patterns in data and provide visualizations on it to stakeholders and decision makers. An example of this is the use of

Step 6: Create dashboards

Dashboards help bring the information together in a meaningful manner. Dashboards are built at this stage of the HR analytics process to gauge every KPI that is necessary for decision-making at the managerial level.

Step 7: Implement the analytics steps

The actual analytics happens in this phase using the models and metrics developed earlier, and the results are presented through the dashboards that have been created.

Step 8: Train and re-train the HR staff

The HR team must be up to date on how to use HR Analytics tools. They must be trained on how to use it to present to decision makers the challenges faced in talent management in the organization.

Step 9: Monitor outcomes, evaluate and iterate

Are there positive outcomes like increased employee engagement, increased productivity, and reduced employee turnover? Do not maintain the AI models as they are but keep training them to get more effective and accurate over time. Adjust the metrics too if they need re-adjustment with a newer business goal.

What are the Different Aspects of HR Analytics?

Recruitment Analytics

HR teams can use recruitment analytics to determine the places from where great talent is coming, what their basic skills are, what industry majority of them belonged to, and the channels used to reach them. Recruitment analytics, when done right, can enable decisions that could possibly even reduce employee turnover considerably.

Performance Analytics

Strong performers bring a sense of pride to the organization and every organization craves more of the same over time. Performance analytics can help:

1. Identify employees with strong performance and then assign appropriate tasks to them.
2. Identify employees who need to improve at their tasks and whether it is right to retain and train them or let them go.

Employee Engagement Analytics

Employee engagement is a critical measure of happiness and productivity at the workplace. But employee engagement is a more abstract property of a workplace and may not be possible to measure in absolute terms. Employee engagement analytics generally make use of surveys to understand what employees think of the company, the workplace itself, the work culture etc.

Corporate Culture Analytics

Is there an even harder to measure aspect in HR analytics than employee engagement. The answer: Yes, corporate culture is harder to measure than employee engagement. This is because corporate culture is generally only visible in unscripted customer conversations, specialized feedback surveys and voluntary comments and suggestions from employees. Bringing all this together and scoring them is another challenge.

What are the Features of HR Analytics?

HR Analytics is changing the way Modern HR functions and it has moved from an operational unit to a more strategic one, advancing the term ‘strategic HR’ and aligning its efforts with the goals of the business.

1. Metrics and KPIs to measure employee performance, engagement and net promoter score, to help take proactive steps to improve workspaces and company reputation.

2. Data visualization tools that help visualize the presented data in a simple and easy-to-understand format, so that decision-makers are more empowered when they make decisions.

3. Diversity and inclusion metrics help inform stakeholders about the backgrounds the employees come from and the extent of diversity in the company so that they can take steps to improve it.

4. Recruitment metrics such as cost of hire and time-to-hire help arrive at decisions to reduce them considerably over time.
5. Skill gap analysis helps identify present gaps in employee skills and what they need to be trained on to acquire the skills necessary for a new job.

6. Succession planning is another much appreciated feature of HR analytics, where it helps with deciding who will be the next manager/leader of a team/company based on previous performance and current demands and skills expected from a leader.

What are the Benefits of HR Analytics?

Improved hiring decisions

HR analytics greatly improves hiring decisions. It lets you get all the information you need of the candidate in a snap and performs a drill down on the data letting you glean valuable insights that will help you hire the candidates with the right skills.

Increased efficiency in the hiring process

The hiring process is more streamlined now due to HR analytics. Recruiters can now target certain locations and channels which contribute more talent. This greatly increases the overall efficiency of the hiring process.

Improved training

The training process is more streamlined too, thanks to HR analytics. Mentors can now go over the performance management system and get valuable insights around key skills and areas that need improvement.

Increased workforce productivity

The productivity of the workforce has also increased a lot because of HR analytics. It’s possible to track every employee’s progress and suggest changes that may benefit them. Thus, they would be able to contribute to the company’s profits.

Improved workforce planning

The planning of the workforce requires meticulous planning. At least it used to need, but HR analytics has simplified that a lot. With HR analytics, your team is better prepared and can make use of staffing solutions for lean periods or off days when people take a break.

Reduced employee turnover

HR analytics greatly reduces the employee turnover. It does so by helping organizations understand which employees are leaving and why, what the attrition rate is for new employees and why is so high or low etc. These insights will help organizations design strategies that lets them be better prepared for such unwelcome scenarios.

Supporting internal mobility

People within the organization can move to new job roles quite easily because of the insights that HR analytics provides. It can guide managers in deciding which employees can be migrated to another team that best makes use of their skills and how to train them if they don’t have those now.

By enabling internal mobility, organizations can rest assured that the cultural fit will continue to be great, especially if the employee has been working with the organization for a longer period.

How HR Analytics can Transform the Workplace?

HR analytics can give a handy boost to the recruitment process in your organization, increasing its efficiency and freeing up more time for the HR teams for some strategic initiatives like skill gap analysis and succession planning, which are also supported by HR analytics.

Employees work better in the roles they excel at, all thanks to HR analytics. It can even measure employee engagement levels to give an idea of how happy and satisfied they are with work and work-life balance.

Closing words

If data is the fuel, then HR analytics is the engine that drives the organization to greater heights. Facing an HR challenge that HR analytics or your HR team cannot solve? Or think you could use a second opinion above the insights your analytics tool gives you.

We at Alp Consulting are here to act on your behalf, be it boosting employee productivity, a faster HRMS or much better workforce planning. Talk to us today.

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