Understanding people analytice & HR analytics

People Analytics

People analytics is defined as the deeply data-driven and goal-focused method of studying all people processes, functions, challenges, and opportunities at work to elevate these systems and achieve sustainable business success. Increasing job offer acceptance rates, reducing HR help tickets, and optimising compensation are just a few ways in which people analytics is quickly becoming the new aspect of HR. 

People analytics is essentially, gathering and assessing people, leading to better decision-making through the application of statistics and other data interpretation techniques. Smarter, more strategic, and data-backed talent decisions are thus closer at hand, and this is applicable throughout the employee lifecycle – from making better hiring decisions and more effective performance management to better retention. People analytics has evolved considerably from when it was first used in organisations in the mid-1900s. There has been a clear transition from prescriptive analytics to predictive analytics, with which organisations can now be better prepared to face the dynamism of their operational environment and be proactive rather than reactive. 

The Process of People Analytics today is a lot more intuitive and predictive.  And involves the following steps.

Benefits of people analytics

organisations have made moderate or significant progress in people analytics in the past decade and stands great significance in day to day organisational activities. People analytics not only gives organisations a competitive advantage but has multiple benefits,  such as

(1) Making data-driven decisions 

By analysing hiring data and improving the recruitment process based on that, organisations can increase recruiting efficiency by more than 80% and decrease attrition rates by up to 50%.

(2) Realising cost savings 

Organisations can achieve this, through reducing turnover with an optimised workforce planning. It enables organisations  to address concerns and work on other areas, such as future hires for at-risk roles basis the study of the current trends in hiring as against future requirements.

(3)Closing skill set requirements

People analytics permits organisations to understand workers’ current skills, the future skills needed according to organisation need and thus bridges the talent gap.This can build a pipeline of talent and create development programs based on the future needs of the business.

(4)Improved performance 

Dashboards and trends that highlight specific problems, including collaboration, workload, diversity and inclusion, workplace risk assessments, all contribute to optimising performance. 

People analytics is a new way to make evidence-based decisions that improve organisational performance. Initially, most organisations have been focusing on the attributes of individuals, rather than on their relationships with other employees.If they harness relational analytics, they can estimate the likelihood that an employee, a team, or an entire organisation will achieve a performance goal. 

HR Analytics

HR analytics is defined as the process of measuring the impact of HR metrics, such as time to hire and retention rate, on business performance. Human resources is a people-oriented function and not one where the HR team’s contributions are limited to extending offer letters and onboarding new hires, human resource analytics can extend a whole new dimension. When used strategically, analytics can transform how HR operates, giving the team insights and allowing it to actively and meaningfully contribute to the organisation’s growth.

“HR analytics is a methodology for creating insights on how investments in human capital  contribute to the success of four principal outcomes

1. generating revenue, 
2. minimising expenses, 
3.  mitigating risks, 
4. executing strategic plans. 

This is done by applying statistical methods to integrated HR, talent management, financial, and operational data.

HR analytics specifically deals with the metrics of the HR function, such as time to hire, training expense per employee, and time until promotion. 

HR has access to valuable employee data, the data useful for the HR function can be used to improve employee performance, the employee experience, and in turn, maximise business outcomes. HR analytics could be used to measure investments in reskilling, which will deliver the right competencies to support a new revenue model, using data-driven insights to modify the training offering.

Here are some common metrics tracked by HR analytics: 

• Revenue per employee: Result calculated by dividing a company’s revenue by the total number of employees in the company. This indicates the average revenue each employee generates. It is a measure of how efficient an organisation is at enabling revenue generation through employees. 
• Offer acceptance rate: The number of accepted job roles divided by the total number of job offers given during a certain period. A higher rate (above 80%) indicates a good ratio. If it is lower, this data can be used to redefine the company’s talent acquisition strategy. 
• Training expenses per employee: can be understood by dividing the total training expense by the total number of employees who receive training. The value can be determined from measuring the training efficiency. Poor efficiency may lead you to re-evaluate the training expense per employee. 
• Voluntary turnover rate: Voluntary turnover occurs when employees voluntarily choose to leave their jobs. It is calculated by dividing the number of employees who left voluntarily by the total number of employees in the organisation. This metric can lead to the identification of gaps in the employee experience that are leading to voluntary attrition. 
• Time to hire: The number of days between approaching a candidate and the candidate’s acceptance of the job offer. Just like time to fill, data-driven analysis of time to hire can benefit recruiters and help them improve the candidate experience to reduce this time. 

For HR professionals to get started with using HR analytics for data-based decision making, the following can be formulated:

1. HR professionals must prepare their teams and organisations for a workflow-driven by analytics. This is a crucial aspect of HR’s digital transformation as well as company-wide digital transformation. Getting the team started on small projects and asking them to create the reports that they will discuss with businesses is a  way to begin. 
2. Bring in data scientists The data scientist is expected to become an integral part of HR teams. They are best suited to assess the viability of an analytics solution. They can also ensure the robustness of statistical modelling. As the role of HR business partners and generalists evolves to include skills such as data strategy, analysis, and communication , the data scientist will serve as the coach, mentoring their colleagues across HR in how to understand, and apply the insights. 
3. The sort of data collection that HR analytics uses is governed heavily by compliance laws. Some legal considerations to keep in mind when implementing an HR analytics solution would be Employee privacy and anonymity, Consent from employees about the amount and type of data being collected, Establishing the goal of data collection and informing employees.

IT security when using third-party software to run HR analytics, Location of the HR analytics vendor – with whom the data will be stored – and their compliance with local laws Collaborate with the legal team of your organisation to ensure ethics and compliance norms are followed.

HR analytics offers some undoubted benefits. It allows HR teams to significantly streamline processes that reduce costs, reduce attrition, and consequently improve the bottom line. IT assists in exploring the human aspect of human resources without spending time on tracking mountains of data from multiple sources.