The 4 type of HR Analytics
Business Analytics is a terminology that can mean a lot to a lot of people. HR analytics helps HR professionals and their organizations improve decision-making with data. It also gives HR professionals the ability to contribute strategically, delivering meaningful insights and contributing more effectively to business results. There are mainly four types of HR analytics methods that an HR professionals can use like descriptive, diagnostic, predictive, and prescriptive analytics.
Why is HR Analytics important?
Although HR has a lot of information about their employees, without analytics it would be raw data. In a large company, this can represent thousands of employees, and their raw data alone cannot identify problems or suggest solutions. HR analytics uses evidence and data-backed models that can help HR understand the reasoning behind what's going on in the business, such as overall well-being, employee engagement, and the amount of training that each team received.
4 types of HR Analytics
1. Descriptive analytics
Descriptive analytics talks about what already happened, or what’s currently happening. Let's say you're tasked with recruiting and retaining all previous year employees in the organization.You may have access to a dashboard or a report that shows the number or percentage of people that have left the organization over the past year. This may be mewled by the business unit, product line or some other delineator.
2. Diagnostic analytics
The Diagnostic analysis shows the causes of the events revealed by the descriptive analysis. In our example, this might be a graphical report showing the ranked reasons why sellers left. The reasons can range from poor compliance with quotas to higher base salaries offered by competitors. The diagnoses reveal the underlying cause of the events presented by the descriptive data. If you know the cause, you know where to focus your efforts to alleviate the problem.
3. Predictive analytics
Predictive analytics focuses on what might happen in the future based on the details of past events. This can be a forecast of employees likely to leave in the next 90 days or in the next quarter. Predictive data is obtained through data modeling, machine learning and artificial intelligence. If you know what is going to happen, you can prepare for it in advance. Just like if you know it's going to rain tomorrow, you can put an umbrella in your briefcase tonight. Likewise, if you know which employees are at risk of running away in the next 90 days, you can advise your managers to approach them now, before it's too late.
4. Prescriptive analytics
Prescriptive analytics is the final and most complex step in the analytics journey that turns predictive analytics into insights into what to do next. A general definition of prescriptive analytics would be the targeted recommendation of decision options and actions based on the results of predictive analytics. It offers options on where and how to act to succeed. You can think of prescriptive analytics like an ott platform for business. It works the same way ott platform suggests movies based on viewing behavior. Prescriptive analytics goes beyond predictive analytics with a more preventative approach to looking to the future. Predictive analytics simply predicts the most likely outcomes of a decision or action. With prescriptive analytics, you can predict what will happen next, why, and what you can do next. It anticipates the most likely scenarios and the interventions likely to bring the best results.
Conclusion
HR analytics is the engine of effective HR planning and decision making. Revealed analytical information provides a more complete insight into what is really going on in the business. It opens up possibilities and opportunities that you wouldn't be aware of. The better you understand the different types of metrics and analytics in HR, the more relevant insights you can glean from the data to help you achieve your business goals. Your ability to leverage analytics allows you to serve your organization more strategically.