Did you know that CIBIL credit score, matrimonial websites, and Google all use predictive analytics to predict user behavior?
While CIBIL credit score clearly tells financial institutions if a person is good with debt or not, the matrimonial sites use your behavior and predictive analytics to match you with prospective grooms and brides. And Google analytics predicts website traffic, usage, and how the user behaves.
Now, imagine implementing this in the HR department. Wouldn’t it be great to know how employees will turn out just based on their behavior? You will be able to retain more employees and reduce the resources your company is spending every year on hiring.
HR Predictive Analytics
Predictive analytics is now everywhere. However, in HR, although most companies talk about it, the actual implementation is low.
If you implement predictive analytics in HR, it would be like predicting the success of an employee. Many companies even believe that these analytics help them keep toxic and incompetent employees at bay.
Similar to how your CIBIL score is calculated to predict if you are a creditworthy person, predictive analytics in HR can tell if an employee is worth hiring.
Let’s Consider an Example
Let’s say you are analyzing the frequency and amount of customers in a busy market. If you relate it to weather and form an analysis of the market situation, it would look something like this.
|Day||Weather||Market Situation – Amount of Customers|
|Day 4||Hot||Very low|
**Above values are taken only as an example and do not contain actual statistical data.
Now, looking at the above table, it is evident that the frequency of customers is low on hot days. People are less likely to visit the market when it is extremely hot outside. Using this as a reference, you can easily predict what is the customer pattern.
However, this data may seem irrelevant and small when compared to data and information available in the HR department. Let’s see what would actually happen if the data is much more than this.
Analyzing the Decision Tree
The decision tree is a common algorithm used in predictive analytics. It contains conditions, possible decisions, and their relevant outcomes. In simple words, using the weather and previous behavior, we can actually predict if customers will arrive on a particular day.
When this data is implemented in HR, the predictions change such as will an employee stay, what is the progress, and identification of toxic employees.
Implementing HR Predictive Analytics
HR predictive analytics has a wide level impact on the organization. Once this structure is implemented, the human resource department can analyze and predict a lot of things such as:
- If a policy will be well received by the employees
- If an employee will stay for long-term in the company
- If an employee is involved in toxic behavior
- If an employee is working efficiently
- Performance of a team
Some companies evaluate employee retention based on risk scores. For instance, if an employee just got a promotion but the rise was low, he is more likely to leave. Considering the previous behavior, the predictive analytics would give a risk score. The HRs can then take measures to retain the employee.
Predictive Analytics: Enhancing HR Functioning
Imagine being able to predict employee behavior before the bomb drops on you suddenly? It would be like being prepared for the worst. You would know the employees who are not good for your office culture and performance graph of every staff. Decisions become better and retention becomes easier. Some organizations, in fact, use predictive analytics to retain customers and predict the working pattern.
Hence, this technological tool is an amazing opportunity for the HR ecosystem. It would make things stress-free and save companies the cost of replacing resources.