8 Analytics terms every HR should know in 2022

The moment we hear HR Analytics, the first things that hit our mind are algorithms, data mining, AI, or ML Yes, these are some of the lingoes that are mostly used by human resource management, as they do in other industries. But how many HR professionals are familiar with such terminologies is the next big question. Ground-breaking digital innovation and new-age technologies have not only powered HR functioning but also the way they think. Let’s try and understand how they impact human resource managers to become more agile and futuristic keeping up with the trends and advances both at the bottom line and macro level in the HR realm.

Data Mining

The word data mining is self-explanatory as it involves the act of mining. You know how metal miners work! Dabbling in the dirt, digging deep into the earth, and breaking and cutting to find out the precious resource. Similarly in data mining, your rig out for raw data and convert them into qualitative and tangible information to understand patterns of employees, customers, or any event. Data mining can be extremely useful for HRs as they can evaluate the pattern of employee behavior to fuel organizational performance and growth, but sadly according to research over 95.4% of data has been underutilized by companies globally.

Machine Learning

Machine Learning is one of the tools in the data mining process. This method can actually help your computers analyze data and identify patterns and it acts as an automation tool for computers and other systems to absorb new information on a particular event or person. ML is more focused on software development that has the capability to change when exposed to new information or data, thus enabling the computer to learn automatically.

Decision Tree

A decision tree is a model that has decisions and possible consequences of those decisions. This powerful tool enables HR to make decisions both in the near term and future. It is one of the critical tools that help you predict future events from the existing data. HR professionals can optimize this tool to understand the business results from the decisions made in collaboration with the C-suite leaders.

Data Security

Every organization gathers information from others from websites or platforms. But what is the assurance that they would use your information for a productive purpose? This is where data security plays a big role. Human Resource professionals hold key and confidential information of a company and if there is no firewall or data security fenced, then the company data may be malicious dark web intruders for a fraudulent purpose and tamper the ownership of data.

Structured and Unstructured Data

Structured data offers more precise direction to HRs as they deal with many departments in a company. Structured data enables human resource management more effective as they could assess information to make real-time decisions. Unstructured data is in stark contrast to structured data where it can consume time and delay decisions as they cannot be analyzed accurately. Recruiters who engage with the decision-making teams of managers and top executives need this knowledge to convey a clear business picture for future success.

Algorithm

One of the first imperatives that arise in human resources is to solve business problems and operational inefficiencies. How you do that is by leveraging the new-age algorithms that help you follow a set of rules to solve a particular problem. Instructions are more important as they can reduce stress on time and redundancy.

Cleaning Data

The HR functions today are more to deal with data analyses to enhance employee retention, engagement, work culture, interview, and business performance. For successful analyses, you need clean data. Not every piece of data that HR has is clean but old, corrupt, inaccurate, and perhaps unused. In order to have filtered data, all these data need to be cleansed and this is one of the methods that lead to obtaining precise information for informed business decisions.

Workforce Analytics

Talent is key to organizational success and HR to achieve that goal needs workforce analytics that provides deeper insights into the prospective employee. This model is applied to provide ROI evidence so as to make informed talent decisions and also helps plan the future of work.

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