HR data analytics: What HR professionals need to know
HR data analytics: what HR professionals need to know
Table of contents
HR data analytics can help small, medium and large companies with performance reviews and decision making. In the past, HR was an operational discipline that mainly focused on administration and logistics, such as payroll, or resolving the odd workplace conflict.
Today, HR plays a much more significant role in the running and success of an organisation, from recruitment and retention, to onboarding and much more. With the growth of remote working, the role has become even more complicated. Thi meanshis means that HR professionals need analytics tools more than ever before.
HR data analytics allows a company to analyse the activities, strengths and weaknesses of each member of a workforce, and make the relevant changes and decisions to ensure every colleague operates to their strengths.
Almost every aspect of a workplace or company in the modern world is data-driven. If you want your company to be successful it makes sense to use modern technologies, like AI, to track and analyse certain aspects of the workplace and allow for quick and easy improvements.
Where HR analytics can help
If your company is dealing with poor levels of staff retention, and a high attrition rate, you can utilise data analytics to find out why this is happening, and how to improve this. Examples may include a change in onboarding and training methods, or better employee support schemes.
They can also be integral to top talent acquisition. One study found that 56% of applicants have encountered a technical problem whilst in the application process for a new role. With top talent already a challenge to come by for employers, you really cannot afford to be losing potential talent to preventable technicalities.
Other benefits of HR analytics include the use of key performance indicators. One study found that only 36% of employees are actively engaged. By applying analytics, and being able to monitor aspects of performance, you are able to pinpoint areas in which certain employees are doing well, and areas where they are struggling. This means they can receive the exact support they need.
How to get started
In order to use HR data analytics successfully, it’s important to follow these four steps:
- Firstly, you need to identify the types of conclusions you’re looking for, the questions and results that are most important to your organisation. Without this, you’ll be looking through raw data mindlessly.
- It’s then important to identify the data, how where you will collect it from, alongside exactly how you will do so, such as through a third party application.
- Following this, the organisation will need a method of data analysis in order to ‘clean’ the data. This means formatting the raw statistics into a language that colleagues will understand. Some organisations may use a data analyst for this. Others may use HR analytics software, a great example of which is Lattice.com.
- Finally, once data has been collated and is intelligible, it can be used for people analytics, to identify strengths and weaknesses of the organisation and/or employees, and gain insight into the best course of action to make improvements to the running of an organisation.
A great example is Learning Record Store. This is a key tool in collecting data and presenting it in an intelligible way, to clearly identify what improvements can be made. For example, it can tell you the percentage of employees that got a question wrong on a training or learning platform, allowing you to focus on educating and informing employees on specific topics, or workplace conduct/biases.
At BestAtDigital, we know the benefits of HR analytics, and we think that a modern approach can be one of the best tools for an organisation’s success.
Although HR data analytics is a relatively new area of practice, it has the potential to transform your HR department from operations management to a department that improves employee retention, aids with talent acquisition, analyses KPI’s and more.