As the HR of a leading company, I look back and think of how easy and fulfilling HR’s role has become. It’s more than just handing out paychecks and recording attendance. I take pride in playing my part in improving workplace conditions and other areas of my organization.
However, I’ll be honest, none of this would have been possible without the improvements in the field of HR analytics. We all have data, but it’s useless if it doesn’t give us a direction or a common goal. Fortunately, I see HR analytics fill this void.
Analytics in HR is a broad field that includes various data, which result in different conclusions, which help us decide the organization’s direction and improve the overall experience. But, I feel sad when people neglect HR analytics’ importance for the organization. Nevertheless, I share my professional view on the effective approach and challenges of HR analytics for the organization today.
Also Read: Explaining the Negatives Positively – How to Talk About Work- Related Issues with Employees
The Three Essential Steps Of HR Analytics
Just like everything, HR analytics is a systematic process. I divide the process into three steps, making reaching conclusions and making decisions easy for my team. For ease, I explain my approach, so keep reading.
First Step – Data Collection
Data is the base for any further action. It’s like “sugar, spice, and everything nice.” The data collection process is vast, so there’s much to focus on, rather than only collecting heaps of data.
There’s a saying, but I focus more on chewing as a synonym for data-collecting capability. Let me help. Improving your data handling capability is easy; invest in good cloud software with loads of storage space, and you are done halfway. Furthermore, use good security software that protects against hackers and cyber threats.
Once you have the data all gathered and safe, now is the time to look for common trends. Many people find this part hard, but don’t worry; I shed light on this part with my experience, so keep scrolling for more enlightening knowledge.
Second Step – Data Analysis
Pro tip one for analysis: Break down your data into parts to make your work easy, depending on how it explains and what it tells. I sort my data into three types, namely: descriptive, predictive, and prospective analysis. This approach helps me work with one part at a time.
Descriptive analysis tells me about past trends. Predictive analysis tells about future trends, and prescriptive analysis tells me actions to improve the situation.
Ultimately, the huge jigsaw of data begins taking shape using this approach, and my team and I move to the next step, data visualization.
Third Step – Data Visualization
The final cherry on the top is giving your findings shape, known as data visualization. The process involves converting your analysis into bar graphs and charts, making it attractive and easy to understand.
When visualizing data, understand the people you address. For example, using simple bar charts and graphs to address business stakeholders. No need for hard and wordy pivot tables or other detail. Let the images talk.
Board meetings are there for reaching conclusions rather than understanding complex graphics. In a crux, make your images and text easy for everyone to understand and make decisions.
Let’s move on to the next part, which discusses HR analytics’ challenges.
Challenges For HR Analytics
I see many challenges for HR analytics in the present and the future. The most notable ones are data security, quality, and talent acquisition.
Challenge 1 – Data security
Data is an asset in the 21st century, making protecting it important. HR data includes private information, like employee pay, bank account numbers, minutes of board meetings, and much more; if the data falls into the wrong hands, it can spell disaster.
Many things lower the risk of data compromises, such as firewall protection and security certificates. If you still have problems, take help from an information security consultant. Also, keep a data backup to help you continue with your work.
Challenge 2 – Data quality
Data quality also plays a role in the results of your HR analytics practices. The more detailed and relevant the data, the better its results. To improve data quality, use simple questions without complicated jargon. Remember, everyone doesn’t score well on their IELTS test.
Also, keep a simple method for collecting data, don’t use long questionnaires, and ensure that your software is responsive. Most respondents hate answering long questionnaires, so they may fake information just to get done with it.
Challenge 3 – Talent acquisition
Hiring the right talent is equally important. You need skillful people who manage tons of data and issues which arise along the road. So, hire people with the relevant experience, commitment, and drive to succeed and help the organization. Like they say. Persistence is important.
However, just handing in a large paycheck won’t get the job done; there is more than meets the eye. Give your team a work environment which helps their physical and mental well-being and encourages work-life balance.
Also Read: HRIS – HR Information Systems – A New Approach To Human Resources
Conclusion
HR analytics is a blessing if used the right way. The process helps with recruitment, addressing employee issues, and making decisions that benefit the organization. However, the field has many challenges, like maintaining data quality and security and hiring competent and dedicated talent.
