The HR department is responsible for collecting some of the most exhaustive and sensitive data in any organization. Unfortunately, many HR departments don’t make proper use of this data.
Data has been described as a game-changer as it gives insights into a lot of things influencing people’s decisions, removes uncertainty, and even helps predict the future. HR departments stand to gain a lot from proper data analysis.
Here is an overview of three examples of how data analysis can help improve efficiency in HR operations.
1. Informed Hiring Decisions
Employees make a critical pillar of any organization’s success, which is why it is important to pick the best people for each position. However, finding good talent is difficult, but essential for success. It is threatened by cut-throat competition. In most cases, however, HR departments usually don’t screen candidates well enough. Data can help change this by identifying valuable traits that may be difficult to uncover from conventional interviews and screening processes.
Gartner, a leading analysis company, is a good experience of how this works. The company used data to identify its employees’ performance determinants based on their hiring decisions.
Data analysis revealed that employees from prestigious learning institutions did not necessarily perform better than those who came from lesser-known institutions. The data also pointed to the individual employees’ grades as the determining factors for success. Gartner went on to make changes based on these findings, and it increased its revenues by $4 million as a result.
2. Unlocking Employees’ Potential
Hiring the best employees is not enough. Every organization should work towards bringing out the best in their employees for its benefit. This is the HR department’s responsibility, and employee data is the best tool for the job.
Everything about an employee – their qualifications, experience, achievements, and even personal traits – affects their performance. HR collects sensitive information about employees, as mentioned, and, as such, has the insights necessary to improve their performance.
One good starting point is getting employees’ opinions and thoughts about workplace affairs. They know the workplace environments well and will have good suggestions that will help improve things, which will, in turn, improve their productivity. The organization can also go the extra mile and try to help employees with reasonable personal issues that may be getting in the way of their work. Finally, there are more ways in which data can help improve in between the starting point and the extra mile.
3. Improving Customer Experience
For companies to get a real-time data analysis, using streaming processing would be ideal. One of the greatest benefits of data analysis is its ability to understand and predict customers’ behaviors. It is the single greatest driving force behind the competition to advance data analysis. To this end, major tech and retail giants, including Amazon, have been accused of exploiting users’ data against their consent to improve their edge over the competition.
Web-users leave a trail of data with every keystroke they type in. For example, you can tell a lot about your customer based on their past purchases. You can then use this understanding of your customer to improve their shopping experience by offering recommendations to helpful products, in addition to other tactics. And this is just the tip of how useful customer data is.
HR departments can exploit customer data to improve their experience without breaking the law. Improving customers’ experience on your platform will make them more willing to make a purchase, and this will increase in your organization’s revenues. Other equally important benefits include improving your brand’s reputation and attracting/retaining more customers.
It is at Your Fingertips
You already have the data you need to make significant improvements in your HR departments and the organization as a whole. All you need now is the best data analysis solution to help you make the most of your data.