Ways HR Data May Improve Your Bottom LineTechnology is advancing at a pace that has never been seen before. With this continuous growth in technology, data analytics is becoming more prevalent and possible in just about every area of business. Human Resources (HR) has historically been seen as more of a ‘paper pushing’ area of business with payroll, hiring, firing, and compliance being the main areas of the industry.
However, within the last 10 years HR has become more strategic in focus and the use of data analytics in HR is quickly turning into a hot topic. Many people might find it bizarre to use data analytics in such a people-focused profession; however, there are huge financial savings for companies that choose to do so. Here are some areas where this can happen:
The Marriage of Big Data and Tax Credits – Many companies have been historically unable to tap into the HR-related tax credits available. With big data, these credits are more able to be used to financially boost the company.
Managing Benefits and Health Care – The cost of healthcare benefits is a large cost for businesses. These costs can be reduced by using data to incentivize healthy behaviors and manage healthcare benefits with a financial intelligence in-mind.
Identifying Retention Risks – Replacing employees is an extremely high cost to an organization. Some employees are more costly to replace than others. Using HR Data can help curb some of the expenses related to retention.
Employee Engagement – Employees being disengaged in the workplace can take a high toll on productivity and business outcomes. This high cost can amount to millions or billions of dollars for an organization and using HR Data could reduce some of that cost.
Key Points
There are more ways to use HR Data than just those listed in this article.
HR Data can be expensive to use but can also have a substantially high ROI.
Discussion Questions
How can a business’s MIS department be most beneficial in using HR Data to reduce costs?
What can a business’s HR department encourage objective decision-making through data?
What might be some of the challenges of using HR Data to make decisions?
