HR is seldom considered to be a “data centric” department. Its function in an organization is usually considered to be more about human capital management (HCM) using “soft” management skills.
The past few years, however, have seen an increasing trend of utilizing data analysis for better management of people. From personality surveys at hire through performance reviews and exit interviews, companies are gathering more and more data on their employees.
An Upward Trend for Data Collection & Use
The use of data analytics in corporate decision making has been consistently increasing, and with good reason: the data backs up this strategy’s success. Sierra-Cedar HR Systems Survey for 2016 found that “Top Performing” organizations are those that are able to put decision support analytics tools directly into the hands of managers at a more frequent rate. Giving management the ability to examine and use HR data directly appears to give organizations a significant competitive advantage: organizations who use HR data in their management decision making report revenue per employee of 26% higher than organizations that do not use HR data1.
There are many software systems in the market that can help companies gather and analyze HR related data. Most organizations already track at least some of the following metrics:
Recruitment, hiring, and training costs
Attendance, leave, and absenteeism
Workplace safety incidents and losses
Retention, engagement, and productivity metrics
Collection is Good, Analysis is Even Better
In today’s fast-changing business environment just tracking data and metrics and responding to immediate needs is no longer sufficient. To truly get the benefit of HR data, organizations have to take the next step and gather insights that translate into short, medium, and long-term business strategies. This analysis can help them gain competitive advantages and can actively contribute towards increasing revenue and profits.
Some concrete examples of how insightful HR data and analytics have directly benefited a company’s long-term business strategy are:
Xerox developed a personality test as a predictor of success when hiring for their customer support representative positions. After they began using it in their hiring practices, their turnover rates fell 20%.2
At LinkedIn, the HR team employs data scientists to correlate things like the length of an employee’s review of his or her manager with how happy that employee is. These and other data points allow them to create a employee “heat map,” identifying when an employee may be suffering burnout. This enables LinkedIn to transition or modify the employee’s roles and responsibilities in order to retain him or her, saving money on turnover, recruiting, and retraining.3
At Google, they use a hiring algorithm to analyze which candidates have the highest probability of succeeding on being hired. They also use a “what-if” analysis to predict which employees are at risk of leaving, allowing them to intervene and improve retention. Their data-focused HR practices have contributed to their overall success of being able to generate $1 million annual revenue and $200K in profit per employee.4
As these examples illustrate, it is what a company does with its HR data and how it translates into actionable tactics that are key. HR has a huge volume of data available, which can add to an organization’s struggles if it is not easy to organize and analyze. Efficient, effective analysis is vital to reap the true benefits from any investment in HR analytics software. Whether an organization has too much of data pouring from all sides or too little, or incorrect information that needs to be reconciled, data without analysis is worth little.
The solution lies in understanding that both efficiently analyzing data and responding to the trends is an important part of doing business. Some organizations still struggle with a lack of skilled professionals who are able to collect, analyze, and integrate HR data. These companies will have to make the investment in providing the right tools and training for their HR and management professionals. For others, more efficient and effective analysis and application of HR data will be a matter of individual analysis and optimization. There is no one solution that will fit all problems. Each will have to concentrate on some key metrics that are relevant to their industry, the current “as-is” state of their organization, and their short and long-term objectives. What’s important, though, is to know where they want to be as the first step towards becoming a data-centric HR organization.