The accumulation of worker-related information has evolved into a key tool for making predictions about individuals and larger patterns of employee behavior. Many organizations are ready to adopt advanced analytics into their everyday decisions, and they’re on the brink of taking the first step.

The Power Contained Within Workforce Analytics

As data storage becomes progressively cheaper, many businesses are beginning to recognize that they’re sitting on a hoard of insightful information that can exponentially drive their business. Meanwhile, companies that have staked out leading positions, technologically speaking, are hungry for as much additional data as they can possibly get.

TechRepublic highlights Google as a leader in this area. Since before 2013, Google has been using HR Analytics to “determine the characteristics of good leaders, design the most productive work environments, predict which employees are most likely to leave the company (and) which candidates have the highest probability of succeeding,” as well as forecast future hiring needs and increase diversity in hiring.

When we explore how workforce analytics can increase productivity, the answers are abundant and impressive. Below we’ll detail some of the benefits.

Strengthens Recruiting

The international law firm Allens used contextual recruiting, derived from data about candidates’ demographics and educational backgrounds, to yield deeper diversity in candidates. Miriam Stiel, partner and head of the intellectual property group at Allens, commented that “Candidates from disadvantaged backgrounds are 50 percent more likely to be employed at firms that use the Rare content recruitment system.”

Streamlines Hiring

Data from industry hiring patterns contains valuable insight on how to improve job postings and attract exactly the kind of candidates that your organization seeks. It facilitates an analytical process that takes into account an assortment of variables, including location, job duties, and industry trends, as well as historical data on cost per hire and time-to-fill figures.

Reduces Turnover

Employee churn is an expensive fact of life for every company, and reducing it is an ongoing challenge. Predictive modeling helps employers define the characteristics of a successful candidate and reduces turnover by matching candidates with jobs that are well-suited to their unique skill sets. The software uses profiles to identify traits characteristic of high performers and eliminates any unconscious biases that the hiring manager may have. Drawing on current employee data for predictors of productivity, recruitment analytics also enable new candidates to be scored against the traits of current high-performing employees.

Optimizes Employee Engagement

One key to employee productivity lies in the engagement levels of employees. Gallup reports that only one-third of American employees are engaged in their jobs, while over 50 percent are “just there,” not really interested in what they’re doing. More disturbingly, the Gallup poll finds that 16 percent of workers are actively disengaged, possibly hunting for a new job or even preventing their co-workers from being productive.

These figures show how much room for improvement currently exists, and MIT professor of management Emilio J. Castilla points out that workforce analytics are perfectly suited to contribute to that improvement. He writes, “Leaders need to be extremely proactive in trying to understand what is happening with employee engagement and how the company can take advantage of data collection and analytics to continue to be successful in engaging employees and creating quality jobs.”

Identifies Patterns

As every HR professional knows, the art of managing human capital is not limited to hiring the right people. Forecasting how many people will be needed within a given window of time is equally important, and workforce analytics provide value here as well. Based on historical patterns of demand, the analytical software can run simulations of possible economic scenarios to predict short-term and long-term staffing needs.

Legal Issues Surrounding HR Analytics

Naturally, there are legal issues attached to collecting information about current or future employees, so it’s important to be mindful of these potential hazards. In order to safely harness the power of workforce analytics, your company should abide by the following cautions:

Make sure that you’re following legal and ethical procedures.

Ethics and privacy issues emerged as workers’ primary concerns at a recent leadership conference attended by Tracey Smith, president of analytics consultancy Numerical Insights. Smith observes that even if companies have access to that information, it’s important not to integrate it into specific predictive HR models. Violating the federal HIPAA laws surrounding personal health information can result in significant penalties, and you’ll need to use aggregating and anonymizing tools in order to avoid a legal quagmire. Smith gives an example (related to pay rates rather than health) in which individual worker salaries were anonymized into pay-level tiers, allowing predictive algorithms to do their work without endangering individual privacy.

Businesses have to walk a fine line, encouraging their workers to engage in positive health habits while not discriminating against people for health issues beyond their control. The use of individual health information becomes highly controversial and potentially risky for organizations when it fuels prediction models or guides decisions on which employees will be most profitable to train, promote or lay off.

Make sure your technology can support your data collection.

Private cloud storage is a good start for protecting your sensitive data, and HR analytics must be deployed with strong safeguards for employee privacy. The ACLU calls employee privacy “an endangered right,” and your brand as an employer can easily be damaged by just one high-profile case of leaked personal worker information. Any new digital solutions that involve your HR department must be carefully vetted for the robustness of their security measures as well as their legal viability.

Practical Needs of Data Analytics

As companies play the game of digital “catch-up,” information sometimes starts out in simple formats such as spreadsheets. This might work in the very short run, but you can’t turn raw data into actionable information unless you’re feeding it into an analytical platform that utilizes big data visualization. The ability to visualize data is at the heart of digital transformation, and it requires your organization to undertake an entirely new relationship to its data stream.

The use of HR analytics is easily misunderstood, and while some of these analytic operations go unnoticed by workers, rumors about new software innovations will inevitably circulate. It’s imperative to get out in front of any concerns that employees feel and to demonstrate to your whole staff that the purpose of HR analytics is to create a more engaged, sustainable workplace. The Wall Street Journal raised alarm with an article entitled “Bosses Tap Outside Firms to Predict Which Workers Might Get Sick,” and Entrepreneur later addressed the controversy. They present the potential volatility of HR analytics, and point out that companies must “always be open and honest with employees about how health data will be used, and analyze organizational health holistically.”

Hire experts to analyze data, extract insights and present to the company.

If your HR department is still largely operating in an analog world, you’ll save all stakeholders a huge amount of time and stress if you bring in some experts to lead the way. The effectiveness of your company’s analytics depends on highly trained analysts and the proper analytical tools to decipher and read through the data that your company requires to make it’s best business decisions. We’ve found that it’s also essential to ensure one clear vision of intelligence across your entire organization.

Your managers and executives will also benefit from clear explanations. Their willingness to make the investment needed to bring effective workforce analytics online may hinge on their receiving a clear overview of its benefits, and your own IT and HR departments may still be scaling the learning curve themselves.

HR Analytics Is a Tool, Not a Replacement

A few years ago, Google experimented with a data-centric approach to deciding who should be promoted. Google pitched this to their hiring committees, pointing out that the analytics tool tested out stable and could relieve the committees of up to one-third of their work. To the company’s surprise, the hiring committees rebelled vigorously, and that particular tool was never activated in the way it had been envisioned. Instead, Google’s People Analytics team now uses the algorithms to give managers better information so that human decision-making is strengthened with new insight.

Advanced analytics is clearly a necessary tool in today’s business landscape and the benefits with respect to the efficient management of human capital are too obvious to ignore. When these tools are integrated on a solid legal basis and with clear respect for employee privacy and professional HR skill, they lead can to new levels of productivity and engagement.