Analyze This: A Primer on People Analytics
“You can have data without information, but you cannot have information without data.” — Daniel Keys Moran
If yours is like most successful businesses, you’re using analytics to drive your development, target your customers, and optimize your operations, so why aren’t you using them to maximize your company’s human potential?
People Analytics, also known as Talent Analytics, HR Analytics or Workforce Analytics, is possibly the newest trend in Human Resources, but it’s still far from commonplace. This primer will explain how you can leverage business intelligence and analytics tools to drive your employee engagement goals, as well as secure HR’s seat at the table in critical executive discussions.
If you’d like to take a deeper dive into the rewards that People Analytics can offer your company, we welcome you to visit us at Honestly.com to learn more.
How Talent Analytics Work
As new tech streamlines employee management, today’s Human Resources departments face increasing pressure to innovate. HR Analysts use computer software packages called Human Resource Information Systems to collect information on topics such as salaries and desired skills while informing budget line items like retirement plans.
Human Resource Information Systems have a wide range in functionalities and specialties. BambooHR’s user-friendly online suite is optimized for use in small- to mid-size organizations, while Workday’s enterprise-class solution is designed to effectively manage global businesses.
By gathering data on employee efficiency and other workplace functions, talent analytics helps HR departments establish a clear connection between their initiatives and business outcomes. With this data on hand, HR can create strategies that boost business through improved personnel acquisition, compensation optimization, and employee development.
“The value of a business is a function of how well the financial capital and the intellectual capital are managed by the human capital. You’d better get the human capital part right.” ― Dave Bookbinder, The NEW ROI: Return on Individuals
People Analytics Capabilities
The capabilities of people analytics are divided into three levels. It’s important to note that most businesses are only able to perform Level 1 analytics, with few having the infrastructure for Levels 2 and 3.
Level 1a: Descriptive Analytics
In Level 1a, data collected is used only to describe concepts related to Human Resources, or to record changes over time, with no further analysis tied to the data.
Level 1b: Descriptive Analytics Using Multidimensional Data
Level 1b is similar to 1a, but multiple data sets are compared and contrasted in order to observe correlation. Again, the comparisons are only used to describe concepts, with no further analysis.
Level 2: Predictive Analytics
Predictive Analytics uses high volume, high-quality data sets, along with special technology and expertise, to predict future trends.
Level 3: Prescriptive Analytics
Prescriptive Analytics uses mathematical and computational sciences to provide in-depth decision-making assistance based on Level 2 predictions.
Metrics
There is an almost endless array of metrics available for use in HR analytics, from areas like Performance and Recruitment to Revenue and Employee Training. Even so-called “Soft Skills” metrics, such as Communication, or Teamwork, can be gathered through specialized surveying and applied to benefit your organization. The key to successful analytics, as always, is to emphasize quality as much as quantity in these myriad data sets.
Why HR Analytics Matters
”War is ninety percent information.” ― Napoleon Bonaparte
By combining and visualizing data, HR analytics can be used to benefit businesses in ways that could previously only be guessed at. Talent and Recruitment Analytics, for instance, can help you to electronically sift through thousands of CVs and derive the best candidates. Training programs can be made more productive and efficient. With strong data, employee engagement can be addressed more efficiently, financial compensation methods completely revamped, retention levels increased, and much more.
Case Studies
In the near future, analytics usage will be par for the course for Human Resources standard practices. To get us there, it’s helpful to take a look at some successful work done by pioneers in the area:
In one well-publicized example, Hewlett-Packard used data science to determine “flight risk” (likelihood to leave the company) for its employees. While the program is said to have saved the company up to $300 million, the negative PR once employees realized what was going on is a good reminder on the importance of sensitivity when applying analytics to a human problem. That said, the case serves as an excellent early example of effective People analytics usage in practice.
In a more positive use of HR analytics, AMC Theaters, a major American movie theatre chain, recognized the importance of staffing in providing a superior customer service experience. By using Talent analytics and employee profiling to identify the core traits shared by their ideal customer service candidates, they remodeled their hiring process to predict employee success. The program ultimately served to increase employee engagement and customer satisfaction while reducing turnover.
Finally, a more in-depth example comes from Kaiser Permanente, the American healthcare consortium. The company successfully undertook two major analytics projects to improve company processes. Supply and Demand Forecasting helped them to predict future critical business drivers in relation to market forces, while Leadership Behavior Modeling analysed high-performance team indicators. Together, the processes helped them significantly in closing anticipated gaps in their service delivery.
Along with success stories like those above, there are other major trends showing promise in the field. Blind Hiring, for instance, uses analytical algorithms to calculate candidates’ likelihood to succeed in a given role. The use of computers with minimal human interactions both decreases human bias and increases diversity. New and varied data sources are also consistently being embraced, and forward-thinking companies are moving toward an increased focus on wellness in the workplace. These shifts and more are all solid indicators that workplace data analysis is fast becoming a vital part of effective HR strategy.
Challenges
The difficulties in collecting and applying data analysis in the workplace are significant and should not be overlooked. As such, it’s important to tread carefully when expanding the role of data in Human Resources. One hurdle is that with so many data sources available, it takes expertise to collect and clean data (to separate the most valuable metrics from the rest), then integrate those data fields with one another in a reliable way.
”Not everything that can be counted counts, and not everything that counts can be counted.” ― Albert Einstein
Some Human Resources managers are resistant to using talent and recruitment analytics. Instead, they would rather trust their gut–not an inhuman algorithm.
In addition, hiring the right talent for operating Human Resource Information Systems and performing HR analytics can be exceedingly difficult. While many HR leaders are equipped to oversee them, the operation of analytics tools frequently require a combination of HR knowledge and skills in data modeling, computer science, statistics, and math.
Currying executive support for a shift towards analytics can also be difficult, as cost considerations can vary wildly. Lingering skepticism and an outdated lack of confidence from HR managers and executives can also hamstring progress before it has a chance to begin.
With these challenges in mind, it can be helpful to gather as much information as possible in order to enter the realm of workplace analytics with the necessary conviction to succeed. If you’re considering doing so,take the first step by downloading our ebook for more in-depth information, and for details on how we can help.
People analytics has become an essential HR toolkit in and of itself, with the ability to yield positive returns for every organization. However, data analysis, interpretation, and management are complicated enough to require companies to approach the field with careful determination. Success relies on understanding that its potential impact on decision-making, rather than the mere quantity of data itself, is the key to successful analytics.
Through proper usage of analytics, HR departments can take a lead role in defining key areas of employee and performance objectives through real data, rather than conjecture. And by recognizing and fulfilling its role as the most important data hub of a business, HR has the potential to communicate its value throughout any organization. After all, Human Resources represents people, every company’s most valuable resource.
