Analyze your organization’s most precious resource.
Ask CEOs what makes their organizations special, and invariably they’ll answer “our people.” Yet CEOs are likely to have reams of data on virtually every aspect of their business except employees. That’s because the packaged applications and tools capable of meaningfully analyzing a company’s work force are relatively new and, until recently, evaluating information on employees was considered more art than science.
Work force analytics is an emerging, fast-growing segment of business intelligence (BI) that promises significant bottom-line results. It delivers fact-based insights into employee activities, business processes and work relationships, which drive business day in and day out. It leads to targeted recruitment strategies, better rates of employee retention, improved productivity and a more motivated staff.
Market intelligence firm IDC pegs the packaged work force analytic applications market at $190 million annually. But IDC analyst Brian McDonough says that figure does not include the billions spent building data warehouses and BI solutions that analyze work force and human resources (HR)-domain data. He calls work force data one of the “four pillars of business intelligence that provide the source for key performance indicators that guide an organization toward its strategic goals,” along with financial, customer and supplier-related data.
The crucial nature of understanding a work force has led many organizations to build custom tools on top of traditional applications to help HR departments gather and track metrics on performance. These solutions have been used for years, McDonough says, particularly in departments like sales. There, data from other systems, including customer relationship management (CRM) and finance software, can be integrated to build models for compensation and incentive programs as well as to establish and monitor sales goals for individuals, geographies, divisions and the company as a whole.
Work force analytics is an emerging, fast-growing segment of BI that promises significant bottom-line results.
As an example, McDonough points to consulting firms, which often depend on work force analytics to match individual skill sets to myriad projects. These companies need to accurately determine what kind of talent is required for each engagement—and for how long—all while factoring in normal staff turnover during a project’s life span. They then need to add finance data to build pricing and profit models for each project and roll those numbers into an overall business forecast.
“The complex nature of the analysis requires robust technology as well as design, implementation and training expertise for a solution to be successful,” he says.
That complexity is daunting for many HR managers, says Susan Cantrell, CEO of The Cantrell Group LLC. She helped develop Accenture’s Human Capital Development Framework, which is used to analyze an enterprise’s personnel from top to bottom to glean information on everything from executive leadership to line worker productivity. The framework also pinpoints processes to improve employee performance. Cantrell and David Smith, director of Accenture’s Talent and Organization practice, co-wrote the book “Workforce of One: Revolutionizing Talent Management through Customization,” set to be released in January 2010.
The essential data warehouse
According to Cantrell, HR departments have been slow to embrace analytics for good reason. Most are only now getting access to integrated systems with data about employees and developing a common taxonomy. These developments are eliminating roadblocks and helping accelerate adoption. Another impediment is that HR professionals have traditionally used fad, fashion or faith to make judgment calls on employee issues, she adds.
Historically, HR departments have relied on qualitative data, such as performance reviews or exit interviews, to make decisions. Although qualitative analysis is essential, relying on it alone won’t enable a business to achieve its goals, Cantrell observes: “Without empirical data, you are taking a shot in the dark.”
A key component to housing, maintaining and querying the necessary data for work force analytics is a data warehouse, according to McDonough and Cantrell. “A data warehouse is essential for a robust analytical capability,” Cantrell notes.
Finding meaningful data for work force analytics will vary by organization, but potential sources include financial and payroll systems. CRM tools can also be a gold mine of information about individual and group activities and their performance. Other sources include recruitment and hiring data, employee-training results, customer satisfaction surveys, internal focus groups, performance appraisals and exit interviews. The data warehouse can even be populated with external industry data so an organization can compare its efforts with those of others, such as the number of hours or amount of money spent on training.
Smile for success
Employers should be creative when implementing work force analytics, suggests Cantrell. She cites work done at one company that studied employee behavior when interacting with customers. The company quantified behavioral traits such as how often customer service representatives smiled, frowned and looked people in the eye.
It then found a strong correlation between smiling and customers’ perception of waiting time. This is a key factor in customer satisfaction, which in turn drives sales. With that insight, the HR department led a training effort to teach representatives to smile more often, resulting in improved business.
Work force analytics transforms the “touchy-feely” approach to HR and puts it on solid empirical ground when working with other data-driven parts of the business. With it, HR professionals take a more active role in developing and monitoring business strategy because the information they provide management leads to more effective deployment of human capital, generating more revenue, better margins, increased customer loyalty, and improved employee performance and satisfaction.
“The payoffs are real. There is no doubt in my mind that work force analytics improves the bottom line,” Cantrell concludes. And bottom-line performance, after all, is what CEOs ultimately demand from all employees.