Data from human capital management systems has delivered significant value to organizations for decades. The value continuum has included ensuring compliance with workforce-related laws and regulations around the globe; optimizing human resources’ processes (when combined with various other elements such as change management); maintaining a historical record of key employee activities and transactions; tracking cost trendlines such as those related to recruiting, compensation and benefits; feeding payroll systems from time and attendance platforms; and providing visibility into learning and development needs. This, of course, is just a sampling, but truth be told, the capability to maintain and report on this type of information — while broadly beneficial to every organization — doesn’t pass what I refer to as my “ascension test.” In other words, merely doing a better or even great job of tracking and reporting on these and many other types of people data is not likely to allow an organization to ascend the ranks within its industry sector.
Many of us can recall the excitement generated by the first Applicant Tracking Systems or ATS’s hitting the market in the late 1990s and early 2000s. After all, activities related to sourcing, screening, selecting and offering jobs to candidates was perennially a very manually intensive endeavor that also produced many false positives (unsuccessful hires) as well as false negatives (potentially great hires that were never brought into the recruiting process). The first wave of ATS’s proved to be extremely successful in the market due to the impact of their automation capabilities, with virtually all of the ATS market leaders back then either getting acquired and folded into larger HCM platforms, or continuing their path to amassing very large, typically global, customer bases today.
It’s no secret that many large organizations operate in a somewhat insular and siloed manner. This dynamic applies to corporate functions where value-creation from taking advantage of operational synergies could otherwise be quite significant. Historically, human resources and finance departments, for example, were among the operating areas known to closely collaborate only when absolutely necessary. Actually, the 1992 book, "Men are from Mars, Women are from Venus," comes to mind when I reflect back on how I needed to navigate around a lack of integrated HR/finance data and processes when I was a global HR practitioner, especially since this was often exacerbated by the use of stereotypes like "people/people vs. numbers/people." The combination of these factors clearly created a sense of disconnectedness between the two groups. And having different definitions for commonly used business terms — like headcount and labor costs — as well as different methods for measuring and reporting on these items didn’t make the situation more manageable. But that wasn’t the whole enchilada of operational challenges when linking HR and finance: You also had to account for different processing and reporting cycles and cutoff dates, which often created hours of agonizing reconciliation work for the respective teams.
This analyst perspective (presentation) covers how Compensation Management, related enabling technologies and data strategies continue to evolve, particularly in the context of prominent business issues facing all organizations today.
Human resources and recruiting departments, and most job candidates, are well aware that we are firmly in a seller’s market when it comes to finding and hiring high-quality talent. Primary reasons for this include record low unemployment, the need to fill a variety of digital-age jobs across all industries that did not exist a few years ago and organizations competing fiercely to make their value proposition to candidates more attractive. This emphasis on effectively engaging candidates to maximize recruiting has motivated employers to devise new ways of elevating candidate interactions and personalizing the engagement experience. Some of these new methods are proving effective, while others may yield better results only when other variables are present.