2017: A Year of Preparation, Not Disruption

2001: HAL 9000

Every year begins and ends with predictions about the dramatic developments we should expect to see in business, politics and life in general over the coming 12 months. The world of HCM technology is no different, and since November we’ve read more articles about what disruptions to expect in the space during 2017. And, to be sure, the world of human capital technology is changing to meet developments that touch both the workplace and workforce.

2001: HAL 9000We question, however, the idea that 2017 is going to be a year of “disruption.” While vendors of all types are exploring areas of artificial intelligence and more mobile solutions, we’re thinking this will be a year of evolution more than revolution. Certainly, the teams at known brands such as Ultimate Software and SAP SuccessFactors, as well as newcomers like Pymetrics, are looking at new ways to solve old problems and in some cases go even further by improving the very processes involved in recruiting, workforce management and corporate learning. But at the same time, we’re still waiting for workforce analytics to hit the mainstream, and that hasn’t happened yet.

We can hear the voices objecting to that last sentence. And it’s true that workforce analytics has built significant momentum over the last several years: Deloitte’s Global Human Capital Trends 2016 reports that 77 percent of the executives it surveyed say people analytics as a “key priority” for 2016, “up slightly” from the previous year. “In response, companies are building people analytics teams, rapidly replacing legacy systems, and combining separate analytics groups within HR into one strategic function,” the report said. >

But as Jacob Morgan noted in Forbes, HR departments “need to understand what to do with that data and how to make sense of it. This requires a deep understanding of analytics and data science. The smart HR teams around the world are staffing up with plenty of data, science and analytics professionals to help … understand their people better.”

Disruption Costs Money

But Morgan should have included a key phrase with “smart,” specifically, “well-funded.” According to PayScale.com, the median salary of a data scientist in the U.S. is about $91,600. The Social Security Administration reported that the average American wage for 2015, the latest figure available, was roughly $48,100. That means any organization ready to hire a data specialist dedicated to Human Resources must be willing to spend nearly twice the national average for a single person with the necessary skills.

In Deloitte’s 2015 report, 75 percent of the executives surveyed felt that people analytics was “important,” but only 8 percent thought their organization was “strong” in the area. (We couldn’t find comparable figures in the 2016 report.) So while there’s no question the use of analytics could do great things in terms of workforce planning, talent acquisition and management, it’s difficult to say it’s gone mainstream when only 8 percent of Deloitte’s global universe are taking full advantage of it.

We don’t see that dynamic changing anytime soon. Despite the ever-increasing talk among executives of HR as being “strategic,” companies still hold back from allowing it to take “exclusive control over organization development (25 percent) or succession planning (11 percent), and very few companies with merger and acquisition functions have assigned those duties to human resources alone,” reports Bloomberg BNA’s HR Department Benchmarks and Analysis 2015-2016. And, the majority of HR practitioners and managers we speak to continue to say that their company’s leaders talk big when it comes to investing in HR, but rarely back up their words with real money.

The HCM Technology Conundrum

Today, a number of factors pressure what we’ll call the “traditional” HCM tech vendors, companies like Oracle, SAP, Workday, ADP, Cornerstone OnDemand and the like.

  • First, the role of HR is changing, though no one is quite clear about how. Second, new technologies appear at a mind-bending pace, and customers seize on the notion of incorporating the latest and greatest into their systems.
  • Second, the workforce itself is changing, with contingent workers playing a greater role in most aspects of a company’s operations. As a result, an organization’s workforce can come under the management of two distinct functions: HR and Purchasing. Interestingly, vendors seem more concerned about this than HR executives do.
  • Third are employees themselves. As the workforce turns younger, its members have become more impatient with bureaucracy, are less willing to compromise on the technology tools they use, and in general expect employers to be more flexible in accommodating both their work and lifestyles.
  • Then there’s the way work gets done. More of it is done remotely, teams are often scattered geographically–both nationally and internationally–and are comprised of both contingent workers and full-time employees. This makes seamless communication critical at every level of the company and puts additional pressure on HR to ensure messaging is effective across locations and performance management proceeds smoothly even when manager and employee are located hundreds of miles apart.
  • Finally, a number of new, smaller HCM tech companies are appearing, often focused on solving a single, narrow issue. They have the advantage of lower overhead, the ability to pivot quickly and work with technology that’s unburdened by their own legacy approaches.

The solution to the first four challenges lies in the use of more advanced technology, but the market often forces vendors to either move more quickly than they should or overstate their case in their marketing. Without delving into the details of what constitutes true artificial intelligence–which will be a whole article until itself–we see many articles being written about how it will improve sourcing, streamline HR operations and better predict which employees are in danger of leaving the company.

While we can envision all of that coming true at some point, it’s not going to be in 2017. There are simply too many people with too many visions of what role AI should play in HR, and how practitioners and line managers will use it.

HR organizations should use 2017 to examine what technologies will best address the challenges they face and how they can implement these tools in the most effective way possible. This means, for example, avoiding the mistakes many companies made in adopting analytics, when they forgot the needs and capabilities of the system’s users. Many vendors have already recognized this and are incorporating more learning and recommendation content into their offerings, but customers, too, should consider the implementation of any new HR tool from one end to the other: That means paying greater attention, and investing more, in training, well-executed roll-outs and understanding where technology’s job ends and the HR practitioner’s begins.