Bracing for Big Data Analytics
A new survey finds only one-quarter of companies equipped to meet their anticipated analytics needs in the future. Experts predict many organizations will rely on a combination of developing internal talent and bringing in outside expertise to fill analytics capability gaps.
By Mark McGraw
The era of big data analytics is upon us, and new study findings suggest many companies aren't exactly ready.
Conquering Big Data: A Study of Analytical Skills in the Workplace, a global survey from the American Management Association, asked nearly 800 respondents from more than 50 industries if their organization has the capabilities to meet its anticipated analytics needs.
In the poll, only 26 percent of respondents indicated their companies have the ability to meet those future requirements.
Organizations finding themselves ill-equipped to meet anticipated analytics needs "have likely been behind the curve in implementing enterprise planning and integration initiatives for a long time," says Jim Stoeckmann, senior practice leader at Scottsdale, Ariz.-based WorldatWork.
"The systems at the heart of these initiatives -- enterprise resource planning systems -- paved the way for big data analytics by enabling much greater data visibility, which organizations have used to integrate and streamline myriad business processes such as sales forecasting, order fulfillment and revenue tracking, to name just a few," says Stoeckmann.
Current availability and access to big data, however, demands better analytical capabilities across the organization, "rather than concentrated in the hands of a few specialists," he says. "That's the fundamental change that organizations are dealing with, and it is evident that many are not prepared."
Indeed, the volume and variety of data available today, coupled with less costly technologies, "have changed how organizations view information," says Alexandra Ellis, director of the New York-based American Management Association.
"Research shows that higher performing organizations collect and leverage data at every stage of their strategic initiatives, while their competitors take a more reactionary approach," says Ellis. "Companies that miss the opportunities hidden in their data risk being left behind."
In order to avoid such a fate, many companies plan to look internally, with 47 percent of respondents to the AMA survey saying they plan to invest in training current staff to fill analytics capability gaps. Just 17 percent said they plan on hiring mostly additional analytics staff.
"Many organizations are coming to the realization that it's not enough to have just a handful of experts to interpret data. Every function and department needs employees who can understand and act upon the information that is now available," says Ellis.
While some companies may look externally to fill a few critical strategic roles, "it's more cost-effective to train current employees in analytical skills, so the larger workforce is conversant in big data. Companies that train current employees are able to augment existing skills with new ones, creating a well-rounded workforce."
An investment in improving big data capabilities will likely require a multi-faceted approach that includes developing internal talent as well as bringing in additional expertise, adds Stoeckmann.
"If technical skills are required, it's probably a good bet that IT specialists such as database specialists, data-warehousing specialists and database developers can learn new skills, as they have seen this trend coming for a long time," he says.
"Data expertise is the more challenging talent gap for most organizations," says Stoeckmann, "as this skill set has often been presumed to be the province of the experts. Organizations are now realizing that strong analytical skills are required in all functions, including HR. Addressing this skill deficit -- as broadly distributed as it is -- will probably require a mix of training and recruiting strategies. Neither approach is likely to be effective unless they are tied together as part of an organizational talent roadmap."
From a human resource perspective, "the more HR offers an integrated solution to business problems, the more successful they will be," adds Dave Ulrich, professor of business at the Ross School of Business at the University of Michigan.
"When analytics is separate from HR work on staffing, workforce planning, learning, performance management, compensation and so on, it becomes an afterthought more than an integrated solution," says Ulrich. "HR analytics expertise should not begin with the data or analysis, but with decisions that will enable business results. Business results increasingly come from integrated HR solutions."
A lack of resources and corporate culture "are the biggest roadblocks" standing between organizations and HR truly harnessing the capabilities of big data, says Ellis, adding that HR leaders "are on the front line" to address these challenges.
"Analytical skills -- including critical thinking, problem solving and decision making -- can be learned through both informal peer-to-peer interactions and formal training programs," she says.
"In addition, HR departments can leverage cross-functional projects and job rotation programs allowing employees to work in areas where data analysis is highly leveraged. HR leaders are in a unique position to influence both the corporate culture and the allocation of training resources, driving the development of this valuable skill set."
Determining how to carry out the necessary big data analytics training is "a tough question in this new world we live in, with the cloud and big data," says Stoeckmann, noting that vendors have developed big-data training taxonomies, while some universities have created big-data curricula as well.
"Most [programs] include a mix of concepts and tools that are a part of today's vernacular," he says. "The specific details can be customized for each organization, using a training-needs analysis."
Stoeckmann draws parallels between the challenges tied to big data analytics and the total quality management movement, which espoused an organization's continuous improvement in its ability to deliver top-notch products and services.
"TQM was about more than quality," he says. "Rather, it was about employee involvement, process re-engineering, a focus on services and many other themes that were much broader than just quality."
Big data analytics is similar "in that organizations will want to develop learning and change roadmaps that engage the entire organization," says Stoeckmann. "HR leaders can play a pivotal role in taking the long view and positioning this initiative as the important organizational culture change that it represents."