Big Data Drives Predictive Talent Planning
How do you know which talent trends to invest in?
At Accenture, the professional-services company with 449,000 workers in 120 countries and $33 billion in revenue, big data are helping providing the answer to that question, according to Mike Gabour, a next horizon skills lead with the organization.
“Tech is changing at an exponential pace,” he said during a Thursday session at the the HR Tech Conference titled “Hiring for the Next Big Thing at Accenture: Big Data Drives Predictive Talent Planning.”
“Gone are the days when you had 10 years to respond to a new tech trend. These days you’ll be lucky if you get two,” he said. “So we always have to look ahead to stay ahead.”
But what if you could use that same technology to predict those next trends?
About two years ago, Gabour said, Accenture teamed up with Ph.Ds at MIT, “dumped a boatload of data on the conference-room table and asked them one question: How do we make sure we don’t miss the next trend?”
After the MIT representatives looked at job-posting data and talent-pipeline data, they were able to understand what those trends markers were and successfully be able to understand what was coming up. But they soon realized they were missing a key component: What was happening outside of Accenture’s internal data?
And that’s when they turned to Burning Glass Technologies to dive into the larger world of human-capital data to get answers to questions like: How do we validate what we’re seeing internally? How do we make sure we’re not missing what’s happening in the external marketplace? And how do we look to the next one to two years and predict what those future trends will be?
But human-capital data are “super-unstructured and very messy,” said Enrique Cruzalegui, vice president of strategic accounts at Burning Glass Technologies, adding that people use the same words to describe completely different concepts.
“An associate at McKinsey versus an associate at Walmart, that kind scenario,” he said.
So in order to create order out of all that chaos, Burning Glass collects data from 50,000 sources and has nearly 1 billion jobs in its database going back to 2010.
“What that data contains is essentially very coded job postings from wherever that data lives, combined with government data, educational data,” Cruzalegui said, “and we have mapped that to a taxonomy that we have developed internally.”
This approach allows them to see job skills in context and make appropriate comparisons between two companies in the same industry in order to get an accurate look at the companies’ “talent shape” and see what types of skills workers have that they are most hiring.
Based on the quantities of the job postings, he said, Burning Glass is then able to determine what a company values in terms of skills.
That’s important for employers to know, he said, “so you know who you’re comparing yourself against and who you’re competing with for that talent, and also to understand what are the important skills that the job market is saying are in the most demand.”
Through this approach, Cruzalegui said, Burning Glass has defined four different skills categories, including escalators, which are growing fast and build on existing technology, but “it’s not going to shake your world up,” while disruptors “could potentially really change the way you do business.” Stabilizers “might be a type of day-in, day-out type of skill, such as data manipulation,” while challengers are skills that “you know you’re going to need, but they’re just hard to find, such as data architecture.”
This information is critical for companies like Accenture, Cruzalegui said, because it has to be able to forecast the skill that “hasn’t been invented yet that’s going to revolutionize how you do XYZ.”
But tracking disruptions across multiple dimensions means not only looking at job descriptions but also keeping an eye on “internet chatter,” as well as maintaining a large database of resumes that Burning Glass uses to validate their findings and “see how people are moving across their career pathways,” he added.
Using this information, Gabour said, allows companies like Accenture to identify where those future skills gaps will be and how to invest in future learning, as well as where to focus on hiring.
Accenture was also able to answer some key questions for its leaders, Gabour said, including: Which skills are growing fastest? Which skills are growing faster than expected? Which skills are declining in the marketplace?
“Using this information can really help inform our decisions and prioritize those investments we need to make on a quarterly or annual basis,” he said.
As an example, Gabour noted that when working with Accenture Security, “we found that cybersecurity skills were far different than information-security skills.”
“It’s at this level of specificity that those insights can be actionable,” he said, adding that, “without that tangible information, it’s really difficult for a business leader to make those decisions.”