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November 16, 2021

Three Tips for HR Managers Deploying Analytics and Career Mapping

Predictive analytics and career mapping offer powerful ways to understand workers’ capabilities and keep them engaged throughout their careers. Using these tools can be daunting at first, especially because they’re often based on artificial intelligence and other algorithms that seem somewhat mysterious.

Fortunately, human resources managers don’t have to be programming experts to put predictive analytics to work in career mapping and employee coaching. Here are three ways HR teams can ensure that they’re using these tools effectively. 

Climb the Spiral Staircase

It’s tempting to think of any process as a linear path, and the adoption of predictive analytics for career mapping is no exception. The most effective ways to use these tools, however, involve doubling back to review results and rethink applications. 

“The best teams don’t climb directly from one step to the next one; they are constantly iterating — retracing their steps and climbing the same stairs again — at every level of the journey to the top,” write Elizabeth Ledet and fellow researchers at McKinsey. The result is a deeper understanding of how to use predictive analytics tools to improve career conversations with staff members at every iteration.

This deep approach to predictive analytics can unlock a new level of value for a tool many U.S. companies are already embracing. For example, a Mercer study by Kate Bravery and fellow researchers found that 55 percent of US human resources leaders have already embraced predictive analytics in some capacity. The difference among the companies that use it will be the extent to which they dig deep with the tool. 

Think Big (Data)

For humans, data influx has its limits. We make better decisions when we have more information, but only to a point. Once that point is passed, more information tends to overload our ability to think critically, shutting down good decision-making in favor of quick shortcuts. 

Artificial intelligence, on the other hand, doesn’t get overwhelmed. As a result, it is well suited to glean insights from massive data sets. In fact, the more relevant information AI algorithms can parse, the more nuanced and useful the results of their analyses may be. 

The best predictive analytics tools work from vast data sets, including information gathered both within an organization and outside it. They’re trained to spot and ignore patterns that aren’t relevant to career success, focusing instead on the skills required to do well in a particular role or on a particular career path. 

Because they can take the big-data view, predictive analytics tools can identify potential career paths that might elude the notice of humans working without AI support. They can use a particular person’s current skill set to suggest roles and trajectories that might support the worker’s current and future career success, based on how others with similar skills have succeeded in the past. 

In this way, predictive analytics can open up a world of possibilities for career mapping. Employees aren’t limited to the most obvious or well-trodden paths; instead, they can work toward futures that genuinely support, challenge, and enhance their skills.

topographic map with flag pushpins close up; Analytics and Career Mapping concept

Embrace Innovation

Artificial intelligence has matured into a useful tool for career pathing in part because those dedicated to developing its abilities have embraced innovation and advancement. The more they learned, the more they put into refining AI and its capabilities. Human resources teams seeking to use AI-based predictive analytics for career mapping can learn from this approach. 

While using predictive analytics itself is a form of embracing innovation, it’s only one way to improve career mapping. Predictive analytics can help enhance another key form of innovation in career mapping: reimagining career paths. 

Past approaches to career mapping typically focused on the traditional career ladder: Join an organization, work up the ranks, and retire having reached the highest level of management or leadership available. For those who didn’t want to take this path, the options seemed limited. Many workers switched companies or career tracks entirely because there were no other options available to them. 

HR teams considering predictive analytics should include someone on the team who is conversant in the tools used and their limitations. Organizations that incorporate AI into their core strategies have a better chance of seeing success from the use of these tools, says Atif Kureishy, founder and CEO at AI and data analytics platform Vistry. 

With the help of predictive analytics, workers and their human resources managers don’t have to limit their vision. Nor should they. Predictive analytics makes it easier than ever to understand a career as a process of skills growth and to map that growth onto alternate paths. By embracing new ways to look at career planning, human resources managers and employees can find new ways to help workers expand skills and stay engaged within the company throughout their careers. 

By offering insight into promising future options, predictive analytics revitalizes career mapping. It allows human resources teams to learn more about their own companies, improve mentorship of employees, and rethink how skills drive retention. 

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