Careers are much more complex than they used to be, even within organizations. Now that companies have replaced rigid hierarchies with flatter, more fluid team-based structures to promote agile ways of working, they have also made it much harder for employees to figure out what their next job should be, let alone the one after that. This challenge is also increasingly a concern for employers, who must — for the sake of engagement and retention — show high performers how they can progress within the organization.
During the past year, researchers on the Wharton People Analytics team talked with managers at 14 industry-leading companies and hosted two daylong meetings to explore how organizations are helping their people build better careers. Through those discussions, we identified a couple of key ways that companies are using analytics to tackle the challenge.
Forging Pathways in Fluid Environments
A common first step for companies that apply analytics to building careers is to use HR data to map out the paths that people have pursued in the past. Because conventional career ladders based on a hierarchical organization chart have essentially disappeared, companies are starting to analyze the myriad ways people have advanced to highlight different pathways employees might pursue. At its simplest, such career mapping uses historical data to show what prior incumbents of a given role have gone on to do, allowing people who are currently in that job to see a range of plausible options for their next career move. In other cases, companies identify the jobs that have fed a given role to show the variety of paths employees can take toward a position they covet. Either way, analytics is being used to uncover options for advancement and growth that are not defined by formal organization charts but instead emerge from the decentralized decisions of employees and hiring managers as they craft careers within the organization.
A more ambitious and forward-looking version of career mapping also incorporates data on the kinds of skills and competencies needed for each job, looking for overlaps in profiles across jobs. Although not every company has such data, and developing competency profiles for different jobs from scratch can be a long and costly process, this approach can potentially highlight which roles are more similar in their requirements than they appear. This method is particularly valuable in fast-changing fields, where the continual emergence of new jobs and the disappearance of older ones make it difficult to infer career paths from historical data.
For example, many of the skills required for an HR analytics role — such as experience with organizational data and reporting, analytical proficiency, and the ability to communicate with business partners — may also be found within an organization’s pool of financial analysts. Identifying these overlaps helps create new career opportunities for people in both roles, providing them with unexpected paths for internal development and growth, and it establishes new sources of talent for their teams. For jobs that are hard to fill, this approach can streamline search efforts and generate significant savings for the organization. As an additional benefit, bringing skills into the career-mapping process can help managers give employees actionable advice about which skills they would need to develop to transition into their next roles.
Connecting With ‘Passive’ Internal Candidates
A number of organizations are also trying to be more proactive about finding “passive” internal candidates — people who would most likely be very good at certain jobs but may not know about those openings or may not have considered applying. Identifying those candidates involves developing analytic models to predict how well each of the current employees within the organization would fit the profile for a given role. Recruiters can then reach out to the best fits and solicit applications. Being able to identify internal candidates doesn’t just hold down recruitment costs — evidence suggests that internal hires consistently outperform people brought in from the outside. As a result, a number of established organizations have been exploring how to use analytics to better identify promising candidates within their ranks, and a suite of startups are developing products that could help companies matchmake between their jobs and their people.
Building the models themselves is analytically very simple, requiring only rudimentary statistical or machine learning capabilities. The bigger challenge for most organizations is building and maintaining the robust data about jobs and employees that those models draw on. Some companies have rigorous and up-to-date information on job requirements — but almost none have the information on employee skills needed to figure out a good match.
One way organizations are trying to solve this problem is by building an internal LinkedIn-like system in which people can post their profiles and increase their internal visibility. After all, LinkedIn has much better data on most people’s skills than their employers currently possess. But early attempts to implement internal skill profiles have suffered from chicken-and-egg problems: Recruiters don’t use the systems because the profiles are not completed, so people don’t bother to complete the profiles.
Some employers are making updated skill profiles a mandatory part of the performance review process, which might help. Others are exploring creating skill profiles directly from people’s work products. For example, IBM is scraping data from internal documents and workflow information to infer workers’ skills before asking people to validate their profiles. Both approaches seem promising, although it is too early to confirm their effectiveness. What is clear, though, is that as organizations take more interest in managing the careers of their employees, they will need to substantially improve the quality of the data they maintain on them.
Taking the Long View
Systems to map internal career paths and identify internal candidates tend to have a short-term focus: What job should somebody take next? Yet in many cases, employees’ careers within an organization will extend well beyond that next job. It’s important to also consider what kinds of career paths most often lead to longer-term success.
For instance, you might ask: In the end, is it better to allow people to deepen their expertise in a particular specialization or to foster broader skill sets by moving employees across functions? The analytics team at one financial company discovered that “broadening” moves early in a career slowed progression initially but eventually allowed people to rise higher in the organization. Such benefits of breadth are consistent with what we know about executive hiring, but it is not clear that varied careers are always a good idea.