Organizations Benefit When They Help People Identify Paths for Growth and Development.
Today, careers are much more complex than they used to be, even within organizations. Now that companies have replaced traditionally rigid hierarchies with more dynamic and fluid team-based structures to foster agile ways of working, it has become harder for employees to discover what their next role will be—and even more so, what their next job should be.
This challenge is also a growing concern for employers, who must—for the sake of engagement and retention—show high-performing employees how they can progress within the organization. Late last year, in conversations with managers from 16 leading companies across various industries, we explored how organizations are helping their people build better careers. Through those discussions, we identified a couple of key ways companies are using analytics to tackle this major challenge.
Forging Learning Paths in Fluid Environments
A common first step for companies applying analytics to career development is using HR data to map the paths people have followed in the past. Because conventional career ladders based on a hierarchical org chart have practically disappeared, companies are beginning to analyze the countless ways people have advanced to highlight the different paths employees can take. In its simplest form, such career mapping uses historical data to show what positions people held prior to a given role, allowing current role holders to see a range of plausible options for their next career move. In other cases, companies identify the jobs that a specific role has led to, showing the variety of paths employees can take toward a coveted position. Either way, analytics are used to uncover advancement and growth options that aren't defined by formal org charts, but instead emerge from the decentralized decisions of employees and hiring managers as they build their careers within the organization.
A more ambitious and forward-looking version of career mapping also incorporates data on the types of skills and competencies needed for each job, looking for overlaps across profiles and between jobs. Although not all companies have this data, and developing competency profiles for different jobs from scratch can be a long and expensive process, this approach can highlight which roles are more similar in their requirements than they might appear. This method is particularly valuable in rapidly changing fields, where the continuous emergence of new jobs and the disappearance of older ones make it difficult to infer career paths from historical data alone.
For example, many of the skills required for an HR analytics role—such as experience with organizational reporting and information, analytical competence, and the ability to communicate with business partners—can also be found within an organization's financial analyst group. Identifying these overlaps helps create new career opportunities for individuals in both roles, providing them with unexpected paths for internal development and growth, while establishing new talent sources for teams. For hard-to-fill jobs, this approach can simplify recruitment efforts and generate significant savings for the organization. As an added benefit, incorporating skills into the career mapping process can help managers offer employees practical advice on which skills they need to develop to transition into their next roles.
Connecting with "Passive" Internal Candidates
Several organizations are also trying to be more proactive in searching for "passive" internal candidates: people who would likely excel in certain jobs but are unaware of those openings or haven't even considered applying. Identifying these candidates involves developing analytical models to predict how well each current employee in the organization fits the profile for a given role.
Recruiters can significantly improve the process for new job openings. Being able to identify internal candidates doesn't just lower recruitment costs: evidence suggests that internal hires consistently outperform candidates brought in from the outside. As a result, several established organizations have been exploring how to use analytics to better identify promising candidates within their ranks, and a number of startups are developing products to help companies match their jobs with their people.
Building the models themselves is analytically quite simple, requiring only rudimentary statistical or machine learning capabilities. The bigger challenge for most organizations is creating and maintaining solid data about the jobs and employees on which those models are based. Some companies have rigorous, up-to-date information about job requirements, but almost none possess the employee skills data needed to make a good match.
One way organizations try to solve this problem is by creating an internal LinkedIn-like system where people can post their profiles and increase their internal visibility. After all, LinkedIn has far better data on most people's skills than their current employers do. But early attempts to roll out internal skill profiles have suffered from typical "chicken-and-egg" problems: recruiters don't use the systems because profiles are incomplete, so employees don't bother completing their profiles.
Some employers are making updated skill profiles a mandatory part of the performance review process, which could help. Others are exploring building skill profiles directly from employees' work products. For example, IBM is analyzing data from internal documents and workflow information to infer worker skills before asking individuals to validate their profiles. Both approaches look promising, though it is too early to confirm their effectiveness. However, what is clear is that as organizations become more invested in managing their employees' careers, they will need to substantially improve the quality of data they maintain about them.
Taking a Long-Term View
Systems for mapping internal career paths and identifying internal candidates tend to have a short-term focus: What job should I take next? However, in many cases, employees' careers within an organization will extend far beyond their next position. It is important to consider which types of career paths most frequently lead to long-term success.
For example, 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 a financial firm found that lateral "broadening" moves early in a career ultimately allowed individuals to reach a higher level in the organization. Such benefits of breadth are consistent with what we know about executive hiring, but it is not yet clear that varied/multiple career paths are always a good idea.
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