Why Internal Mobility in 2019?
Retention of key talent is a top priority for any enterprise – and a primary driver of retention is the sense of opportunity that comes from career mobility within an organization.
But there are typically considerable barriers to mobility – both intangible barriers such as internal culture and incentives, and tangible barriers such as data robustness and market-making capability.
New technological solutions now enable enterprises to strengthen the robustness and utility of their data, and overcome the tangible barriers to mobility – and that in turn will help them to overcome cultural resistance.
In a world where young talent is changing employers at twice the rate of previous generations and losing an employee can cost a company up to 200 per cent of the individual’s annual salary, employers must be aware of the business case for retention. But do they realize how artificial intelligence can help to identify internal hires and improve retention?
Happy employees, successful businesses
The above quote outlines the mindset of business leaders when it comes to measuring people success. Successful organizations view employees as brand ambassadors; therefore, they emphasize the importance of employee satisfaction.
When asked to select from human resources challenges they believe could be helped with artificial intelligence, only 6% of HRPA survey respondents believed it could help with promotions, and 6% thought it could improve retention. This suggests that the majority of organizations are likely missing out on an opportunity to retain top talent.
Get me the right people into the job, make them productive and happy, and get them to help us attract more customers and drive more revenue - Josh Bersin, as seen in Forbes
Identifying Flight Risks
There are several ways in which artificial intelligence can help with internal promotions and retention. The first is by identifying employees who are at risk of leaving the company. Tech company Veriato has developed a variety of AI platforms to single out flight risks among employees. Their software tracks employee computer activity—emails, keystrokes, internet browsing, etc.—and stores it for thirty days.
Then an AI system analyzes the data to determine a baseline of normal activity patterns in the organization. Based on that knowledge it flags outliers and reports them to the employer. Variato also detects changes in the overall tone of employees’ communications to predict when employees might be thinking of leaving. When an employee’s “sentiment score” begins to stand out from the company baseline, managers can step in to try to retain them. When used properly, these technologies can assist employers in preventing unnecessary attrition.
Retaining Top Talent
How exactly can these employers retain flight risk employees? According to CEB Global, “a lack of future career opportunities in the primary driver of employee attrition, topping compensation and manager quality.” If employers can improve their processes for promoting employees from within, they can both save money on the hiring process and retain talent that might otherwise leave.
At Paddle HR, we specialize in internal career mobility for companies with 1,000 or more employees. Our algorithm and career matching tools are based on the concept that successful professionals have “T-shaped” careers; rather than following a linear path based on one specialization, they thrive when they can work across multiple sectors and functions.
In addition to providing our own platform, Paddle HR also conducts ongoing research on career mobility. Based on their research, they were able to share some cases of companies using AI to improve internal career mobility practices.
General Electric is recommending top job matches to employees based on where their peers with similar job titles and career histories have moved within the company—a method called “collaborative filtering.” The next step is to analyze employees’ career profiles using natural language processing to further filter job opportunities not caught by historical patterns.
Accenture created a global standard process and established a team to focus on internal mobility. They believe internal recruits cost less, get up to speed quicker and have a higher probability of success. Over the course of a 4-year program, the internal hiring rate jumped from 6% to 40% in Canada & United States.
Salesforce is experimenting with a novel approach to recommending new job opportunities by analyzing the text of employees’ annual reviews. If it finds employees are talking about skills or interests that are outside of the scope of their current job, it finds and recommends open jobs that utilize those skills or interests.
When these programs are successful, companies can save themselves time and money. A study by AirBnB found that internal candidates require 25-50% less interviewing time than external recruits. As mentioned earlier, any time HR professionals save in the recruiting process can be devoted to supporting the more important strategic functions. Additionally, Professor Matthew Bidwell from the University of Pennsylvania found that internal hires perform better, stay longer, and cost companies less. If companies can leverage AI to improve their internal mobility programs, the returns will be valuable.
While AI has the potential to transform companies’ internal mobility programs, there are some challenges preventing universal adoption. First, data is limited by the scope of collection and how employers choose to interpret it. What are the best indicators of success for making internal promotion decisions? Are employers collecting the right data? Research analysts David Johnson and J.P. Gowdner express concern that employers’ ability to gather data about employees has outstripped managers’ capacity to interpret it properly, opening the door to a variety of counterproductive practices. This is where outdated ideas about HR metrics still have a hold in some workplaces. Some managers will zero in on one measure of potential without understanding whether or not it is the most effective indicator. Johnson and Gowdner attribute this to managers’ tendency to pay most attention to what they can measure while ignoring more nebulous qualitative factors. Therefore, managers must be confident that the measures they track are proven indicators of success.
At Paddle HR, we have also identified some major challenges based on discussions with their clients. The first problem is cultural barriers to mobility. In other words, managers may not be motivated to support internal mobility out of fear of losing talent from their department. One large New York City bank addressed this by encouraging leaders to champion internal mobility while also making it clear they weren’t encouraging employees to leave their departments. The second problem Paddle identified is companies’ limited budgets for mobility initiatives. This sentiment is echoed in the HRPA survey, where of the people who said their company will not be moving towards AI, 10% cited budget restrictions as the main reason.
We have also found that it is unclear which organizational function “owns” internal mobility, which complicates the funding process. Finally, data readiness is an issue for many companies. Our recommendation for this problem is to leverage external career data to provide more information to algorithms – something we at Paddle HR have solved.
Based on our experience and analysis, we offer two recommendations to enterprise talent leaders:
Recommendation: Employers should assess employees’ perceptions of internal career opportunities and track internal vs. external hiring in various organizational functions in order to identify problems, indicators of success, and potential solutions.
Recommendation: Organizations should consider AI technologies to help them manage internal mobility initiatives, which can allow for better internal candidate matching and more timely marketing of internal jobs to both passive and active candidates.