predictive analytics

Global Mobility Teams Need Not be Intimidated by Predictive Analytics

In this fast-changing world characterized by disruption and unpredictability, global mobility managers and their human resource colleagues have a secret weapon. One they can harness to their utmost advantage, if only they can stop being afraid of it:  namely, predictive analytics.

Discard that initial discomfort with its association with everything data, and just focus on the one critical support it can give you: use the information pouring through your infrastructure not just to understand the present, but to forecast the future.

Analytics 1.0 tends to intimidate many professionals with its blend of high-minded mathematics and mysterious algorithms.

One legitimate reservation lobbied at it is that it is too reactionary. By the time that the data analysts have made sense of the current challenges by studying the data, the situation that has to be addressed is over — or it could have evolved  into something else.

In contrast, my HR Future says that predictive analytics can use that same detailed study to show the decision-maker various options that can confront him in the near future. More important, it can also point out ways on how he can address them, and perhaps even turn them to his advantage.

Here are a few examples:

First, predictive analytics can assess the attrition risk of individuals in the workforce, and then check how that development will impact the entire personnel in the organization.  Regular analytics can monitor which of your team members are high performers, moderately productive staff, and just plain slackers. Predictive analytics can go a step further and factor in a few more variables, such as an assignee’s average length of stay in an organization, ability to blend in a culture, and behavioral tendencies concerning teamwork.

Once it starts crunching all that information, it can accurately forecast which assignees are at high risk of quitting given certain challenges such as culture shock and/or time away from family.

The beauty of predictive analytics lies in that it does not leave the global mobility manager with a challenge on his hands.

It can empower them to assess the positive influences (not just the negative ones). It can point out elements that can improve the motivation of the assignee, for example, or suggest certain work conditions that can prevent them from sliding into depression.

The second way that predictive analytics can be used just might endear the global mobility manager to their CEO and Chief Finance Officer: determine the true value of the global mobility program costs.

According to, it can put a number on the following: the value of investment that the organization places within the assignee, as well as the return of investment that the assignee provides the organization.

It can also pinpoint the total costs of each event or program that the global mobility manager makes for recruitment or retention, for example. Obviously, some programs — like some assignees — will give a healthier ROI, than others.

Taking predictive analytics to the next level, the global mobility manager can then prioritize the more effective programs and recommend further investment, e.g. training, into the more productive assignees.

Finally, as pointed out by Business, predictive analysis can chart global recruitment hotspots where assignees can be hired in the near future.

The AI can discern patterns from behaviors and results that the human manager for the moment just might regard as coincidences. Once the trends emerge, the global mobility manager can continue to keep a watchful eye on the talent-heavy regions.

They can ask the AI to narrow down specific abilities of the talents in those areas. Afterwards, it would be easier to align the kinds of assignees and skillset they could locate in those hotspots with the  organization’s own human resource needs.

Data will always play an important part in a company’s growth during the digital age. It has helped birth tech-savvy meccas like Silicon Valley. It’s about time that global mobility managers embrace it, and use it not just to analyze what’s happening now, but also how to plan for the future.