The global mobility sector is a constantly shifting landscape. As new economies rise, industries evolve, global connections change and relocation practices develop, the business of moving people remains in a perpetual state of motion. Discover why data analytics is the next stage in that evolution.
Do you know about the latest development in the ever-changing world of global mobility? It's the use of data analytics.
Industry leaders are coming forward to support the development of analytics technology and processes to improve the way we move talent around the globe. The goal is better and more successful practices, with aims of boosting everything from profitability to talent development.
But what role does data play in that future?
What exactly is data analytics?
Data analytics is used across a variety of industries. The concept is the simple tracking of information relating to all facets of operations. This includes all aspects of work projects, such as costing, time absorption, successes and failures, income and profitability, geographical interests, and peak seasons. Management can then defer to this data, looking at historic information about the company and using it to inform decisions.
In terms of corporate relocation practices, data can provide insight into previous relocation projects. With the use of data analytics, those managing employee moves can make more informed choices about upcoming projects.
Why is data analytics the future of global mobility?
Success in global mobility revolves around a number of key factors. Businesses want to maximize cost-effective relocation programs, improving the effectiveness of matching candidates with assignments to reduce the occurrence of misplaced individuals, while streamlining to save both money and time. Core to achieving such goals is trial and error, and experts believe data analytics can optimize lessons learned for better mobility prospects in the future.
Collection of data from previous global mobility projects – not just from your own brand, but also through collaborators, competitors and any other data you acquire – enables mobility managers to assess strengths and weakness of previous moves. This in turn allows them to produce better strategies for future relocation based on said data.
For example, data may show geographical locations that offer poor ROI, programs that lead to high staff attrition rates, or roles that are notorious for failed workplace integration. Conversely, data analytics can open businesses to locations that are highly profitable in terms of relocation or global mobility schemes that produce and develop the best quality of talent.
Data can also be used to automate mobility practices and provide projections and predictions for future projects. When you're looking to establish new global services, trade and placements, data is a critical tool in making the most beneficial business moves. By leaning on data analytics for decision-making, management can make choices that use previous successes as indicators of better goal achievement rates. This can significantly reduce wasted resources and failed global mobility projects by eliminating investment in underperforming mobility programs and putting greater focus on the strongest platforms.
Without data analytics, businesses simply can't do this. They cannot use information of the past to influence the future.
Current barriers to success
Data analytics is a rising star in the global mobility industry, but many brands still face challenges before they can use it for optimal business growth. So what are the common obstacles to the integration of data into global mobility strategy?
No data set: If you aren't recording data, you can't use it in the future to make decisions. Awareness is step one. Acquisition of information is step two.
Misunderstanding of data: Those who do have data may be unaware of how to use it to actually boost their global mobility programs. Investing resources in developing data analytics skills of staff members involved in global mobility management will result in better use of the information at your disposal.
Ignorance of data: Many corporations record information but simply ignore it, favoring old-fashioned methods of decision-making like instinct or industry predictors. The data should speak for itself here, and those who fail to see the value in it may want to reconsider their position as more and more business rivals pay attention to their analytics.
Lack of software utilization: Global mobility projects can range from single employees to legions of workers. An individual can produce a lot of data; a whole team can produce endless reams of it. Recording, deciphering and using this data can be challenging without the right tools. Software platforms such as iMercer and Ineo are specialist tools designed to support global mobility data analytics and help businesses use it to achieve future success.
Integrating data analytics with global mobility in 2018
Most businesses running global mobility projects acknowledge that data analytics will play a critical role in the years ahead. For those not currently using data analytics, and those who have not previously considered it an important aspect of their relocation process, how can this information be integrated to assure future success?
Getting ahead of future trends means immediate integration of data analytics procedures, including the recording of all global mobility data and investment in software to improve usability and predictors. Further to this, businesses must maintain a commitment to accurate data acquisition, as improper or incomplete records cannot be used to properly make decisions about future mobility programs – and, of course, patience.
This method is a relatively new concept in popular global mobility processes. As such, many corporations won't have built the extensive data sets required for meaningful analysis. Once data stores are at levels that mean practical choices can be made based on the previous results, data analytics can be integrated into global mobility programs to enhance future success.
While it may sound complex, with proper thought, training and software utilization, data analytics can actually be a simple yet highly effective tool for better relocation practice.