There is one surefire way to make your corporate relocation program more successful—and it’s not increasing program benefits. It involves easing the transition for your relocating employees by crowdsourcing mobility data from an expert source that’s already close at hand: your workforce.
When relocations fall through, three times out of four, it’s because relocating employees and/or their families fail to adapt to the new environment. By tapping into your people’s collective wisdom, newcomers can get to know their new world even before they arrive.
After all, no one knows what it’s like to work for you…commute to your office…and navigate your city than those who already do so. The solution: collect that invaluable firsthand relocation data and share it with your relocating employees.
At best, a corporate relocation is an exhilarating life experience—a chance to pursue an attractive opportunity and explore a new area. However, there’s no avoiding the fact that two of life’s most stressful events are 1) moving and 2) changing jobs.
According to one Allied Van Lines’ relocation survey of 1,000 people relocating for their job, acclimating to a new community is the most-challenging aspect of moving—even more so than finding a new home.
Employers can mitigate some of this stress by providing comprehensive relocation benefits and vetted vendors that provide “settling in” services. However, the most thoughtful relocation programs also prepare relocating employees and their families for what lies ahead. They do this by providing accurate, detailed relocation data to help them set realistic expectations about the new area.
That’s where crowdsourcing mobility data comes in.
You may not realize it, but we all rely on crowdsourced information—information that’s been collected from a large group of people. Wikipedia, Yelp, TripAdvisor, Reddit, G2, Twitter and other social media are all based on crowdsourcing models.
Because no single person has all the answers, obtaining data from a large sample set renders the information statistically relevant. For example, when you read a dozen product reviews on Amazon, you get an overall sense of whether or not you want a product.
Furthermore, you’ll place more credibility on like-minded reviewers who appear to share your values. That’s why crowdsourcing mobility data from coworkers—a group of people who share significant characteristics and values—is so effective.