February 28, 2018

Introducing Cartus’ Leading Edge Analytics Practice: LEAP

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Introducing Cartus’ Leading Edge Analytics Practice: LEAP

Posted by: Neil Bussell, Director, Business Intelligence & Data Management 

We may not see another Leap Year until 2020, but for the next 24 hours, I hope you’ll join me in celebrating LEAP day.

What am I talking about? Only Cartus’ new Leading Edge Analytics Practice, LEAP, which will bring revolutionary capabilities to clients and their relocating population through predictive analytics (aka, advanced analytics, artificial intelligence, data mining, data science, deep learning, machine learning—you get the idea).

With our unmatched database of 2.3 million moves to 7,700 unique country combinations, Cartus is singularly positioned to provide the depth and scope of data needed to forward-manage our clients’ relocation programs in ways that have never been seen in the industry before.

For example, our Interactive Timeline in CartusOnline uses advanced analytics to predict your employees’ personal relocation journeys. Using data we’ve acquired over millions of moves, the Timeline dynamically updates as the move progresses, shifting key activities and tasks while reforecasting future milestones.

Ultimately, predictive analytics will power a new level of service and value for HR and mobility managers as well as relocating employees. Whether your goal is to optimize cost management, program management, talent management—or all three—email us at leap@cartus.com or contact your Cartus representative to learn how one small step for you can lead to one giant LEAP for your relocation program.

Please watch our short LEAP video below and visit our Technology overview on Cartus.com to learn more about the innovations behind our new mantra, Technology that Moves YouSM.

Picture of Neil  Bussell

Posted By

Neil Bussell

About Neil

Neil is responsible for the development and execution of global data strategies for both internal and client facing needs. Neil brings to his role a long career in information technology with deep experience in the areas of analytics, master data management, business intelligence, data architecture, and application development.

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