self-sufficient with AI

LEXINGTON, MA, May 10, 2019 – Ironside, an enterprise data and analytics firm, was featured in a Wall Street Journal article about AI consultants that enable their clients to be self-sufficient with AI and not have to rely on their consulting counterparts to manage the model.

Ironside’s client, Cartus, the largest global relocation management company (RMC) in the world by volume, was looking to build a data science program that would provide increased customer value, leverage their wealth of data, and help drive them forward and transform from a traditional RMC to a “data-first,” “technology-first” organization within their industry. They brought in Ironside in early 2018 to assist them in developing this program.

“The decision was made from the start not to become dependent on a consulting company.”

– Neil Bussell, Director of Analytics, Data and Robotic Process Automation at Cartus

Ironside’s data scientists, data engineers and Experience Design team engaged with Cartus on an “AI Jump-Start” to implement predictive analytics capabilities to enhance their relocation products for their corporate clients with decision support. Ultimately, this would allow Cartus to enable the sales and client services organizations to make their products even more attractive to their customers. For this initiative, Ironside partnered with DataRobot to be the catalyst for the data science practice to enable the non-data scientist knowledge workers to contribute with an easy-to-use AML technology platform.

Ironside spent the better part of 2018 designing and testing AI models in order to develop a product that would allow Cartus to predict relocations and costs for their clients. Once the product was created, the Ironside team trained and enabled the Cartus staff, as well as helped them hire a full-time data scientist to maintain the AI model moving forward. Cartus launched MovePro Vision in early 2019.

Through our experiences, Ironside formulated a point-of-view on how data science should work in practice and how to develop use cases that generate real value. We also believe that if we seek to enable more non-data scientists to answer questions in a data science way, using statistical or machine learning methods over visual methods alone, that they and their organizations would be much smarter and mature faster in their use of data for decision making.


“If a company can master its data and master AI, and really start building their own models, they’re going to start curating a ton of valuable intellectual property that may have actual direct enterprise value to that business.”

– Greg Bonnette, VP of Strategy & Innovation at Ironside

Read the full Wall Street Journal article here.

About Ironside

Ironside was founded in 1999 as an enterprise data and analytics solution provider and system integrator. Our clients hire us to acquire, enrich and measure their data so they can make smarter, better decisions about their business. No matter your industry or specific business challenges, Ironside has the experience, perspective and agility to help transform your analytic environment.