Challenge

MARS DRINKS, now known as Lavazza Professional after a 2018 acquisition, is part of the Lavazza Group, an Italian coffee roaster established in Turin, Italy in 1895. The Lavazza Group operates in more than 90 countries with 63% of revenues coming from markets outside Italy.

MARS DRINKS knew they need to constantly innovate to stay ahead of the competition. To help drive innovation, they had launched a pilot project in Germany with their KLIX vending machines. The pilot project strove to collect real-time data in predictive analytics, helping to avert machine downtime and out-of-stock products.

After launching the pilot alongside a German IoT vendor, MARS DRINKS quickly realized that the solution showed potential and wanted to create a global solution, not just a solution for their German market. MARS DRINKS also recognized, however, that to achieve this would require a different technology platform than the one they were currently using with this limited scope pilot.

“We approached the project from two points of view. We wanted to use IoT technologies to improve operational efficiency for our partners in the field. And while achieving that for our European business, we also wanted to build a platform that was scalable and flexible enough to meet future strategic requirements for customers across all markets,” said Jamie Head, Chief Information Officer of MARS DRINKS.

Solution

The project kicked off for MARS DRINKS when they met with Microsoft and Neal Analytics at Microsoft’s campus in Redmond, Washington. Intrigued by the possibilities created by Microsoft’s stack of Azure and IoT services and Neal Analytics’ expertise driving end-to-end digital transformations, MARS DRINKS decided to run a proof of concept with the KLIX vending machines and Microsoft Azure.

Leveraging Azure IoT Suite, Cortana Intelligence Suite, and Power BI, Neal Analytics was able to create a new solution for MARS DRINK that was later dubbed the “Global Platform for Advanced Analytics.”

To train the AI models, the platform initially analyzed three years of historical data alongside real-time information from vending machines. This enabled MARS DRINKS to explore three different use cases:

1. 1. Monitoring machine performance to maximize overall yield
   2. Out-of-stock prevention to maximize sales
   3. Global scalability to scale across worldwide MARS markets

Result

It became rapidly apparent that the solution Neal Analytics built for MARS DRINKS would enable much more than just predictive maintenance. The solution gave MARS DRINKS far greater visibility into their entire value chain. It provided granular insights into usage rates of vending machines, distributor performance, workplace consumption levels, and much more.

Through these insights, MARS DRINKS was able to optimize its business in a variety of ways. For example, service experts, who repair and restock vending machines, can now gain unprecedented workflow efficiencies including remote, real-time machine performance and stock levels. They can also access route optimization for planning the most efficient route for servicing machines in various locations.

The solution also enables innovative inquiries into consumer behavior. This has allowed MARS DRINKS to capture new insights, including issues that were previously difficult to address, such as the impact of seasonality, weather, and other factors have on sales. Leveraging the new solution, MARS DRINKS can now ensure their customers’ vending machines are appropriately stocked for any season.

“The world of work is changing rapidly. As more organizations look towards the workplace and workplace beverages to create environments that are vibrant and alive with potential, we can use data to add significant value. Putting machines online, considering how space is used, and looking at people’s beverage consumption will unlock a wealth of information that we haven’t been able to easily access before.” says Jamie Head, Chief Information Officer at Mars Drinks. “We can give them simple, actionable data that can be acted on straight away.”