Case Study
Thirsting for New Growth
Consumer Good / Self-Service Retail
Summary
A major consumer-beverage provider needed to revamp its food-service business, which included fountain products as well as bottled beverages for vending machines and retail coolers. Its portfolio had more than 700 product SKUs and millions of transaction data points. The company was generating more than $300 million in annual sales from more than 16 million consumers — but revenue was dropping by double-digit percentage points, for many reasons.
Because consumption data wasn't being captured effectively, the company lacked the insights needed to rapidly address shifting consumer preferences. Inventory levels, delivery schedules, demand patterns, and maintenance were misaligned and managed in different parts of the business. Existing equipment frequently malfunctioned and couldn't take on new challenges like sensing demand in real time. But high capital costs meant outright replacement wasn't an option for this low-growth, low-margin business.
The Silo Problem
Disconnected Data. Misaligned Operations. Declining Revenue.
Beverages were being placed and restocked based on one-size-fits-all planogram lists, a best guess by the driver, or whatever inventory was on the delivery truck — not necessarily what the location's customers wanted or were buying. Popular beverages tended to be out of stock, while ones with less demand were overstocked and languished.
The P&L owners determined they needed a holistic, cross-enterprise approach — one that would enable them to fully understand market demand and connect that demand with their supply chain, so they could uncover growth opportunities, reduce operating costs, improve margins, and optimize and modernize their business.
The Transformation
A Smart Network of Cloud-Connected Equipment
To support the business's need to understand demand in real time, r4 started by helping the company turn its installed base of equipment into a smart network of intelligent IoT sensors connected by the cloud. With this new connectivity, r4 combined real-time demand data with other data from across the company — including production, supply, sales, products, deliveries, sites, and equipment — as well as external demographic and location-related data, to create a unique, client-proprietary AI model of the company's business and markets.
The r4 Cross-Enterprise Management (XEM™) Engine then applied this model to uncover, at a location-specific level, previously unknown opportunities to improve business performance. Rather than replacing core systems, XEM connected them — routing the right intelligence to the right function at the right time.
What Changed Operationally
Sales & Revenue
- Optimized product selection and placement for each location
- Introduced the right new products to locations that hadn't stocked them
- Eliminated out-of-stock situations
- Increased equipment availability by remotely monitoring uptime
Operations & Supply Chain
- Improved forecasting accuracy reduced delivery frequency
- Optimized warehouse inventory levels
- Streamlined supply-chain operations end to end
- Lowered energy consumption via remote equipment management
The company's intelligent routing application now put the right SKUs on the right trucks on the right days, while automated loading and delivery instructions were sent to warehouse staff and drivers over the handheld devices they were already using. As a result, the company went from using large trucks that returned to the warehouse half full to using small trucks that came back empty.
Business Impact
Real Results in Only a Year
When commercial and operational data were unified into a single coordinated intelligence environment, the yield that had been hiding between silos became visible and capturable.
The algorithms in the r4 XEM Engine have been continuously learning from results. Continuous machine learning also enhances predictive accuracy, so that results continue to improve — without any human intervention.
Just one year after deployment, the r4 XEM Engine transformed the way the company is managed. By embracing XEM, the business exceeded expectations for growing new revenue, lowering operating costs, increasing profitability, and developing new competitive advantages. These results from the initial market also drove a decision to roll out the solution globally.
Creating New Competitive Advantages
By applying Cross-Enterprise Management from r4, this consumer-beverage provider unlocked capabilities that further differentiated it from the competition:
- Micro-targeted product-mix recommendations by location
- Accurate real-time inventory monitoring by location
- Inventory selection, order fulfillment, and delivery routing based on real-time demand
- Targeted real-time offers delivered directly to smart vending machines and a loyalty program mobile app
- Dynamic pricing