- 50% reduction in customer stock outs
- 75% reduction in unnecessary deliveries
- Greater than 20% increase in delivery productivity
- Inflexible, static delivery model scheduled months in advance.
- Dependent on manually updated, resource-intensive spreadsheets
- Decentralized processes varied between locations
- Low customer satisfaction
- 20% of deliveries were too late
- 40% of deliveries were unnecessary
- Plants often failed to keep up with demand
- Raw material inventories were off
- Drivers generally failed to follow their routes
- Field leaders were so distracted by delivery planning issues that their performance slipped in other areas
Reddy Ice implemented John Galt's Atlas Planning Platform. The project aimed to centralize delivery processes and completely automate their demand planning utilizing near real-time data from a variety of sources.
Atlas was setup to receive data from drivers (inventory on arrival, delivered units, and did-not-service), weather updates, daily POS from many customers, and customer orders from their CRM.
And as part of an Internet of Things (IoT) pilot program, Galt placed internet-connected sensors in Reddy Ice iceboxes to monitor how much ice is being held at a given time. This data is transmitted to the Atlas Planning Platform every 30 minutes and is used to project when iceboxes will run out of ice.
The delivery execution system automatically re-plans every day for next day, taking the delivery planning period from several months to daily. And there is flexibility to shift plans based on weather updates.
Replenishment-related decisions (e.g., frequency, quantity and routes) were automated. The near real-time nature of the data helps to quickly identify anomalies that a projection could not anticipate, such as a spike (or drop) in demand. Atlas Planning helps Reddy Ice make adjustments on the fly, which minimizes delayed shipments and stockouts.
“Atlas has enabled us to become more profitable by allowing us to react more quickly to changes in our customers’ demand.”
Grant Daniel, Director of Delivery Optimization at Reddy Ice
Tags: Case Study