GPS and Fleet Tracking Data Correlation Provides a Holistic View For Sales & Operations

A national plant wholesaler that supplies retail stores throughout the United States re-engaged Imaginet to work on a data correlation project. The client has greenhouses and production facilities across the country and a network of trucks to deliver products to various stores. The trucks have been outfitted with J.J. Keller ELDs and use the J.J. Keller Encompass Fleet Management Platform to monitor their GPS locations and other key metrics (e.g., engine RPMs, speed, and braking). In the Encompass system, each retail store has a defined geofence that shows the boundaries of that location, and it can track when a truck enters and leaves a store’s geofence. The Encompass data helped the client address safety concerns, schedule shipments, and improve staff efficiency, but they lacked a holistic view of their trucking fleet. They needed to bring the Encompass data into their data warehouse to determine where shrinkage may be occurring.

Imaginet built a utility in Azure Functions, using C# and the J.J. Keller REST API, to extract data (JSON files) from Encompass. The data was brought into Azure Storage, transformed through Azure Data Factory, and placed into the data warehouse (built in Azure SQL Database). We thoroughly reviewed, interpreted, and mapped the data from Encompass and, with Power BI, plotted the coordinates of the trucking fleet (organized by details such as speed incidents, locations where trucks are prone to speeding, and how long trucks spend at each stop). We used Agile methodology and Azure DevOps to create and track work items.

Imaginet helped the client connect their data source to their data warehouse to provide a clearer view of sales and operations, helping them make crucial business decisions, and optimize their processes to eliminate product waste and increase profits.