Trucks equipped with IoT sensors capture truck utilization and loading efficiency data. However, there is no scalable framework to understand what of those metrics can be used to generate actionable insights to improve truck utilization and load-time efficiency. What further stands in the way of Retailers adopting these sensors permanently is the lack of a tool that could translate the improved efficiencies into ROI $ for the Retailer. Without such a tool, the risk of converting pilots to real engagements remains high when the trial period ends.
First step, to overcome lack of clarity on what metrics to use, was to leverage sensor data from active pilots to arrive at actionable alerts. Second, was to set up an alert system that would send real-time nudges based on deviations from best practices across these metrics. Third, formally establish customer baseline metrics “the Before” to compare against “the After” of pilot installation necessary for ROI calculations. Final step was to standardize the metrics measurement framework from the improved truck utilization and load efficiencies in order to articulate customer ROI.
With the logistics solution sensors now enabled with ROI analytics, the large scale adoption of these IoT sensors by Retailers has increased.
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