I had a chance to spend a few hours with the folks at a large global food manufacturer discussing the evolution of their mobile app strategy. The company has been using a GPS-enabled mobile app with its thousands of sales and merchandising resources for over five years.

What started as a strategy to track its field resources to automate the payroll process, has turned into a large-scale program to improve productivity and performance.  In my view, this manufacturer reached the second wave of value in mobile apps – using all that great data to gain a better understanding of what its resources are doing in the field and using it to recalibrate its planning processes and management strategies.

For this manufacturer, the second wave returns have been as compelling, if not more, than the benefits achieved during the initial deployment.

Why GPS Tracking for Fleets is a Must-Have

Unless you are tracking your field resources with a GPS-based mobile app, you have no idea what they are really doing. Field workers are largely unsupervised and, unfortunately, there are a few "bad apples" in most organizations who aren't entirely honest about reporting their activities.

"Stretching" is also particularly prevalent, with hours worked and/or miles driven "rounded up" in an overly optimistic manner. If you want to know where you are losing 2-3% of your productivity and costs, it could be right there. On the other side of the coin, without accurate tracking, it can be difficult to identify and reward high performers among those largely unsupervised field workers.

Which brings me to the second point - mobile data is untapped performance improving gold. This manufacturer captures billions of data points every year.

Every GPS ping tells a story; one that you wouldn't get from doing the monthly ride with one of your field resources. A lot of mobile data is transactional (stop location, arrived, depart, etc.), but provides a wealth of operational performance information because GPS tracking for fleets provides the time, speed, and location context.


Telematics-Driven Transformation

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Enhance Planning and Performance with Operational Data

Using analytics applications and machine learning with that data can determine the true picture of good and bad performance, break down field performance into its fundamental components, and determine what key planning parameters like stop and drive time and customer location should be.

Getting the fundamental view of what is happening in the field provides a tremendous opportunity to improve the planning processes, management strategies, and human resource policies. Planning without operational data is an open loop process that runs off too many assumptions.

This particular manufacturer was able to use the operational data to determine which factors really impacted its planning processes. The company actually simplified its planning models and can now more effectively deploy its resources to drive sales. Management is now focused on exception management and spotting workforce trends.

An interesting and counterintuitive point that occurred over time was the simplification and streamlining of the company's mobile app and data collection process. While the natural inclination is to capture as much data as possible, it became apparent that data capture consistency was more important than breadth of data collected.

With a fair amount of turnover and part-time employees, ease of use became as important as determining what data they wanted to capture and they didn’t want the mobile app to be another reason for employee turnover.


There were two key takeaways for me from this conversation. First, if you aren't using GPS fleet vehicle tracking mobile apps with your field resources, your company is experiencing higher costs and more inconsistent customer service—you just don't know it. Second, all that transactional data you are collecting as part of your mobile strategy to go paperless or simply track your resources can be turned into a tremendously powerful continuous improvement program.

Technologies like machine learning can be applied in a “lights” out fashion to make the analysis process much simpler and evergreen.

Solution Highlight

Telematics and Compliance

Written by Chris Jones

Executive Vice President of Industry and Services

Descartes Systems Group

Fleet Resource Center

Expand Your Routing, Mobile & Telematics Knowledge

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