PeopleNet, TMW announce product integrations

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Updated Sep 28, 2012

PeopleNet, a provider of innovative and integrated onboard computing and mobile communications systems, and TMW Systems, a provider of transportation management solutions, on Monday, Sept. 24, announced new integration features for both TruckMate and TMWSuite to make drivers and dispatchers more efficient.

“These new and enhanced features are the result of our continued joint focus with TMW Systems on helping our mutual customers more deeply leverage their in-cab technology investment in our Tablet and Blu computers,” said Randy Boyles, PeopleNet vice president of tailored solutions, making the announcement at the TMW Systems TransForum 2012 User Conference and Exhibition being held through Sept. 26th at The Peabody Orlando in Orlando, Fla. “By further expediting in-cab and back-office workflows, we are adding new efficiencies that generate even greater productivity throughout fleet operations.”

New TruckMate functionality includes enhancements that embed decision-tree forms within Automated Workflow for prompting the driver upon stop arrival. Auto-arrive and depart geofences further enable monitoring of terminal stops. New customizable looping and branching enhancements to embedded decision-tree forms help less-than-truckload fleet drivers who have multiple freight bills. Decision-tree forms embedded in PeopleNet’s Automated Workflow as part of the TruckMate dispatch automatically prompt the driver at designated points after arrival, so drivers don’t have to search for blanks to complete, helping to make form completion faster and more accurate.

Another new TruckMate feature that allows dispatchers to customize stop profiles with either an “arrive” or “depart” geofence enables complete monitoring of terminal stops. If a driver is at a terminal when starting their load, a “depart” geofence indicates that the driver is leaving the terminal stop. The departure initiates a load progression that follows the departure with an arrival, etc. In addition, dispatchers can select or deselect stops from the “load offer” screen in Automated Workflow and send an updated dispatch reflecting their changes.

TMWSuite integrations have been extended to include signature capture for fleets equipped with Tablet; another new Tablet integration allows signatures captured on a form to be accepted by TMWSuite and automatically entered into its billing system, helping expedite and automate billing immediately after a customer receives a load and improving cash flow.

The two companies also announced a new integration between PeopleNet’s Vehicle Management engine data and TMW Systems’ TMW Data Warehouse to enable custom ad hoc reporting that meets a variety of information requirements across key operational metrics such as asset utilization, compliance to fueling program, on-time deliveries, idle time and percentage, and profit analysis as examples.

“Recognizing that executive management needs access to a variety of different information affecting different business objectives and profitability, the amalgamation of engine, dispatch and maintenance data within TMW Data Warehouse creates an opportunity for ad hoc reporting through TMW Data Warehouse Explorer about key performance indicators across fleet operations to enable proactive decision-making that supports achievement of business goals,” said Kerri Tabor, PeopleNet manager of integration services.

As tools to help with decision-making, these comparative reports benchmark performance and highlight areas for improvement as well as progress in meeting daily, weekly, monthly, quarterly or yearly business goals across all operational areas. The reports provide flexibility to drill down to the desired level of detail in critical areas in need of improvement.

“Through inclusion in the TMW Data Warehouse our customers can create reports relative to operational and fleet maintenance content from other TMW systems,” said David McKinney, vice president and general manager, Optimization, for TMW Systems. “This marriage of data creates new relationships for historical analysis and brings us closer to predictive modeling based on reports from the asset in near-real time.”