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ThingTech: Availing Real-time Data for Fleet and Asset Tracking

Tim Quinn, CEO, ThingTechTim Quinn, CEO
The technological advancement in geo-location services has transformed the logistics landscape. The introduction of fleet management solutions has enabled customers to manage mobile workforce, monitor movement of assets and much more. However, real-time visibility and performance monitoring are major concerns for companies in the logistics landscape. Enterprises have invested in technology for integrations of their systems with the fleet but are still searching for efficiency and augmented customer experience. “Customers want real time updates and status on their assets, mobile workforce, and distribution network,” says Tim Quinn, CEO, ThingTech. While addressing the rising concerns of connectivity, ThingTech, a Georgia based solution provider, with a ‘connected customer’ approach delivers cloud-based solutions for tracking assets with integrations into the customer’s CRM and ERP systems. These integrations provide route optimization, fleet tracking, and mobile workforce management, thereby, reducing fleet operating costs and improving on-time performance. The connected environment creates a collaboration portal using mobile applications to distribute information.

ThingTech delivers a suite of real time cloud solutions comprising of tracIT, maintainIT, routeIT and workIT. The product suite provides complete real-time fleet and asset tracking, and monitoring solution for supporting the entire lifecycle. The offering is used to track and manage assets in real-time, optimize and plan routes, and maintain those assets through preventive and corrective work order management. The mobile applications in the suite enable the field and mobile staff to collect data and inspect the fleet, heavy equipment, and machines. “The platform is both device and carrier agnostic allowing us to support and integrate real-time location, and utilize data from GPS devices to automate alerts,” says Quinn. This feature provides the customers with substantial flexibility while choosing the proper tracking and monitoring equipment, and communication infrastructure. With the reporting and analytics component incorporated in the solution, customers can access meaningful information for operations, driver scorecards, capital planning, and replacement.


The platform is capable of capturing and integrating large amounts of real-time data into the customer’s daily business workflows


In addition to cloud solutions, ThingTech also offers Asset Intelligence Platform Tools to support the integration of major components like vehicle GPS and sensors, geospatial and location based systems, cellular communication gateway and CRM / ERP connectivity to back office. “The platform is capable of capturing and integrating large amounts of real-time data into the customer’s daily business workflows,” says Quinn. With this capability, the platform provides insight for better delivery, safety and customer collaboration. The delivery of these products is peppered with customer success programs to ensure the utilization of the solution to an optimum level.

With the delivery of intuitive cloud-based solutions, ThingTech has enabled numerous clients in the logistics landscape to collect and share asset data. For instance, Atlantic-Pacific (AT-PAC), a service driven logistics company, used paper processes and technologies to manage their inventory, equipment rental, asset tracking and inspection processes. “We streamlined warehouse, inventory, and mobile field data collection with RFID tags and integrated these data silos into a single enterprise container for end to end visibility of the equipment,” says Quinn. While moving the equipments with these tags from the warehouse, the customers will be notified in the application in real-time.

With these solutions benefiting the logistics industry, ThingTech plans to expand their ThingX Connect™ API server to support latest real-time tracking and monitoring technologies. ThingTech envisions launching of a major release in early 2016 which will incorporate big data and predictive analytics around engine diagnostics data captured from the vehicle. “These tools will allow our customers to move from a “find and fix” model to “predict and prevent” model,” concludes Quinn.