Uncontrolled truck arrivals are typical for many loadings or unloading stations. The result: demurrage costs, bad dock utilization, and process waste. Companies need real-time knowledge about truck arrivals to manage their warehouses in an optimal way. But how can they achieve this?
The following situation illustrates common practice within a lot of companies. Warehouse docks are planned and managed based on a one-off, static truck arrival schedule. As such, trucks are expected to arrive at specific times during the day, based upon which the dock employee capacity is estimated. Now imagine the following typical scenario:
One truck is expected to arrive at the warehouse at 2pm but is stuck in a traffic jam and is late. As a result, a dock employee tries to contact the driver of the truck to determine at what time the truck is expected to arrive. Unfortunately, a direct communication line with the driver is not available and the employee contacts the carrier instead. The carrier in turn needs to contact the subcontracted carrier, who in turn needs to contact the driver for the actual status. In the meantime, the shipper reassigns the dock employee other warehouse tasks as a no-show is assumed. Administration is prepared accordingly. Suddenly, the truck shows up simultaneously with two other trucks that arrived on time as the last trucks of the day.
The above, vivid description represents an uncontrolled truck flow typical for many (un)loading locations. The disadvantages and consequences are many and include, among other things:
- Increased demurrage costs due to long waiting times in the yard
- Inefficient dock usage, which effects the internal material flow routing, process times and costs
- Unreliable dock capacity scheduling due to unpredictable truck arrivals leading to inefficient resource utilization
- Multitude of process waste due to manual follow ups, emails and phone calls to find out actual statuses
Imagine the advantages of managing trucks in real time whilst maintaining a direct link to drivers for effective communication
The Camelot Dock Scheduler Optimizer (DSO) application provides the infrastructure to facilitate just that. It integrates directly with the shipper’s transportation management system. Loads (in the form of freight orders) from the transportation management system are sent to the DSO application to arrange a pickup time. Obviously, the DSO application is set up to reflect the warehouse dock capacity and working times.
Carriers or drivers access the DSO application to organize an appointment for (un)loading, based upon which truck tracking commences. Trucks are traced through a connected app on the driver’s smartphone. Based on HERE data services, the estimated time of arrival (ETA) is calculated. Alert functionality triggers warnings to dock employees in case of significant deviations in the ETA.
The usage of the smartphone app then enables direct communication with the truck driver. Hence, information is exchanged efficiently and effectively, which ensures a smooth change of the dock schedule.
A cooperation with Synfioo, the ETA experts, now extends the DSO application
Synfioo is the first company to calculate an integrated process ETA for intermodal supply chains. The coverage of almost all possible disruptions along the supply chain through direct integration of many different telematics services makes Synfioo’s holistic approach to ETA prediction unique.
In addition to HERE data services, Synfioo combines a multitude of real-time data sources to improve the quality of the ETA predictions significantly. Driver telematics data, for instance, are included to add exact driver break times in the calculation.
Based on machine learning, an algorithm processes real-time data on weather, traffic, traffic jams and construction sites as well as about 50 other influencing factors and combines them with telematics and transport data to provide a detailed view of complex and multimodal transport chains and possible disruptions. The outcome: greater transparency in supply chains, empowering transport planners to manage their transports by exception.
Optimal supply chain visibility
Integrating the two tools provides companies with an ideal way to manage their truck flow in real time. As such, supply chain disruptions can be managed early and proactively leading to demurrage cost reductions as well as to improved dock and dock resource utilization.
The authors would like to thank Alessandra Wischnewski for her gracious support in creating this article. Alessandra works in the field of logistics and supply chain. With a focus on transportation management and track and trace solutions she is looking for new ways to enhance supply chains transparency.
