Reading the Logistics Radar Screen
Private network proliferation and the Internet’s global commercialization improve productivity in manufacturing and customer-facing business operations. But at the interface between information technology and the physical world of transportation and logistics, we still have a long way to go.
The flip side of the IT revolution is that the quality of data fed into logistics management systems is often unknown or the quality is suspect. Errors can be introduced into systems through inaccurate or incomplete data entry, delays in communication across a system, or because data produced by one source is not presented in the proper format across an extended supply chain.
A New View of Logistics
While automated data collection technologies such as GPS and RFID location systems address aspects of the information quality problem, the concept of fully automating source data collection is not practical on a global scale. The answer lies in the ability to merge the available information inputs into a single, reliable system for communications event management and logistics execution.
One possible image of the information overload solution is a logistics radar screen. Imagine the equivalent of air traffic control radar, providing a constantly updated view of all relevant activity within a well-defined, multi-dimensional environment.
Instead of a specific physical airspace, a logistics radar can scale its view across a wide range of parameters. The screen view of a logistics environment can be defined to include all available data on a given shipment, status of specific items in transit, or a combination of views across time and physical locations.
Reading the Radar Screen
The key to effectively operating a logistics radar screen starts with the ability to accept any type of relevant data, and to generate instructions and actions in formats that can be easily transmitted. Inputs include legacy and EDI data, manually scanned bar-code and key punch entries, wireless and wired communications from phone and fax sources, and automated inputs. Outputs are equally varied—from automatic routing change orders, to e-mail, fax, or pager alerts calling for human intervention.
When evaluating IT solutions for a logistics network, managers need to look closely at both the level of support for multiple data inputs and data communications flexibility. Systems are often designed around a limited number of data types, such as forecast-driven demand supported by EDI. This can limit flexibility because it may limit a user organization’s choice of logistics providers to companies with compatible systems.
Building a system that accommodates multiple data inputs also creates a new opportunity to improve the logistics network’s intelligence. It becomes possible to set values for the accuracy of different types of data. This knowledge can be used in regular operations to provide alerts for verifying or validating data when needed and to set priorities for data collection methods depending on the value of different in-transit items.
Creating a data reliability ranking also helps to develop a clear understanding of the cost-benefit equation for different data collection methods, and to evaluate the payback for investment in new technologies.
Working Smarter
One example is the increasing use of RFID source data collection by pallet and container suppliers. Adopting reusable plastics laid the groundwork for container management firms to bring new value to the industry. With RFID tags, each pallet or container is transformed into an information asset. The data produced about location within a distribution center and asset movement through antenna-equipped choke points has a measurable value both to the container’s owner and to shippers and receivers.
In locations with a tag reader infrastructure, however, the technology does provide accurate, automated information feeds to the logistics radar screen, enabling users to make real-time adjustments and corrections as the supply chain executes.
Ultimately, the logistics industry’s IT revolution will create a new class of knowledge worker. Providing the means to gain greater control over logistics processes will enable logistics managers to use time more efficiently, leading to increased productivity.