Manufacturing and distribution organizations can learn a lot about the back-end logistics of their operation through data mining and analytics. Fleet managers can analyze massive amounts of data to expose flaws and recognize trends surrounding the delivery of their merchandise.
Big data is aptly named, however, and in many cases, an organization's leaders may be overwhelmed by the amount of information he or she has access to and may not know how to interpret it. Collecting data in the tech age is a breeze, but interpreting it can be another story. Information is mined throughout the manufacturing and distribution processes and tracking should not stop when packages leave the dock.
The ability to collect data during all stages of the supply chain arms managers with information they may not even realize they needed. Companies may discover that a particular account eats up a large amount of delivery time and expenses, and can adjust freight rates accordingly.
Data Collected in Real Time is Easier to Analyze
One way for an organization to streamline the analytical process is to use mobile automated data collection that syncs directly with ERP software. When barcodes are scanned and cargo data is logged, analytic teams can draw more accurate conclusions from the data. Automated data collection software products that update in real time from any location mean that whether a package is in the warehouse or in transit, important data can always be logged.
Data collected from the fleet provides useful information about the drivers, in addition to the products they are carrying. Mining the correct type of data can help explain driver turnover, damage rates and accidents rates. Perhaps packages on trucks that leave the warehouse late are found to have higher incidents of damage. Trucks that leave at dusk may also be more likely to get into a wreck and damage merchandise. Using automated data collection, organizations can keep an eye on merchandise throughout the entire supply chain process.