The Ultimate Manufacturing Corp.’s VP of logistics put down the report and smiled. There had been considerable resistance two years prior, when he had engaged Smoke & Mirrors Logistics, but the company’s performance report for the previous month showed it to be consistently exceeding the requirements of its service level agreement (SLA). In particular, its put-away performance had been outstanding, as it had been every month since the firm’s launch. The SLA specified two hours from goods receipt to put away, and the task was always completed well within the requisite time—often within one hour. Such performance reports were provided for all of the company’s operations, including manufacturing, materials management, line-side kanban replenishment and anywhere else that physical activity took place.
But what was that performance report based upon? Since what is being measured is a physical activity, the report could be based only upon observations of that activity. In the case of the requirements for put-away, that activity would consist of moving goods received from the inbound dock door to their correct storage location. The time taken to accomplish this is measured from when the products crossed the receiving dock door until the time at which they were put away. The SLA allows two hours for this task, so provided that all goods are put away within that timeframe, the SLA has been met.
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But how was that data collected? Currently, most warehouse operations do not record the exact time that goods arrive through the receiving dock door. It’s much more likely that a manual bar-code scan of the received goods or pallets is performed on the inbound dock itself, though it’s also possible to scan inside the truck before offloading. When the received products are moved to their storage location, the goods or pallets are scanned once more, along with a location code, thereby indicating that put-away has been completed. The time between that first receiving scan and the put-away scan is the total put-away time, as specified in the SLA. So everything is OK, then?
It might not be. Imagine a scenario in which the logistics service provider (LSP) is short of warehouse associates, and thus risks not meeting the SLA. What if the truck were unloaded, and its contents temporarily staged at inbound, until sufficient labor was available to complete put-away, preferably in half the time specified in the SLA? That first scan is delayed until the LSP is sure that put-away can be completed well within the SLA’s stipulations. No receiving scan is conducted, so the start time for the put-away measurement has not yet been triggered, even though the goods have been received.
The system would not record what had physically occurred. Consequently, the logical and physical inventory counts would be out of sync, and the LSP’s reported performance would not match the actual physical performance achieved. Indeed, the reported performance would far exceed the actual levels. The LSP’s customer would be happy, perhaps even extremely pleased, with the LSP’s performance above and beyond SLA. But they would be happy about the performance that they did not receive, instead of being concerned about the one that they should have received but didn’t.
So what can be done in these situations?
Good supply chain practice is to try to get logical and physical data to match as closely as possible. This has numerous benefits, but ensuring that a company’s accounts accurately reflect its current assets on hand is reason enough on its own. No system is foolproof, but the use of radio frequency identification can get you much closer to recording data that matches what is physically taking place.
If your RFID infrastructure and processes are correctly set up, then just bringing each pallet or carton through the receiving door, past the antennas, should automatically record that receipt at the precise time that it actually physically occurred. And this principle of automatically and logically recording what is physically happening can be applied to many other supply chain processes as well, such as a manufacturing stage being executed, or a completed unit leaving the end of a manufacturing line.
Most business decisions at your company—even top-level strategic ones—are based upon business intelligence that is usually an aggregation of what has taken place within your operations. Indeed, all levels of reporting, except that of the raw physical events, are aggregations of those events. Reporting volumes, production rates, capacity usage, process times, inventory levels, inventory turns and order cycle times are all examples of aggregations of raw data regarding a physical event that took place within your operations. So it follows that anything you can do to improve the quality of your raw physical event data will ultimately improve the quality of those aggregations, management reports and business intelligence.
Implementing RFID into your processes can often provide an increase in the accuracy of that raw data. And it can make it viable to collect information more frequently, at a more granular level, and in areas where it was not viable to do so before.
RFID is an exciting technology. But the intelligent use of the data that the technology collects can be even more exciting—and good for your business, too.
Ian Robertson, formerly Hewlett Packard‘s worldwide program director of RFID, is the CEO of Supply Chain RFID Consulting. Robertson is also the author of Improving Supply Chains Using RFID & Standards, a book that explains how RFID data can benefit businesses, from the receiving of raw materials all the way to the sales of end products to customers or consumers, as well as the benefits of employing the technology to process returns through reverse logistics. Copies of the book may be purchased at RFID Journal’s Web site.