I’ve been hearing one word a lot lately—”predictability.” Companies that have deployed radio frequency identification technologies are finding that the massive amounts of data the system provides cost-effectively essentially enables them to anticipate what will happen in the future and be ready for it.
Last week, I attended an International Air Transport Association (IATA) meeting focused on RFID. A senior executive from one airline told the gathering that his firm performed a fleet overhaul a few years ago and had found that a large number of oxygen canisters were nearing their expiry date (they all had been on airplanes purchased at the same time, roughly 15 years prior). As a result, the firm incurred an unexpected $3 million expense to replace all of the canisters. Now, he said, “With RFID on each canister, we know exactly how many canisters are expiring next month, and the month after that and the month after that. This enables us to have the right number on hand to replace them, and to forecast our expenses more accurately.”
Health-care organizations that have deployed a real-time location system have found that they can track utilization rates, something they never could do before. This ability enables them to forecast, based on previous years’ experiences, what the need will be for certain pieces of equipment. They can then use this information to predict rental expenses and reduce capital expenditures on new equipment that they know will not be needed.
I spoke recently to a manufacturer that is using RFID to track tools. The company installed a reader in its repair shop, so that it could know when a tool was unavailable while being repaired. After a year or so, the firm realized that the data being collected allowed it to predict when tools were likely to need servicing. It began conducting preemptive maintenance to ensure that tools did not break and disrupt manufacturing work.
Retailers have been using data collected from readers in dressing rooms to determine problems with some items. They find that one size or style might be tried on 100 times with no purchases, while most others have a relatively stable number of purchases. This means there is a problem with that item’s fit, and that it can be fixed proactively.
Retailers are also realizing that accurate data regarding replenished items lets them order more effectively. In the past, a retailer had limited insight into sales trends, because inventory data was so inaccurate. Did an item not sell because customers didn’t want it, or because it was never put out on the sales floor? Did a particular pair of jeans sit on the shelf for a day, a week or a month before being sold? Did a specific product come from a shelf in the back of the store or a special display up front? Was an item stolen via the main store exit or an employee exit?
RFID provides 95 percent inventory accuracy (higher if you cycle-count more often) and enables individual items to be tracked, so retailers can identify trends they could not previously see. One retailer told me it can now view the percentage of stolen items that move through its front, side and back doors, and it is deploying resources to reduce theft.
Carlo Nizam, Airbus‘ head of value chain visibility, who now leads the company’s digital strategy, likes to say: “Without RFID, there is no big data—only more data.” By that, he means RFID alone can provide the volume and granularity of data required to perform predictive analytics. Based on what I’ve been hearing lately, I think that’s exactly right.
Mark Roberti is the founder and editor of RFID Journal. If you would like to comment on this article, click on the link below. To read more of Mark’s opinions, visit the RFID Journal Blog, the Editor’s Note archive or RFID Connect.