“Woohoo! You have reached your destination and you can hold your head up high – BECAUSE YOU ARE A GENIUS!”
For those not familiar with America’s best-known cartoon family, that line comes from Homer Simpson and is the most downloaded voice “skin” for the TomTom GPS navigation system. Going beyond the simple overlay of voice skins from Homer, Ozzy Osbourne, or nearly any other celebrity, in-vehicle and after-market navigation systems continue to be pervasive and this sensor-based technology keeps evolving. In fact, while recently upgrading my mobile phone, I was pitched an offer by Verizon for a comprehensive in-vehicle monitoring system provided by Delphi. This is just another example of how sensors continue our progression into the Internet of Things.
This sensor-based technology is great for the consumer trying to get from Point A to Point B or for keeping a close eye on our newly licensed teenage driver in the household (I’m only 3 months from this…yikes!). However, what if we applied this same kind of solution to improve the visibility, insights and predictability in the supply chain? In a recent survey of more than 664 supply chain management executives, IBM listed visibility as one of the three rules for optimizing supply chain performance. This visibility necessity – and challenge — is the problem that Savi Tracking solves today, but instead of making sure the driver takes the right interstate exit, it monitors and measures the status of high-value assets in some of the most remote locations on earth (think dirt roads in sub-Sahara Africa). And, fortunately, it enables that monitoring from the comfort of your office thousands of miles away. It’s like a virtual TomTom and just as easy to implement, but manages an entire fleet. Unfortunately we do not have Homer’s voiceover…yet.
By leveraging RFID, GPRS, GPS and other technologies, Savi’s customers are able to pinpoint the exact location and state of the cargo in-transit. But we don’t stop there. We marry that data with other sensor data, such as real-time traffic and weather information, to avoid delays before they happen, saving fuel and labor costs. We can also consume location-specific Twitter and Facebook data to help provide a complete picture of the in-transit visibility situation (is the delay a simple fender-bender which will clear out quickly, or is it a multi-car pile-up that will take hours to clean up?).
By collecting and normalizing both real-time and historical streams of sensor data into a single view, Savi customers are jumpstarting their ability reduce risk, improve profitability and maintain customer loyalty – optimizing their overall supply chain performance. And that’s the value of knowing…brought to you by Savi.