There is no question that in its early days, the development of Automatic Identification and Data Capture (AIDC) was driven by innovations in dedicated scanning hardware. However, in more recent years, smartphone innovation has become the driving force in continued AIDC evolution. And the retail supply chain will never be the same.
Let’s start with a look at the state of AIDC in the 1980s. Dedicated scanning devices were the dominant means of capturing supply chain data. Smartphones with built-in cameras were decades away from hitting the market. Existing mobile phones had low screen resolution and limited battery life. There was no real need for supply chain organizations to look beyond dedicated scanners to perform AIDC.
However, something interesting started happening as the 1980s gave way to the 1990s. The design of dedicated scanning hardware became more ergonomic and screens grew larger. But there was no significant new innovation in the capabilities of dedicated scanning devices.
In contrast, the 1990s were the decade when mobile phones started morphing from bulky toys for tech connoisseurs to convenient consumer devices. Mobile phones entered an ongoing period of dramatic evolution in both form and function. As they became smaller and sleeker, mobile phones also kept improving their screen resolution and battery life.
Apple’s introduction of the first iPhone in 2007 is generally seen as the birth of the first true smartphone. The iPhone offered dramatically superior screen resolution and battery life. In the decade since the iPhone’s release, smartphones have continually improved in these areas, and also expanded to other operating systems such as Android and Windows.
In addition to offering better screen resolution and battery life, the iPhone also revolutionized the very purpose of a mobile phone. Beyond serving as basic communication tools, smartphones have become outstanding data capture devices. High-performance CPUs, high-end image sensors and advances in machine learning enable smartphones to empower the connected worker far past the potential of dedicated scanners.
In the retail supply chain, connected workers equipped with smartphones can move beyond scanning one barcode at a time to improve operations across the enterprise. In the back end, smartphone-based scanning enables faster inventory counts. Meanwhile, store associates can accelerate their search and find efforts and ensure planogram compliance. And these are just a few examples.
The evolution of mobile data capture is a continuous process. As smartphones are fulfilling tasks once performed by dedicated barcode scanners, other devices have begun assuming functions previously executed by smartphones.
These include “hands free” devices such as wearable “smart” glasses, as well as “hands off” devices such as robots and drones. Especially for retail supply chain tasks that involve large amounts of repetitive scanning, such as inventory management, removing hand motions from mobile data capture makes sense from ergonomic and efficiency standpoints.
In addition to evolution in device platforms used for mobile data capture, there is also ongoing growth in the type of data mobile devices can scan and decode. Thanks to the emergence of technologies such as Optical Character Recognition (OCR) and Object Recognition, in the future retailers will be able to identify multiple issues on the shelf with a single scan.
For example, an associate at a grocery store might use a mobile device to capture a wide variety of data points from all the different items on a multi-level shelf, in one scan. In addition to verifying the presence and number of individual products by barcode, that single scan could also decode prices with OCR and compare them to the current product database, allowing the instant detection of wrong prices.
Other shelf-level issues that could be identified in real time with a single scan include out-of-stock (detecting empty shelf space with image recognition), low stock (determining a shelf is partly empty with object recognition), and wrong product placement (comparing product visual to shelf barcode information).
OCR can also provide tremendous value in shipping and receiving. For example, a delivery driver could read important information such as addresses directly off delivery labels, ensuring that the right packages reach the appropriate recipients.
Another emerging technology starting to make its presence felt in mobile data capture is augmented reality (AR). AR superimposes digital information into the screen view of a smart device. In one of many instances where AR-enhanced mobile data capture can streamline retail supply chain operations, the information on the contents of plain brown boxes could be displayed at the scan of a barcode, allowing store and warehouse associates or delivery drivers to quickly identify which boxes need to be opened or delivered.
AIDC has moved far beyond the constraints of dedicated scanning hardware, and continues expanding all the time. As new technologies and new device form factors evolve, the capabilities and potential of AIDC evolve with them. The one sure thing we can say about the state of AIDC is that it is constantly in motion.
Christian Floerkemeier is the VP Product, CTO and co-founder of Scandit (www.scandit.com), the leading software platform to turn smartphones, tablets and wearable devices into enterprise-grade barcode scanning and data capture devices for employees and consumers.
