Technologies Needed for a True Digital Transformation

By Mark Roberti

RFID is just one element—a foundational element—of any company's digital transformation efforts. Here are the different technologies required at each stage of change.

Last week, I explained why I believe that radio frequency identification technology is the foundation on which most successful digital transformations will be built (see RFID Is the First Step Toward Digital Transformation). This week, I would like to explain how I see RFID meshing with other technologies to enable companies to truly transform the way they do business.

The first order of any company breaking down the barrier between the physical and digital worlds is to be able to identify, track and manage all physical objects that are part of its operations—files, manuals, tools, jigs, containers, vehicles, parts, raw materials, work-in-process, finished inventory and so on. For items that are relatively small and low-cost, and that have no power source, that means using passive RFID.

For mobile items that have a power source and/or are larger and more valuable, companies will likely use an active RFID transponder, a Bluetooth Low Energy (BLE) beacon, a Wi-Fi or ZigBee transceiver, or some kind of two-way radio devices. These are technologies that some now considered Internet of Things (IoT) technologies, even though the term "Internet of Things" was coined to explain that passive RFID would enable companies to connect low-cost items to the Internet.

The next level of digitization involves knowing the state of things in the real world. If a tool is overheating, a company might not find out until the motor burns out and the worker using it proceeds to the tool crib seeking a new device. With an IoT sensor (either active RFID, BLE, Wi-Fi or some other type of radio), abnormalities could be reported in real time. Workers could be alerted to stop using the tool and bring it in for maintenance.

Passive RFID sensors could tell companies whether water or humidity has gotten into a container filled with sensitive avionics parts, or pressure is building inside a container, or a pallet of produce is being stored at a temperature outside a predetermined range. Knowing the state of objects allows computers to issue alerts to managers so they can intervene to prevent problems, such as goods spoiling in the supply chain.

RFID and other radio-based technologies are not the only way to give computers visibility into what's happening in the real world. Two-dimensional bar codes can, in some instances, work fine, provided that an object can be oriented so the bar code can be read. Video is another powerful tool. Cameras are being used to track the movements of shoppers throughout a store and even, in the case of Amazon Go, to enable customers to pay for items without stopping at a checkout counter or approaching an employee with a mobile-payment device.

But video and 2D bar codes can't tell you how many sweaters are within a sealed box, and considerable computing power is required to analyze video. Therefore, these and other technologies will complement RFID systems and help ensure that companies cover all the things they want to track, even those they can't tag—such as customers.

The next stage of digital transformation is to give computers control of objects in the real world. The battery-powered radios on tools can not only provide location data, but also enable companies to establish computer controls over the devices. For example, a firm could put an active RFID tag on a person working in an aerospace factory and integrate a battery-powered radio device into a tool. When a worker approaches a tool he or she wishes to use, its tag could be read and the back-end system could look up whether that individual has authorization to utilize that particular asset. If not, a signal could be sent to the tool not to turn on when that person tried to use it. This a fairly standard rules-based IT application.

Artificial intelligence (AI) can be used at this stage if decision-making requirements are more complex. In a grocery store, for example, passive RFID transponders could identify products with expiration dates stored in the back-end system. If an item is approaching its sell-by date, or if a sensor indicates that it hasn't always been kept at the ideal temperature, AI could adjust the sell-by data and calculate the optimal price to sell the item before it expires. The system then could send commands automatically to passive RFID shelf labels (or product labels), and lower the price to sell the item before that can happen.

This is the stage at which digital transformation becomes truly exciting. Companies can now start to apply AI to decisions about every product they sell at each step of thes lifecycle, or each tool or vehicle it owns. The data collected can be shared with partners so they can optimize their businesses, and the benefits can flow back through the supply chain.

The final stage is to bring in outside sources of data and use big-data analytics to find ways to improve operations even more. Companies might layer demographic data, weather information, economic data or information regarding what's trending on social media on top of the data they collect about their own operations, as well as analyze it and find new opportunities to cut costs, increase sales or otherwise become more efficient.

Let's say, for example, a logistics company is tracking weather patterns and finds that when thunderstorms of a certain size hit Chicago at a given time of day, that causes delays in flights in other cities for which Chicago acts as a hub. The logistics provider might use AI to route flights around those cities, or utilize alternate routes based on the storms having a high chance of delaying flights from Chicago to a particular city. Computer systems would instruct workers and robots to automatically reroute certain packages (which are quickly and cheaply identified via RFID tags).

Retailers might use big-data analytics to find, for instance, that a 1 percent decline in economic growth in the European Union translates into a decline in sales of some high-end goods, and an increase in sales of some lower-end items. AI could be used to adjust the store layout and product mix, based on whether or not the forecasted decline actually occurs.

Most companies will not transform themselves digitally in three separate stages, completing one and then moving on to the next. It will likely make sense to undergo all three stages of transformation for some items, because the return on investment or value created is huge, and not transform other aspects to the business until later. But it's important for companies to have a clear roadmap of how they plan to transform themselves, as well as the technologies they will need to do that. RFID, for most firms, will be a key component.

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 or the Editor's Note archive.