It’s accepted wisdom that what you do with the data you capture is just as important as capturing data accurately. Yet since the introduction of bar code systems back in the early 1970s, discussion of data capture has often focused on what’s new with scanning and data collection devices: are they wireless, what type of codes can they read, and what are their ruggedness and ergonomic qualities?
Do these device trends matter? Sure they do, say providers of automatic data collection (ADC) technology—it’s only that the focus is now swinging toward what you do with the data—on how you can apply real-time monitoring and analytics to instantly adjust operations in this era of omnichannel fulfillment challenges.
“While there are new and improved ways to continue to enhance hardware devices in areas like battery management and durability, that’s not really what’s driving the movement and interest in using the data streams from supply chain processes,” says Bruce Stubbs, director of supply chain marketing for Honeywell Sensing and Productivity Solutions. “The underlying issue is how to turn data into actionable insights.”
ADC equipment sales continue to grow at a healthy pace. The main technologies include bar code scanners, which according to analyst firm VDC, should see sales expand at a compound annual growth rate of 3% to 4% through 2019. In the bar code printer segment, sales of small, mobile printers are growing faster than stationary units, while voice-based data collection should grow at about a 5% CAGR through 2019, according to VDC.
The ADC landscape also includes wearables such as ring-based scanners, smart glasses, and more use of Android operating systems (OSs) by ADC suppliers. But the biggest thing in data capture may be the use of sensors and other Cloud-connected systems that are truly “automatic” in the way they capture data. Rather than having to press a scan button or speak into a headset, Internet of Things (IoT) technology is seen as a means of capturing continuous data streams that could help the industry curb supply chain costs or even ensure a safer food supply.
ADC suppliers are responding by placing more emphasis on dashboards that address real-time adjustments to operations, as well as solutions such as sensors and monitoring. Whereas once ADC solutions were about carrying out distinct data collection routines, now ADC vendors are taking aim at broader concepts like “always on” supply chain visibility.
“We have systems now, which using a variety of technologies, give you real-time locating over people, assets and materials,” says Mark Wheeler, director of supply chain solutions for North America with Zebra Technologies. “With that visibility, you can do many things, and without it, you are constrained.”
The technologies for better visibility, says Wheeler, include passive and active radio frequency identification (RFID), connected sensors for monitoring refrigerated trailers and “cold chain” conditions, as well as solutions that monitor the loading of trailers. Such smart infrastructure, as Wheeler calls it, also benefits from IoT platform software such as Zebra’s Zatar that simplifies connectivity.
One example of a real-time monitoring solution, says Wheeler, is Zebra’s Trailer Loading Analytics solution, a connected “appliance” with camera and 3D imaging technology that looks into trailers as they are being loaded to ensure they are being cubed out and loaded correctly. Wheeler sees some differences between point systems such as trailer load monitoring and IoT applications such as cold chain monitoring, but says they are similar in that they move data capture away from being just a “snapshot” of a physical process toward “constant visibility” solutions.
With Zatar, Zebra has been working with other vendors to simplify connectivity. For example, says Wheeler, earlier this year at Modex, Zebra announced collaboration with Bosch Connected Devices and Solutions to offer a reference design for the development of food safety solutions. Zebra also has partnered with SAP to offer connectivity between Zatar and SAP’s HANA Cloud platform.
These types of partnerships, says Wheeler, make it relatively easy for end user organizations to pilot IoT based applications or to integrate IoT data to enterprise systems. So even while IoT adoption is still early days, deployments could accelerate quickly because IoT projects won’t face the type of big bang deployments common to major enterprise systems. “Current system architectures can be costly and complex to implement and change,” Wheeler says. “We want to change that dynamic and have ways of gaining visibility and solving problems that can be deployed quickly.”
Stubbs agrees that cold chain monitoring is a high-value solution area because it gives constant visibility into the safety of goods, and can be combined with alerting and business rules to allow proactive responses to emerging problems. “You never used to have that continuous monitoring over conditions,” says Stubbs. “Now as a manager, you can have alerts pushed out to you, and when you know there has been a problem, you can collaborate with other departments to possibly cut a replacement order versus just waiting until you actually see and discover the problem.”
Suppliers also are adding more decision support solutions that look at data captured by bar code scans or voice picking so operations can be adjusted on the fly by DC managers. While voice picking is touted as a way to make labor-intensive warehouse processes hands free and more productive, managers now have more monitoring tools that look at voice picking processes in real time and alert them to trends that could harm productivity, accuracy or warehouse costs.
For example, says Stubbs, Honeywell now offers a “workflow performance” application as part of its Operational Acuity family of solutions that is constantly looking at voice picking activity to spot negative trends. For example, managers can know if specific pickers are picking the wrong item consistently or skipping locations. And, on a broader workforce level, if the costs of picking are skewing above target, DC managers can see the problems and react. “Now, if I’m getting alerts about critical aspects of my order fulfillment process on a realtime basis, I can look at the trends and decide the best way to adjust my operations to make things better,” says Stubbs
As part of operational improvement and cost efficiency initiatives, DCs are looking ways to leverage data gathered during picking and other tasks to drive productivity, according to Ron Kubera, executive vice president and chief marketing officer with Lucas Systems. New dashboard-type applications can turn data gathered during voice picking, for example, into actionable information for warehouse associates and managers.
“At one level, it’s ensuring the users— the people performing processes like picking—can see what the expected or standard level of performance is, and if they are falling behind, they are notified of that through the application,” says Kubera. “But it’s also the supervisors on the floor getting visibility into current performance of all the individuals in the warehouse and, through a dashboard view, being able to marry that up with information on the outflow of goods and customer expectations. So we’re moving toward very actionable use of data being captured, so you can do things like reallocate workforce based upon the near real-time performance of the operation.”
On the hardware front of data capture, says Kubera, there is increased user interest and uptake for Android devices that are low cost and easy to use. While the devices typically need a rugged case, in voice picking applications, they can be tucked away and well protected, while application vendors can make use of technology such as near field communication (NFC) in the devices.
NFC in Android devices can potentially be used for location confirmation, says Kubera, as can mobile picking applications that support RFID as a data input. The thinking is that either through NFC communication or RFID reads of tags on assets like bins or racks, picking processes can gain precise location awareness and accuracy without adding a lot of infrastructure or burdensome data collection tasks.
“Companies with warehouse operations can face significant penalties from customers for inaccurate or incomplete shipments, so location awareness—being able to easily confirm that pickers are at the correct location—carries tangible benefits,” says Kubera.
Of course, ADC gear such as handheld scanners continue to evolve. Suppliers are adopting the Android OS to run rugged ADC devices, and improvements in ergonomics and device management continue to be a common focus.
For example, Zebra’s new TC8000 handheld scanner features a screen that is oriented toward the user point of view while scanning, thus reducing the need to tilt the device to be able to read the screen to verify information, says Wheeler. The design is said to improve user productivity by 14%. “Anytime we can make the ergonomics of a device better, we improve productivity and accuracy,” says Wheeler.
Small mobile printers are another notable bar coding trend, says Wheeler. They are catching on because they eliminate travel involved in reaching stationary printers to retrieve large batches of labels. Printing on demand “at the point of activity” in DC processes also improves accuracy, Wheeler contends, because there is less likelihood of applying the wrong label to the item or carton.
Android is gaining momentum in the ADC world, observes Stubbs, but more so in field service and logistics. For most high-volume scanning duties in DCs, says Stubbs, there are some user organizations who want Android devices, but they usually want them to be fully rugged, purpose-built devices capable of standing up to the DC environment.
While providers of data capture technologies are evolving to address IoT, sensors and higher-level decision support, it’s not as though bar coding is becoming obsolete. According to a “Warehouse Vision” survey from Zebra that looked at warehouse investments over the next few years, by 2020, 62% of respondents cited plans for IoT solutions, and 76% plan for real-time locating. The survey also found that 68% will invest in bar code scanning.
Thus the likely scenario is that bar code systems and rugged mobile data collection devices will continue to be core solutions for data capture, even while DC operators begin to phase in more systems for real-time locating, or IoT-based monitoring for applications such as food safety
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