Big Data Driven Decision Making – Brought to you by AutoID Solutions

by Richa Gupta | 11/21/2014

Big data is a topic generating significant interest among AIDC industry veterans. Barcoding technology is making a wealth of information available to organizations. Defined generally, big data is simply a set of data too large to be stored and managed using traditional processes. Oracle breaks down big data into three general categories: traditional enterprise data, social data, and machine-generated and/or sensor data. Data capture technology contributes to the collection of this third category of data—machine-generated data – especially in retail, logistics, and supply chain environments.

This generic definition does not identify the specific advantages that big data brings to the supply chain. Big data is important in the modern connected world as the collection of ‘nontraditional’ data increases; information vital to accurate business decision-making can be found not only in transactional data collection methods, but even more so in imagers, machine vision, sensors, and scanners. The machines that produce these nontraditional data sets are now more than ever connected to one another in what is called the Internet of Things (IoT). The IoT allows for continuous, real-time data transactions between devices such as barcode scanners and mobile computers.

In many ways, data capture solutions are facilitating the big data phenomenon that then helps streamline operational processes. For example, FedEx’s SenseAware platform combines location solutions (GPS) with temperature readings and real-time notifications if a shipment has been opened or exposed to light. FedEx is able to analyze these data sets in order to rectify inefficiencies that would have been left unidentified had the data not been available. The IoT uses AIDC technology to provide continuous real-time data in all parts of the supply chain, facilitating optimization. When combined with big-data-driven platforms such as SenseAware, scanners and sensors can be used to assure visibility, traceability and quality control at all steps in the supply chain. These traits contribute to successful short-term and long-term business decisions.

There are undoubtedly challenges in managing big data, particularly with respect to AIDC technology. Data capture is not the same concept now as it was ten years ago. What started out as just barcode scanning has now evolved into capturing a variety of nontraditional data types. Solution providers have to work twice as much to live up to expectations as clients place frequent demands for multipurpose scanners and software that support a range of data capture functions, not limited to simple track-and-trace. This leads into the next challenge that participants in the supply chain face. Big data is only as useful as the way in which it is analyzed and presented; so, how does one integrate all of these vastly different types of data sets together in a meaningful way?

For end users, the issue (and the solution) is in the analytics. Companies such as FedEx are now hiring ‘data scientists.’ These professionals specialize in analyzing and presenting big data in a way that contributes to effective decision-making. Any firm seeking to use big data to its advantage will need to invest in a specified team of data scientists for this purpose.

The future of the AIDC market will depend on participants’ ability to address these prevalent issues head-on. As data volume and variety are continuously increasing, it is no longer enough for a scanner to read a barcode. Data capture solutions providers will need to innovate and make investments in solution development that goes beyond hardware in order to meet increasing demands of today’s connected, big-data-driven IoT world.

(By Kelly Brown, Research Assistant)


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