Finding Big Data in the Supply Chain
Big data. You may not be familiar with the term, but if you’re a supply chain manager, there’s a good chance you’re dealing with a Big Data problem, experts say.
Big data is what technologists call data that falls outside the bounds of transactional databases. It’s generally described by the “three Vs” of volume, velocity and variety.
In a recent whitepaper, “Big Data: Go Big or Go Home?” founder and CEO Supply Chain Insights Lora Cecere explained where you’ll find the three Vs in supply chains:
Volume: Large amounts of data. With data doubling every two years, even midsized organizations are dealing with “big data” volumes. A single ERP system can hold what amounts to a “Big Data” volume of data: Cecere spoke with one company whose ERP held five terabytes of data.
Velocity: In supply chains and on manufacturing floors, a growing army of sensors rapidly pump out data in the form of RFID, GPS location, temperature and QR codes.
Variety: What you typically think of as data is actually one type of data: Structured data, meaning it will fit into a relational database. But there’s a world of unstructured data produced in supply chains, too, including customer service reports, channel information, warranties, video, voice, mapping and digital images.
Big data technology will allow supply chain management to capture, process and better analyze all this data in new ways. Already, some supply chains are starting to experiment with Big Data initiatives, as Cecere discusses in the whitepaper.
It’s still too soon to know for sure how Big Data technologies will impact supply chains, but one thing’s for sure: Supply chain managers will need a new level of expertise when it comes to data, Paul Dennies, program director for high-tech manufacturing with Teradata, recently told SupplyChainBrain.com.
Here are some steps you can take to prepare the supply chain for Big Data:
- Synchronize your data, either through a single platform that can handle large volumes or through the integration of multiple systems, recommends Dennies. That said, even with a single platform, you’ll probably need back-end integration middleware to pull in data from legacy systems.
- Focus on traceability — you should be able to monitor the movement of parts and product from the individual component level to the customer and field-services teams, according to Dennies.
- Focus on data as a core competency, recommends Cecere. Many companies do this through an Integration Competency Center or an information management team. Generally, these disciplines are overseen by the CIO, but often individual business units will launch their own data projects without consulting with IT, leading to integration problems down the road. Don’t be that business unit.