A technology expert has shown how big data analytics has revolutionised the management of today’s mind-bogglingly complex global supply networks.
Writing in Supply Chain Digital, data analytics expert Hugh Simpson notes that before the advent of globalised commerce, supply chains were local or domestic.
Today, thanks to digital, internet-enabled technologies that have facilitated globalised trade, they have become so vast and intricate that they exceed human computational powers.
Simpson writes: “In the late 90s and early 2000s, globalisation was a blessing for prices but a curse for supply chains.”
However, advances in big data analytics are now beginning to enable procurement professionals working in supply relationship management, especially to get a firm grip on these colossal worldwide supply networks.
Digital technologies have helped procurement teams manage a range of core functions that globalisation has rendered immensely complex, from company cost reduction to category management to strategic sourcing.
However, big data tech is now being applied to supply chain analysis, enabling retailers, manufacturers, and distributors to optimise the ways that they get products to consumers, informed by accurate insights into precisely how, when and where people make their purchases.
Geoanalytics has accelerated the pace of this process, facilitating the speedy movement of products through the supply network, not least by allowing rapid reworking of distribution routes when potentially disruptive contingencies strike.
The technology has resulted in a massive 425% improvement in order-to-delivery intervals and a huge efficiency gain of 260%.
With big data analytics constantly crunching data drawn from supply routes and deliveries (both successful and problematic), supply chain managers can now identify potential problems before they materialise in reality, proactively circumventing prospective glitches in the distribution network.
Global supply chains have become a good deal more flexible as a result, enabling routes to be modified to avoid problems after the delivery path has been embarked upon.
The technology is also helping suppliers to anticipate surges in demand arising from previous orders and market trends. What’s not to like?