Big Data has been around for decades in which lie gems that could transform logistics efficiency but those gems cannot be mined while the data remains largely unstructured. This was the main message from John O'Brien, Vice President for Transport and Logistics, at DataArt* during a presentation hosted by DP World at London Gateway, its new container port, and organised by the Logistics Leaders Network#.
Vast amounts of data are generated by people talking to people (Facebook), machines talking to machines (EDI), and the internet of things, involving sensors collecting and sharing data, but ordinary data processing, involving traditional business intelligence using databases, does not work, says Mr O'Brien. But if the information can be structured efficaciously then those who run global supply chains can seriously cut their exposure to supply risks and even improve predicted demand.
By using big data in this way one fuel retailer, for example, employed sensors at its network of service stations and convenience stores so that it would know in almost real time what its fuel/product mix and consumption rates were in each of its geographical territories. Such incoming point-of-sale data also tells it in which mixes of products besides fuel work best by geographical area so it can tailor offers accordingly. The result is faster time to market with offers and better revenue positioning and agility because offers can be instantaneously changed to respond to customer demand shifts.
Market response time is key
This emphasis on time-to-market can be a game-changer for many businesses because it means that their supply chains are their competitive advantage. Zara, the world's leading clothing retailer, built its empire on the unconventional premise that speed and responsiveness are more important than product cost and so it is renowned for its ability to deliver new clothes to stores quickly and in small batches. Another key, successful plus for them is that Zara controls more of its manufacturing than do most retailers and so is less of a hostage to fortune when natural, political and social risks erupt to disrupt far-flung supply sources.
Perhaps mindful of the Japanese tsunami in 2011, one large manufacturer has used big data to minimise exposure to risk in its global supply chain by overlaying its geographical supply chain locations with weather statistics for tornadoes, hurricanes and earthquakes. It also then calculates the probabilities of natural disasters occurring through a predictive analytics program. The result is that the company now has a way to orchestrate its suppliers so that it has back-up plans if a key supplier gets hit by a disaster and the incident takes down production.
In a JIT-dominated supply chain, having a robust, disaster recovery plan is indispensable but global logistics is still exposed by the concentration of too much supply of one key product in one factory. The Japanese tsunami exposed the folly of this because Japan is a choke point for about 95 products key to the auto industry and consumer electronics. When that disaster struck it disrupted just one factory producing 40% of the world's microcontrollers used in cars, leading to idled car plants around the world and multi-billion pound losses in production and profits. Now might be a good time to hold stocks of such small components in higher amounts at point of final assembly, given that the extra costs of holding such inventory would only be a small fraction of, say, a car's cost, if the supplier controls a worrying percentage of world output in a disaster-prone region.
It would be difficult to single out any business discipline more complex and demanding than logistics. It is not simply a job trying to arrange a supply chain most effectively, or trying to manage production flows in factories and warehouses efficiently. It involves grappling with socio-geopolitical issues that could disrupt global supply chains; in short dealing with numerous what-if scenarios. It could even involve the input of bad corporate governance on consumer sentiment. Many leading global players, for example, use Far Eastern labour by subcontractors where working conditions are often atrocious. One huge Chinese-based supplier to the mobile phone and computer industries became so concerned over staff suicides relating to working conditions and pay that it reportedly asked new employees to sign contracts promising not to commit hara-kiri. But poor corporate governance, like use of child labour and morally repugnant, though legal, tax avoidance schemes has led to effective consumer boycotts. It is every boardroom's worst nightmare and there is no reason why we should not see more of these problems and so logisticians should take note.