The journey towards autonomous supply chains

The ever-better quality and availability of internal and external data is enabling companies to predict their future with increasing accuracy. In the next phase, those predictions will be used to support – and perhaps even automate – crucial decision-making processes. Are autonomous supply chains in sight?

Analytics is not new; statistics and operations research are two forms of analytics that have been used for decades as part of activities such as planning and simulations. According to Bram Desmet, the growing focus on analytics is all down to the increasing volume of data and the speed with which it is available. He refers to the analytics trendsetters using the acronym ‘FANG’: Facebook, Amazon, Netflix and Google. “Those companies gather so much data that it no longer even fits into a single database, so they’ve had to build huge data centres”, says the adjunct professor of operations & supply chain management who lectures in subjects including statistics and decision sciences at the Vlerick Business School.

The importance placed on data by this new generation of tech companies has resulted in a reevaluation of all the existing analytics techniques. “Whole new techniques for generating insights from all the data have also emerged – think of the analytics that enable Amazon and Netflix to recommend other products that customers might find interesting”, says Desmet.

Another reason often given is the rapid growth in the availability of computational power thanks to cloud-based solutions. Companies can now make use of extra computing power as and when they need it, without having to invest in servers of their own. “But the real driver of this trend is the sheer amount of data and the speed with which it is available. And it’s no longer just numerical data based on figures from internal applications; now, it can also be things like unstructured data from external sources such as social media”, comments Desmet.

Network optimization

In Europe, Heineken seized the opportunity presented by the availability of high-quality data to set to work with prescriptive analytics. “On this continent, data is often of such high quality that we hardly need to spend any time on gathering and validating it any more”, says Wilko Sierksma, Manager Network Design & Global S&OP at Heineken. “That’s all down to the automation level and maturity in Europe, where many logistics processes are already automated. It’s a different story in a country such as Ethiopia, where it could actually be cheaper to check data manually three times rather than automate the process.” … … …

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This article was first published in Supply Chain Movement 30 | Q3 – 2018