Simon Hardy’s presentation focused on digitalizing supply chain management. He described the chemical industry’s early steps into digital technology to manage the flow of products.
These early efforts focused on streamlining individual bilateral supply chain relationships, connecting the supplier to shippers, importers, warehouses to the consumer, but not leveraging this data to connect to the full ecosystem.
More recently, these data systems are being leveraged to provide wider access to third-party products, for example. “Supply chain operating networks [have] started to morph into digital supply networks and are starting to provide other elements as well,” Hardy said.
More data is being leveraged to smooth the passage of products, he added. Identifying shipping bottlenecks and re-directing orders to by-pass those problems is one example.
These systems are now benefiting from being “always on”, Hardy said. “Constantly, accessible, always on, is a critical part of how chemical companies are looking at their customer base.”
But this is still a digital model: how does the industry move to digitized?
Historically, data has tended to be backward-looking, recording previous events and developments. The challenge, he said, is to start looking forward, moving from “descriptive” to “prescriptive”.
This requires systems and people to plan for small, unseen risks and events, the “day-to-day” risks rather than the “big picture” challenges.
This, Hardy said, requires “emotional intelligence” to dampen the force of these small shocks, and to respond accordingly. Simply following analytics will not work. Human intervention and judgement is needed to smooth the potential shock of a missed delivery and to deliver a solution.
In a more agile and fast-responding world, clients will be demanding that their mission critical raw material supplies are guaranteed, nearby, and they will want to know the status of that supply, Hardy explained.
Suppliers, on the other hand, are also going to want to be more rightly integrated into their clients’ operations. They will want to have insight into production forecasts, for example, which will help them reduce supply chain friction.
As an example, Hardy suggested that a more prescriptive approach to Rhine barge deliveries would take into account seasonal water level changes, and plan ahead for alternative forms of delivery. By tapping into relevant weather or other data over longer periods, prescriptive models of likely river conditions can be built up and help supply chain managers to smooth over any interruptions.
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