The value of digital supply chains is their ability to analyze massive amounts of real-time data very quickly with machine learning algorithms to understand behavior over time and produce actionable, intelligent insights.
Digital Supply Chains leverage demand inputs by:
By constantly analyzing these inputs, and more, with machine learning algorithms, they produce accurate and timely demand signals, which in turn inform inventory allocation decisions that reduce stock-outs and increase revenues.
According to “Innovation Driven Resilience” an annual industry report from the Material Handling Industry (MHI) trade organization and the survey of over 1,000 manufacturing and supply chain leaders from a range of industries done in collaboration with Deloitte:
Each one of us benefits from consumer behavior modeling every day, in ways we probably don’t think twice about anymore. Google, for example has mastered the art of watching, understanding and anticipating consumer behavior. The company has learned about our individual habits, tastes and preferences by watching what we do on the internet. It pre-populates address and credit card information on web forms, if we allow it. It anticipates and pre-populates Google searches after we’ve only typed a word or two, seemingly reading our minds. It proactively anticipates our destination when we get in the car at the end of the day to drive home and offers suggestions for optimal routing, given current traffic congestion. Google also serves up highly tailored ads.
Global manufacturers and retailers are applying these same principles to their businesses, leveraging digital supply chain solutions as the enabler. They are learning about individual buyer preferences, habits and behaviors from their digital signatures, left not only by their activity on the internet, but through the myriad physical devices that consumers use every day. And they are finding correlated events in the physical and digital worlds that either influence or precurse demand.
This, of course, is a dream come true for supply chain professionals. Forecast inaccuracy is often the bane of a supply chain professional’s existence. Anything that can help improve the accuracy of a demand forecast out into the future is more than welcome. But the real-time nature of today’s demand sensing can be a blessing and a curse to a company that hasn’t also evolved the supply side of their equation.
While having a more dynamic understanding of consumer behavior is a positive, it puts an added strain on the supply side of a company’s digital supply chain. By sensing strong consumer sentiment for a brand in the southeast, for example, supply chain managers can take advantage of the demand spike by positioning more inventory in that part of the country. But they have to be able to re-allocate inventory to that region quickly, which means the supply side of the supply chain has to be nimbler.
As the digital supply chain progresses we will see them getting faster as stated by Mckinsey & Company, “in the future, we will even see “predictive shipping,” for which Amazon holds a patent: Products are shipped before the customer places an order. The customer order is later matched with a shipment that is already in the logistics network, and the shipment is rerouted to the exact customer destination. They will be more granular, with customers looking for more and more individualization in the products they buy, companies must manage demand at a much more granular level, through techniques such as micro-segmentation, mass customization, and more-sophisticated scheduling practices”. Those are just two examples of ways the digital supply chain will focus on the customer but there are many more.
A company must differentiate themselves to their customers in the market in all that they do. It’s essential to have an end-to-end understanding of both the demand side behavior and supply side behavior.