Real-Time, Edge and Unbounded Supply Chains


Rather than focusing on the past for insights, organizations are increasingly trying to anticipate events with analytics and real-time data.

Accenture recently released an analysis of what businesses need to succeed in the post-pandemic future ahead, and identified real-time enterprise capabilities and edge computing as “signals” factors that will deliver success.

More than three-fourths of companies in Accenture’s latest survey report, 77%, increased use of both internal and external real-time data over the last 12 months. “Rather than focusing on the past for insights, organizations are increasingly looking forward. Rapid shifts in operating environments and human behavior mean that the historical correlations some analytical models rely on have been challenged. To find new patterns in data and better anticipate future decisions, new data sets—including real-time data from across the value chain — are being processed by new analytic approaches based on artificial intelligence.”

Accenture calls this enhanced approach to decision-making “learning from the future.” But there’s still work to be done – only 31% of the executives in our survey said they are completely confident in their ability to foresee and respond to, behavioral changes that affect demand. “Companies are not being held back by technology,” the Accenture authors point out. “Improved access to diverse sources of granular data and advances in modeling techniques mean that the right predictive tools are increasingly available. Instead, organizations are being held back by mindset, cultural, and organizational constraints—and their approaches to decision-making.”

Edge computing is also a prominent piece of the future unfolding. More than eight in 10 executives in the Accenture survey, 82%, said that “operating more like a broad federation of enterprises to respond to increasingly fragmented business environments will be important to their organization’s success.” Edge organizations leverage the principles of edge computing, a decentralized form of computation and data storage that speeds up processing by moving intelligence closer to the point of use. Several factors have aligned to make edge a growing reality, including “vast improvements in technologies have enabled greater connectivity and securely managed information flows, helping organizations overcome the constraints of distance. The pandemic—which triggered the biggest experiment in remote working at scale—has shown that it is indeed possible to collaborate well at a distance.”

The rise of real-time data, coupled with edge capabilities, also is making “unbounded supply chains” possible, which involves decoupling fulfillment from a distance, and fulfilling more orders from a smaller footprint and with less waste, Accenture reports. “Fulfilling more orders traditionally requires covering more miles, but new technologies – and the business models they enable – can minimize the impact of distance and borders on business. Route-optimization algorithms are helping reduce mileage and improve on-time delivery rates. In logistics, quantum routing uses cloud-based, quantum computing to calculate the fastest route for all vehicles, taking into account millions of real-time data points about traffic congestion.”

Here are some of the Accenture team’s recommendations to act on these emerging signals:

Plan for a broader range of future possibilities: “Organizations can take a clean-sheet approach to dynamic planning, drawing on both inductive AI-driven insights and creative thinking about what the future may hold,” the Accenture authors say. “Instead of asking, for example, ‘What would we do if our servers went down?’ firms might ask, ‘What would we do if there were no servers at all?'”

Take a wide-angle approach to data use: “Because no one knows what particular pieces of data will ultimately turn out to be important for predicting different events, there is no such thing as valueless data. Organizations that take a wide-angle approach to data use, tracking hundreds of variables or more, can better inform their algorithms.”

Go flat to empower the edge: “Edge organizations are structured in ways that make them flatter and faster. They shift away from conventional hierarchies toward networked structures built around empowered, multidisciplinary teams that are centered on customer outcomes.”

Rethink supply networks: “Doing more with less requires thinking critically about the role of each node in the fulfillment network. For example, retailers have tended to carry less inventory in their distribution centers by pushing products to stores, resulting in unsold inventory. Inventory could be more effectively managed upstream, pooled in port warehouses, and pushed out on demand. Alternatively, stores could be used as fulfillment nodes themselves.”


About Joe McKendrick

Joe McKendrick is RTInsights Industry Editor and industry analyst focusing on artificial intelligence, digital, cloud and Big Data topics. His work also appears in Forbes an Harvard Business Review. Over the last three years, he served as co-chair for the AI Summit in New York, as well as on the organizing committee for IEEE's International Conferences on Edge Computing. (full bio). Follow him on Twitter @joemckendrick.

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