about the design and use of agility and responsiveness, Payne says. That leaves their supply chains vulnerable to losing value when exposed to uncertainty. Several vendors are moving into the market with probabilistic forecasting products, Payne adds. Advanced Analytics The category of advanced analytics includes tools that use data science to predict patterns and estimate the likelihood of future events, among other functions, then leverage this insight to address complex business problems. For example, machine learning capabilities, as part of advanced predictive analytics, can detect previously unrecognizable patterns in data, driving greater certainty in determining how demand will materialize. Digital Twins, Artificial Intelligence, and Internet of Things A digital twin can represent one or more supply chain processes designed to help organizations simulate real situations and their outcomes and then make informed decisions. When combined with Internet of Things (IoT) technology, a digital twin can help employees work in ways that enhance communication, operations, and processes, and boost efficiency, says Rajinder Bhandal, Ph.D., a management
well as more sophisticated solutions that support the use of data and information to improve decision making. Common investments include the following: Supply Chain Platforms Platforms can play a key role in supply chain operations. One way companies can increase resilience is by expanding their supply base to multiple vendors, often in different regions of the globe. As they do, a technology platform can provide process controls and a single source of data for their transactions. These attributes enable process consistency and consequent predictability that bring stability as vendors are added. This, in turn, facilitates supply chain diversification and resilience, says Bryn Heimbeck, president and co-founder of Trade Tech, which offers technology that addresses global trade complexities. Probabilistic Planning Working with probabilities—expressions of uncertainty—is a critical tool for shoring up supply chain resilience. “The more you work with probability, the more knowledge you can gain about how uncertainty impacts your supply chain,” Payne says. With this knowledge, supply chain leaders are better prepared to take advantage of uncertainty.
together can facilitate better quality data and data sharing. The data can be mapped onto multiple supply chain processes where workers interact to provide visibility and improve decision-making. Supply chain visibility tools like this chat bot from FourKites provide shippers with access to critical, end-to-end supply chain data they can use to make faster decisions and stay ahead of disruptions.
Conversely, static planning assumes no uncertainty—a largely unrealistic assumption. With no knowledge of the impact of uncertainty on their supply chain, organizational leaders are at risk for making poor decisions Linking advanced AI tools with digital twins can also help organizations plan for and adapt to supply chain disruptions. To help in developing robust scenarios and recommendations, the tools should allow for modeling multiple “what-if” scenarios based on changes within the supply chain, and should be able to ingest diverse sets of data. Impact of AI on Supply Chain Management 43% 29% 14% of all working hours lecturer at Leeds University Business School, and a member of the Digital Twin Consortium Academia and Research Working Group. For instance, the two solutions
of working hours across supply chains could be significantly augmented by generative AI.
of working hours across supply chains could be automated by generative AI.
across end-to-end supply chain activities could be impacted by generative AI.
Source: Accenture research report
64 Inbound Logistics • April 2024
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