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Automation of individual tasks involves steps on the path to fuller autonomy. We’re already seeing some fully autonomous planning and limited forms of autonomous execution. The types of decisions being automated are diverse, including design (generative design and preference prediction), sourcing and procurement (cognitive sourcing and procurement automation), automated “touchless” demand planning and inventory optimization, merchandizing and category management (agile category resets, promotion planning, automated planogram optimization and compliance checking), logistics (precise ETA, disruption prediction, and corrective actions), warehousing, and service (predictive maintenance driving automated parts ordering and service scheduling).
Beyond individual functions, solution providers are striving toward more end-to-end autonomous planning and execution, ultimately including multi-tier capabilities. It will take a while to fully realize that kind of ambitious vision.
Meanwhile, the predecessor of autonomous supply chain execution can be found in control towers, which provide supply chain-wide visibility into the status of orders and shipments, and alerts in the event of delays. Solution providers have been extending control-tower capabilities in several dimensions, representing steps toward autonomy:
Data quality and a digital supply chain are prerequisites for companies moving to autonomous supply-chain capabilities. It’s a lot more difficult to make paper-based systems such as e-mail and spreadsheets autonomous. It’s easier when transactions are digitized and reliably captured by systems, with consistent data and syntax. Lack of sufficient data quality and completeness is an inhibitor to autonomy for most companies. Investments in digitization and data quality will pay off in multiple ways, well before full autonomy is reached.
Bill McBeath is Chief Research Officer with ChainLink Research.
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