Artificial Intelligence Wades Through Murky MRO Inventory Data To Drive Down Costs with Better Business Decisions
Webinar from Verusen and Accenture Details How AI and Predictive Analytics Clarify Data Across Multiple Systems to Right-Size Plant Inventories
The ability of artificial intelligence (AI) to improve visibility of ERP inventory data, as well as the implementation timeline for using AI on a daily basis, were among the top interests of participants during a recent webinar, “Taking Stock of AI Technology for Inventory Management.”
The webinar featured expert advice from CEO Paul Noble of Verusen, an innovator in materials inventory and data management technology, and Erik Green, practice lead, Materials & Equipment, at Accenture, a leading global professional services company.
“Reducing MRO inventory is one way for asset-intensive manufacturing industries to quickly drive value, but siloed data in ERP and other systems result in redundant parts—and understocking—that infrequent manual cleansing can’t address to support dynamic business decisions,” said Noble. “It’s important for organizations to know that AI is a very real option today that can wade through data from multiple systems to present real-time suggestions for in-house teams—and then learn from those decisions.”
The webinar demonstrated how AI replaces disconnected data silos with a digitized network footprint of all goods, services and logistics throughout the supply chain so inventory decisions are visible to teams across an organization. It covered how AI’s machine-learning capability continually updates and interprets market trends to drive accurate predictive inventory analyses for indirect MRO, direct goods and even finished products, instead of relying on subjective decisions.
These were the top three areas of interest in regard to deploying AI technology within the supply chain that were expressed by webinar participants, representing a variety of different industry segments:
- How does AI interface with my ERP system for better inventory visibility? An AI platform structures and understands inventory data, often with inconsistent naming conventions, in materials catalogs and tables across multiple ERP systems. The platform displays the most pressing inventory needs per plant and offers suggestions for planners, data managers and plant personnel to right-size inventories, while doing the heavy lifting that eliminates manual efforts.
- How quickly can my company deploy AI technology for use on a daily basis? A customized AI system could take from 12 to 24 months to implement, but a productized AI platform can be quickly modified for an environment and provide results in as little as 90 days.
- How does AI for materials inventory management benefit sales? By having optimized inventory at each plant, production uptime is maximized so that customers remain satisfied with timely deliveries and are more likely to place future orders.
“Organizations today want to give customers an Amazon-like experience while driving out costs, and while Accenture surveys show 90 percent of leaders believe innovation significantly contributes to high performance, only 20 percent feel they can get there with current innovation engines,” said Green. “AI for applications like inventory management is one way for organizations to embrace innovation at the right pace and in the right place to meet the highest of financial and customer service goals.”
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