A Micro-Gamble in Cincinnati
Microsoft, P&G teaming up for innovation center; expected to bring manufacturing jobs
Procter & Gamble and Microsoft Corp. announced a new multiyear collaboration Wednesday that will leverage the Microsoft Cloud to help create the future of digital manufacturing at P&G in its hometown of Cincinnati.
The two companies will "co-innovate to accelerate and expand P&G’s digital manufacturing platform and leverage the Industrial Internet of Things (IIoT)" with an aim to bring products to consumers faster, increase customer satisfaction and improve productivity to reduce costs.
“Together with Microsoft, P&G intends to make manufacturing smarter by enabling scalable predictive quality, predictive maintenance, controlled release, touchless operations and manufacturing sustainability optimization — which has not been done at this scale in the manufacturing space to date,” said P&G CIO Vittorio Cretella. “At P&G, data and technology are at the heart of our business strategy and are helping create superior consumer experiences. This first-of-its-kind co-innovation agreement will digitize and integrate data to increase quality, efficiency and sustainable use of resources to help deliver those superior experiences.”
Using Microsoft's Azure platform as the foundation, the new collaboration marks the first time that P&G can digitize and integrate data from more than 100 manufacturing sites around the world and enhance its AI, machine learning and edge computing services for real-time visibility. This will enable P&G employees to analyze production data and leverage artificial intelligence to immediately make decisions that drive improvement and exponential impact. "Accessing this level of data, at scale, is rare within the consumer goods industry," the companies said.
P&G also said it selected Microsoft as its preferred cloud provider to build the future of digital manufacturing based on a four-year history of successfully working together on data and AI. The new collaborative effort will reportedly:
Allow for better utilization of data, AI capabilities and digital twins technology.
Optimize manufacturing environmental sustainability efforts.
Increase workforce efficiency and productivity.