November 7, 2025
November 7, 2025
Manufacturing leaders are familiar with physical waste; scrap, rework, and inefficiencies in production.
But digital waste is the hidden inefficiency thatโs just as costly.
It includes:
๐๐ง๐ฎ๐ฌ๐๐ ๐๐๐ญ๐: Factories generate massive amounts of data, but much of it is never analyzed or leveraged for decision-making.
๐๐ง๐๐๐๐ข๐๐ข๐๐ง๐ญ ๐๐๐ญ๐ ๐๐๐ง๐๐ฅ๐ข๐ง๐ : Engineers waste time manually entering, cleaning, or searching for information that should be automated.
๐๐ข๐ฅ๐จ๐๐ ๐๐ง๐๐จ๐ซ๐ฆ๐๐ญ๐ข๐จ๐ง: Key insights are trapped in different departments or legacy systems, preventing AI-driven optimization.
Digital waste silently drains resources, increasing operational costs while blocking AI from delivering its full potential.
Once manufacturers recognize digital waste, the next step is identifying where AI can generate the biggest returns.
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Kudzai Manditereza is an industrial data and AI educator and strategist. He specializes in Industrial AI, IIoT, Unified Namespace, Digital Twins, and Industrial DataOps, helping manufacturing leaders implement and scale Smart Manufacturing initiatives.
Kudzai shares this thinking through Industry40.tv, his independent media and education platform; the AI in Manufacturing podcast; and the Smart Factory Playbook newsletter, where he shares practical guidance on building the data backbone that makes industrial AI work in real-world manufacturing environments. Recognized as a Top 15 Industry 4.0 influencer, he currently serves as Senior Industry Solutions Advocate at HiveMQ.