Critical Manufacturing Named Leader in 2021 Gartner Magic Quadrant for MES


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Critical Manufacturing has been named as a Leader by Gartner, Inc. in its 2021 Magic Quadrant for Manufacturing Execution Systems (MES). According to Gartner, “there has been a fundamental shift in the MES market, driven by evolving technologies that challenge the MES status quo and driven by vendors with the agility and talent to accelerate the adoption of those technologies.” Critical Manufacturing believes that its modern MES delivers on the new capabilities and technologies needed for manufacturers to gain rapid benefits from their smart manufacturing initiatives.

Francisco Almada Lobo, Critical Manufacturing CEO, said: “We are delighted to be chosen as one of the seven Leaders in the Magic Quadrant, and we feel our position also recognizes our advanced vision and roadmap for the future of MES. We further feel that the report recognizes our differentiators, such as our IoT data management capabilities, which combined with MES, allow manufacturers to harness the true value of their data. Our remarkable scoring in customer satisfaction further reflects the innovation, power and flexibility of our MES.” 

Companies were assessed on numerous criteria including ‘Completeness of Vision’ and ‘Ability to Execute’. Critical MES capabilities include Production Management, Quality Management, Data Management, Regulatory Compliance, Analytics, Production Equipment Integration Architecture, Enterprise Integration Architecture, User Experience, Deployment Option Variety and Ease of System Upgrade. Gartner noted that there had been a shift in interest in MES in 2020, with more concern about innovation at scale and so added a new criterion of ‘Enterprise’ to this year’s evaluations. MES is now very much considered as an enterprise solution that should be capable of implementation across multiple sites. 

Almada Lobo concluded, “We have understood how smart manufacturing impacted the more conservative MES market. It is no longer enough that MES covers a wide functional area and is reliable, modular, and designed for extensibility and configurability. It also needs the connectivity to handle the rapid pace and growth of data generated from IoT devices and equipment. It must provide the intelligence that is required to generate valuable new insights from this data, using machine learning and other advanced analytics and also provide a solution that can be deployed on premises, on cloud or a hybrid mode. It must further deliver a new paradigm of usability that includes mobile devices, AR or bots.”

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