Major Industrial and Automotive Manufacturers Are Far Behind the Industrial IoT Innovation Curve

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Major Industrial and Automotive Manufacturers Are Far Behind the Industrial IoT Innovation Curve

New Survey from Software AG Reveals that Manufacturers Are Not Scaling IIoT Across the Enterprise Due to Failure to Invest in Predictive Analytics and Innovative Integration Strategies.

Software AG today announced an original survey of over 125 North American manufacturers primarily in the heavy industry and automotive sectors that revealed they are unable to scale their Industrial Internet of Things (IIoT) investments across their enterprises, and therefore are losing millions of dollars in potential profits while falling behind competitors that have invested in enabling technologies that support IIoT across the enterprise.

The survey also revealed that the vast majority of manufacturers queried report that their IIoT investments are limited – locked in one small department or sector of their company – preventing these organizations from sharing the power of IIoT across their enterprises. This has caused these manufacturers to lose millions of dollars in potential profits as they fall behind more forward-thinking competitors that have invested in predictive analytics and innovative integration strategies that scale IIoT across the enterprise.

Other key findings include:

  • 80% of all survey respondents agree that processes around IIoT platforms need to be optimized or they will face a competitive disadvantage but very few are doing this.
  • IT-OT (Information Technology and Operations Technology) integration is considered one of the most difficult tasks – with 57% of automotive manufacturers stating that this has prevented them from realizing full ROI from their IIoT investments.
  • 84% of automotive and heavy industry manufacturers agree that the most important area of IIoT is “monetization of product-as-a-service-revenue.” However, optimizing production is still important with 58% of heavy industry and 50% of automotive manufacturers agreeing with that statement.
  • Curiously, defining threshold-based rules is considered almost as difficult as leveraging predictive analytics to scale IIoT. More than 60% of respondents stated that defining threshold-based rules was as difficult as integrating IT systems and IoT sensors into existing control systems.

Sean T. Riley, Global Industry Director, Manufacturing and Transportation, Software AG, said:

“Manufacturers place a high value on IIoT, but they are encountering serious difficulties in unlocking the complete intended value to unleash their innovation across their organizations.”

“Fortunately, there is a way for them to quickly and easily resolve this problem. By investing in the right IT-OT integration strategy that leverages sensors, predictive analytics, machine learning, control applications and product quality control, manufacturers can fix this problem in less than 6-12 months while realizing other key benefits, namely extended equipment lifetime, reduced equipment maintenance costs and accessing more accurate data for production-quality improvements.”

Riley outlined five best practices for manufacturers to follow when looking to scale their IIoT investments across their enterprises and realize immediate profits and competitive advantage. Those best practices are:

    1. Ensure clear collaboration between IT and the business by leveraging a step by step approach that starts focused and has clear near-term and long-term objectives to scale.
    2. Create a transparent roll out process and don’t let other plants or departments move ahead outside of it.
    3. Give IT the ability to connect at speed with a digital production platform that is proven to be successful.
    4. Leverage a GUI-driven, consistent platform to enable an ecosystem of IT associates, business users and partners around the platform.
    5. Enable the plant or field service workers to work autonomously without continual support from IT through GUI-driven analytics, centralized management and easy, batch device connectivity and management.

Riley also stated that it is critically important for manufacturers to select the best possible IIoT integration platform supported by key enabling technologies like streaming analytics, machine learning, predictive analytics and a larger ecosystem. Software AG’s Cumulocity IoT platform recently received the highest use case scores from Gartner Group in the brand new “Critical Capabilities for Industrial IoT Platforms” report which included Monitoring Use Case, Predictive Analytics for Equipment Use and Connected Industrial Assets Use Case for its IoT.

Cumulocity IoT is Software AG’s cloud-first and fully extensible IoT platform that lets customers start quickly and scale rapidly. Being device and protocol agnostic allows to connect, manage and control any “thing” over any network. Cumulocity IoT is an industry leading IoT solution, which is open and independent, letting customers connect to millions of devices without being locked into one single vendor.

“Our platform is already helping customers such as Gardner Denver, Nordex and Certuss find the right solution for their IIoT requirements,” said Riley. “The recognition and acceptance of our Cumulocity platform underlines our commitment to enabling customers to quickly and easily bring their ambitious IIoT visions to life. However, the ChangeMaker network has also been created to ensure the talent needs shortage can be managed and projects will be successful in the near and long term.”

The Software AG IIoT Implementation survey was completed in Q2 2019 by Software AG and an independent third-party research house. The survey queried nearly 200 respondents at large manufacturing companies across automotive, heavy industry, high-technology, electronics, pharmaceutical and medical device industries. The respondents were primarily senior executives leading manufacturing or information technology with the breakdown of 50% managers, 38% directors and 13% vice presidents or higher.
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