Sean Riley, Global Director of Manufacturing and Transportation at Software AG, discussed Industrial IoT (IIoT) implementation in industry with me a couple of weeks ago. Now, a survey sponsored by Software AG has been released revealing that manufacturers are not scaling IIoT across the enterprise due to failure to invest in predictive analytics and innovative integration strategies.

The shocking thing to me about the survey is that it mirrors survey results over the past three or four years. Executives and managers recognize a problem further even acknowledging that this is something that could cost them competitively against the market even putting them out of business. Yet, they cannot figure out how to do it right. They whine about how tough it is.

Sounds to me like a new crop of leadership is needed.

There are good practices taught some 40 years ago when I took a deep dive while implementing my first IT project. Things like understanding the system first. Bringing all the departments in on the plans, work to be done, and benefits we all would get. Some recommendations from Software AG sound that familiar—breaking silos, bringing IT and OT organizations closer together (a management problem, not a technical one), transparency in the project roll out.

The survey of over 125 North American manufacturers primarily in the heavy industry and automotive sectors revealed inability to scale IIoT investments across their enterprises results in losing millions of dollars in potential profits.

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.

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 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.

“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,” said Riley. “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.

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.

Software AG product

The press release contained some information about the company’s IoT platform—Cumulocity.

Being device and protocol agnostic allows it to connect, manage, and control any “thing” over any network. Cumulocity IoT is open and independent, letting customers connect to millions of devices without being locked into one single vendor.

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