Industry 4.0 Data Challenges for Manufacturers

Industry 4.0 brings seemingly endless opportunities, as well as seemingly limitless options, for technology investments. Here are just some of the many challenges companies face when looking to tackle Industry 4.0.

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Industry 4.0 brings seemingly endless opportunities, as well as seemingly limitless options, for technology investments. Here are just some of the many challenges companies face when looking to tackle Industry 4.0:

  • Adopting new technology
  • Reorganizing processes to leverage better outcomes
  • Considering new business models/strategies
  • Helping others in the company understand where action is needed
  • Connecting departments
  • Recruiting, developing, and maintaining new talent

What should manufacturers be keeping in mind when addressing these challenges?

Rethink Your Business

According to McKinsey, “Industry 4.0 disrupts the value chain and requires companies to rethink the way they do business. They need to drive the digital transformation of their business to succeed in the new environment.”

McKinsey cites five pillars that are critical for this transformation:

  • Companies need to manage and treat data as one of its most valuable business assets.
  • Companies need to build digital capabilities.
  • Companies need to initiate and enable collaboration.
  • Companies need to manage cybersecurity.

The focus on data and data quality may be the most important one.

“Anyone designing systems should not underestimate the complexity of getting the quality right, and the need to not just have good data, but to provide that data with its full provenance (where did it come from) and security (who can see it or use it),” says MarkLogic Chief Strategy Officer Matt Turner. “The data quality aspect of the job is likely the largest effort and is often overlooked.”

Turner also says another consideration is to make the data reusable. Leading enterprises like AIRBUS and Autoliv pioneered the concept of a data hub as a place to integrate data, maintain that provenance and deliver it with security to multiple downstream systems. 

“Taking this approach to managing data means that any investment in fixing bad data can be used for multiple, additional purposes. For instance, instead of just addressing data quality for one digital twin system, a data hub can enable that verified data to be shared with other processes,” says Turner. “This reusability is key to using data to improve products, increase efficiency and better operate in increasingly complex environments. By building in good data management from the start, organizations can use their data to deliver long term value.”

According to McKinsey, “to leverage these multiple opportunities, companies need to embark on a digital transformation journey: a continuous, long-term effort is needed to successfully navigate the changing industrial environment of Industry 4.0.” If companies can bring these many different activities together with a focus on the data, they will be in position to take advantage of the many opportunities of Industry 4.0.

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