Industry 4.0 requires whole-of-business approach to be successful

It's important to take more than just operational data and improvements into account when digitalizing industrial operations.

Top 5 things to know about Industry 4.0
30:16:40

Even though management guru Peter Drucker, who is widely credited with saying, "You can't manage what you can't measure," never actually said those words, that sentiment holds true regardless. 

As industrial operators continue to digitalize their operations by embracing digital transformation technologies like the internet of things (IoT) and cloud, putting this statement into action is becoming more important than ever, according to a new white paper from the Industrial Internet Consortium (IIC), Enabling Digital Transformation with IoT Performance and Properties Measurement (PDF). 

"Digital transformation leverages connected things to transform processes and operations to produce better outcomes and enables more efficiency, new business, operational opportunities, and flexibility," the report said. "It is a process, an endeavor for more efficiency, new business, operational opportunities and flexibility. The transformation process requires a prompt assessment of what works and what does not. We are looking beyond the operational aspects. We look at performance and the readiness of a solution."

SEE: Digital transformation: An IT pro's guide (TechRepublic download)

Even though the IoT revolution actually started in industrial settings in the 1960s and '70s, operators today still limit measurements to what is easy to measure. They also tend to apply the analytics and data created by those measurements too narrowly. As operational technologies (OT) and IT continue to blend (with operational analytics, for example, taking place on cloud platforms and the output being subsequently shared with ERP and supply chain management systems) using all operational data and analytics to uncover if technology-led process improvements are actually achieving the objectives for which they were deployed is more important than ever.

"What we saw in our test bed activities is all these parties need to be brought onto the same page in order to declare success," said said Jacques Durand, co-chair of IIC's Digital Transformation working group and lead author of the report. "Saying that you just want to reduce a product error rate … is one thing but you have to be precise: What product? When do you measure? There are many aspects of measuring the condition of what you are measuring."

Because of the tight integration taking place between OT, IT, and business workflows, today's process improvement goals go well beyond the factory floor. Stakeholders from across the organization have a vested interest in the success of these efforts as they too work to digitalize there lines of business, integrate processes, and optimize business outcomes using data. 

"As soon as you define more precisely what downtime means, [stakeholders] all have very different definitions of what downtime is," said Durand. "Metrics are very useful to bring all the stakeholders on the same page. There are things that are easy to measure like productivity and speed in the short-term but, for a solution to work on the long-term, and to be solid and robust, there are other things that are harder to measure. If you are on the technology side of these deployments, you have no grasp of these factors."

These can include things like, acceptance of new technology on the factory floor, 
disruption caused to other parts of the business, or process rigidity introduced by the new technology, he said.

To be successful, organizations need to focus on two categories of metrics:

  • Business model validation and improvement metrics, which focus on monitoring the financial and strategic key performance indicators (KPIs), and;

  • Solution validation and improvement, which focuses on monitoring and improving the operational side of the solution from the perspective of functionality, non-functional service level agreements (SLAs) and service level objectives (SLOs), and other system characteristics, including trustworthiness properties.

"Metrics are useful for communicating expectations as well as managing a system, both when determining whether a system is ready to deploy as well during operation," said Frederick Hirsch, one of the paper's authors and co-chair of IIC's Trustworthiness task group. "Important for functional management, they may also be considered for insight into trustworthiness properties such as security and safety."

Beyond operational improvements, the paper lays out seven major business value areas that any industrial digital transformation effort needs to account for:

  1. Process efficiency: Improved agility, speed and reduction in time to market, business process optimization, reduced operational costs, increases in productivity and labor efficiency, enhanced intra-organization collaboration and better integration with greater operational environment and systems.
  2. User experience: Improved customer satisfaction, added value for users, better service and customization. 
  3. Product quality: Reduction of errors and defects, better tracking, measurement and control of quality factors, better consistency in production quality and delivery.
  4. Asset management: Better tracking, monitoring and control of physical assets such as machines, tools and other resources or equipment, improved asset utilization, processing, maintenance efficiency (preventive, predictive) and cost efficiency.
  5. Business innovation: New revenue streams with innovative business models and enhancement of existing models. Contributing factors include new services or products, product enhancement, combinations of product and service, opportunities to create services, and faster research, development and engineering processes.
  6. Governance: Facilitating strategic decision-making, assessing and assuring compliance to policies and regulations. This also includes informing management strategy to balance dimensions such as product quality, cost, delivery timeliness and environment or regulation impact. 
  7. Risk management: Identifying, quantifying and managing the risks in business and operations, enabling risk mitigation, monitoring and improving trustworthiness (security, safety, reliability, resilience, privacy) with an understanding of their interdependencies and enabling assurance.

"Any DX [digital transformation] solution is expected to provide value in one or more of these areas," the report said. "Cost reduction and revenue increase are not listed as value areas because they are a by-product of any improvement in the value areas above. The value areas represent ways to achieve these goals."

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