I came across the intriguing paper – Myths and facts of Industry 4.0 by Guilherme LuzTortorella, Tarcisio A.Saurin, PeterHines, JijuAntony, and DanielSamson. This paper and its findings provoked me to think about the operations digital twin as a catalyst of the Industry 4.0 transition. Distinguishing myths from facts could help companies mitigate specific risks and avoid short-falling implementation of the Industry 4.0 capabilities. Before diving into the nitty-gritty of the paper, let’s unfold the terms of the fourth industrial revolution and digital twin.
The fourth industrial revolution manifests the shift in the company operating models and society from a broader perspective due to technological advancements like artificial intelligence, cloud, BigData, IoT, and advanced robotics. The combination of these technologies blurs the line between physical and digital words raising new questions in business models, organization operations, and societal implications.
Speaking of digital twins, they are virtual representations of physical objects, processes, or combinations of both. The near real-time connectivity between the physical and digital worlds transforms how we monitor, control, and manage equipment, systems, and processes shifting from a reactive to a proactive paradigm. The digital twin enables companies to find answers to the future stated questions, predicting implications from externalities or idiomatic intentional and occasional changes happening in assets, systems, or processes. Leveraging digital twins, companies can realize substantial benefits such as improved operations, product and service innovation, and faster time-to-market.
After conducting numerous interviews, researchers consolidated myths and facts, attributing them to the Roger 5 factors of innovation diffusion theory. Then they surveyed two groups of companies: early adopters that embraced the implementation of Industry 4.0 capabilities earlier and the second group that adopted them later. The survey revealed the difference in the agreement level between these groups over myths and facts.
Myths prevail more among later adopters suggesting companies in this group are less experienced with Industry 4.0 technologies and therefore have unwarranted assumptions yet to be validated in practical implementation. The opposite situation can be observed with early adopters, who started implementation and technology adoption early; consequently, they accumulated broader experience and tested a higher number of hypotheses. Earlier adoption of Industry 4.0 technologies could explain the higher level of agreement with the facts within the correspondent group (early adopters) since they mastered adoption longer.
Let's linger a little longer on the myths and facts themselves. As for me, the myth that all stakeholders will equally benefit from Industry 4.0 looks dramatic in combination with the fact that digitalization is inevitable. The inexorable march of technological evolution puts some people at a disadvantage and benefits others; such a trend surfaces many practical unanswered questions on how to make a company transition to industry 4.0 smooth and innocuous. In addition to the technology questions, the most burning ones are related to people and culture: how organizations can alleviate the inevitable workforce replacement from one side and skill supply and demand disparity on the market.
Speaking of complexity and trialability myths and facts, I cannot overlook a pair of "fails in environments with conditions of uncertainty" and "Digitalization can be used to transform all or part of the organization". They imply that the organizational operating model, an actuating mechanism for business strategy, is deeply affected and should be revised. Implementing only technology without changing processes, at best, yields mediocre results and, at worst, makes the routine more cumbersome and complicated slowing down execution. This is why operations digital twin converge technology implementation and operating model change.
As Marco Iansiti and Karim R. Lakhani pointed out in the book “Competing in the age of AI”, modern enterprises inherited twentieth-century operating models with highly specialized, siloed organization structures [1]. Most large enterprise companies are global, so their teams and processes are globally distributed. Following the mirroring hypothesis[2], the IT landscape reflects a siloed organizational structure compring dozens of systems with a vast amount of fragmented data. These factors inhibit organizations from seeing, comprehending, and improving organizational performance.
A successful Industry transition into Industry 4.0 is contingent on the business results' observability, which in turn depends on the technology and new operating model enabling cross-functional collaboration. So, the business pilot initiative's scope becomes critical; it should be horizontal enough to engage people from different silos to work together and provide enough learning capabilities to prepare the foundation for scale. Thus the operations digital twin is a promising concept for a pilot initiative. It is a holistic end-to-end view of organizational operations shaped around value delivery, enabling cross-silos collaboration spanning from initial order to the customer value delivered so that the critical company functions can work together. A digital twin will reveal a structure of value stream and organizational construct running it with its bottlenecks, variability, and volatility. Having a comprehensive dynamic picture of value delivery, an organization can make many better-informed decisions on what to change, what to automate, and what to augment because it can simulate and verify the decision's impact on the organization's performance before the change. The operations digital twin implementation can make the new process management more salient, dispelling the myth of "the greater the data collection allowed by Industry 4.0, the greater the control over process".
Not all myths and facts got significant differences in the agreement level among early and late adopters, suggesting that neither group had yet been exposed to the cases forming an unequivocal judgment, or these myths and facts are irrelevant to the implementation experience. Hereunder is the list of these myths:
- as predominant behaviors and values of the organization are not affected;
- the use of new technologies is fully reliable;
- the use of technologies alone does not lead to significant improvements on performance;
- ethical and legal standards must be revised
To conclude, the paper under observation outlined the practical implications for leaders driving digital transformation. First and foremost, understand and alleviate the negative impact on the potential stakeholders within and beyond company boundaries. The second important consideration of Industry 4.0 adoption is the socio-technical nature of the transformation so that, along with the technology introduction, the social construct of the organization will evolve along with the skills required. The last is the proper pilot’s scoping to accumulate enough learning building the foundation for the further scale along with weighted expectation management since operating model change takes time. To facilitate the transition toward new operating model operations, the digital twins look like a promising option.
Author: Pavel Azaletskiy
- Iansiti, Marco, and Karim R. Lakhani. Competing in the age of AI: strategy and leadership when algorithms and networks run the world. Harvard Business Press, 2020.
- Colfer, Lyra, and Carliss Y. Baldwin. "The mirroring hypothesis: Theory, evidence and exceptions." Harvard Business School Finance Working Paper 10-058 (2010).