Part 1 in a 2-part series. Read Part 2.
Call it a “Forrest Gump moment:” an instance of being in the right place at the right time for no other reason than just plain luck. A “Forrest Gump moment” is based upon Tom Hanks’ character in the movie “Forrest Gump,” a guy who always seemed to be in the right place at the right time, meeting Presidents Kennedy, Johnson, and Nixon at critical points in American history.
I too have had a Forrest Gump moment in meeting President Reagan. However, my deeper Forrest Gump moments have been my long association with the history of analytics. I was fortunate to be at the birth of the business intelligence and data warehouse era while working for Metaphor Computers to deploy decision-support systems across Procter & Gamble in the late 1980s. And I was fortunate again in the late 2000s to be at the launch of the data science era while building Advertiser Analytics at Yahoo.
Now again, I find myself at another Forrest Gump moment in my opportunity at Hitachi Vantara. We are at the cusp of the next Industrial Revolution, fueled by new technologies such as autonomous vehicles, virtual/augmented reality, artificial intelligence (AI), robotics, blockchain, 3D printing, and the Internet of Things (IoT). The purpose of this blog is to provide some insights into how to properly prepare to derive new sources of customer, product, and operational value for this next Industrial Revolution: Industry 4.0.
Birth of Industry 4.0
A recent Deloitte report titled “Forces of Change: Industry 4.0” describes Industry 4.0 as such:
“Industry 4.0 signifies the promise of a new Industrial Revolution—one that marries advanced production and operations techniques with smart digital technologies to create a digital enterprise that would not only be interconnected and autonomous but could communicate, analyze, and use data to drive further intelligent action back in the physical world.”
The key aspect of Industry 4.0 is the melding of the physical and digital worlds around new sources of operational data that can be mined to uncover and monetize customer, product, service, and operational insights.
Figure 1: Powering the Physical-to-Digital-to-Physical Loop
Analytic profiles for the human players and digital twins (see Figure 1) for the physical devices will play a critical role in powering this “Physical to Digital to Physical” (PDP) loop:
- Physical to digital: Capture information from the physical world and create a digital record from physical data.
- Digital to digital: Share information and uncover meaningful insights using advanced analytics, scenario analysis, and artificial intelligence.
- Digital to physical: Apply algorithms to translate digital-world decisions to effective data, to spur action and change in the physical world.
In the world of Industry 4.0, the digital twin is the foundation for IoT monetization. It is around these digital twins that organizations will build intelligent IoT applications such as predictive maintenance, inventory optimization, quality assurance, and supply chain optimization (see Figure 2).
Figure 2: Digital Twins Monetization Platform
A digital twin is a digital representation of an industrial asset that enables companies to better understand and predict the performance of their machines, find new revenue streams, and change the way their business operates.
Understanding Industry 4.0 challenges
The biggest challenges for Industry 4.0 will be where and how to apply these new industrial technologies to derive and drive new sources of customer, product, operational, and market value. However, we are fortunate to have learnings from previous revolutions – Industrial and Information – that we can apply to Industry 4.0.
In the blog “How History Can Prepare Us for Upcoming AI Revolution,” we discuss how those revolutions were fueled by organizations that exploited new technology innovations to identify and capture new sources of customer, operational, and market-value creation. The Industrial Revolution was driven by new technologies such as interchangeable parts (the famous ¼” bolt), specialization of labor, factory-floor assembly concepts, and availability of steam power. The Information Revolution was powered by new technologies such as x86 and MS-DOS/Windows standardization, packaged database and transactional applications, and availability of the Internet.
And the driving force for capturing the economic benefits from each of these revolutions – and what we are seeing today with the Intelligence Revolution – was the transition from handcrafted solutions to prepackaged, mass-manufactured solutions. I expect the same pattern from Industry 4.0.
One other Industry 4.0 challenge with which organizations must wrestle is the role of the government (in the form of regulations that nurture both competition and collaboration) and universities (in preparing workers for Industry 4.0). Government and universities will need to work with industrial concerns to accelerate the preparation and ultimate adoption of Industry 4.0.
Industrial Revolution Lessons
- The Industrial Revolution changed society rapidly and permanently, and workers, owners, and government responded differently to negative effects.
- Government and owners expected the marketplace would self-correct the worst ills, but it did not.
- With government and owners unwilling to enact reforms, workers, reformers, and critics responded on their own, sometimes violently.
- Decades into the Industrial Revolution, the British government began gradual reforms.
To successfully nurture “revolutions,” governments must play a leading role, providing guidance to encourage sustainable growth while preparing masses.
The need for collaboration
There must be strong collaboration, as I am seeing from organizations like Team NEO (Northeast Ohio) and Jobs Ohio that are driving collaboration between government, universities, and industrials like Hitachi.
In Part 2 of this series, we’ll look at how Industry 4.0 is creating smart products and spaces.
This article originally appeared on LinkedIn and is republished by permission.