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“As an industrial engineer, I take abuse from the other self-proclaimed ‘real engineers’. But I ask them this: How many revolutions have you gone through in your discipline? Today, us industrial engineers are talking about our fourth revolution!” Teifel begins.

Quoting Albert Einstein, he says: “We cannot solve our problems with the same thinking we used when we created them”.

PTC productONE Cre0 5 ThingWorx IioT Harry Teifel“We have already completed three industrial revolutions. Is the fourth simply about doing the same things we did in the past – just more of it using smarter technology? Or is it really doing something differently. In this presentation I will be presenting the argument for the latter,” he says.

To achieve this he believes we need to unlearn a lot of the things we have relied on in the past: “Young people are far more fortunate as they have less to unlearn. The 4th Industrial revolution is breaking existing paradigms and leading to the creation of a new world,” he predicts.

4IR, he says, involves a phase of exponential productivity growth. “If you think about the other three industrial revolutions, they were all limited by physical things. In the first industrial revolution, for example, farm productivity depended on land, tools, cows and children. These all restricted how much could be produced.

“During the second and third industrial revolution: materials, energy and skills were physical limitations to growth. Bigger machines bigger factories and more resources were applied. In the third, limitations started to be overcome by physical automation systems that offered better quality and much faster mass production. But for the fourth revolution, we are in an area where sustainability and exponentiality is no longer defined by physical objects. It is defined by data,” he tells us. “We can now exponentiate data, which has phenomenal power,”
he argues.

“Exponentiality is the thing that now determines our expectations, not linearity. Each of the technologies associated with 4IR has considerable power, but combined they have unbelievable power – and we have only seen the beginning of these technologies working together. How is it possible that an organisation can grow rapidly and across the globe in previously unheard-of time frames? This was impossible during previous industrial revolutions and this is what is now changing the world,” Teifel explains.

Citing Amazon and AirBnB he says that the network effect has enabled these companies to reach massive target markets. So for traditional businesses, the message is: “Your shareholders will soon gauge, not what you are doing at the moment, but the network effect your business has going forward. While we can’t only have AirBnB-type businesses, these models have a drastic effect on how the world sees and appreciates what it is that businesses do and how they perform,” Teifel warns.

Explaining the notion of shared assets and their optimisation, he says that, in the past, business was all about owning stuff: a big factory, many employees and a flashy car in the car park. “It was about power.”

“Businesses will probably never need as many assets as they currently have because assets will be used jointly and owned and used collectively,” he continues.

Describing another key difference, he says that organisations of today are supply-chain like and linear. Future 4IR companies will have hybrid digital value chains with more and more parts of businesses being networked: It’s like the difference between a simple rope and a multi-dimensional net – and the linear chain will soon fade away completely.”

While supply and demand type relationships will continue to exist, ultimately networking to find and connect to unknown and wide networks will be the norm as opposed to depending on historically established supply lines. “When working in a network there is far less guidance and certainty about what’s going to happen.

“The networked consumer has the power to directly dictate what he or she wants. Instead of a car, we want mobility. A shift is happening where the power of the networked customer and their creativity becomes critical and any successful company must be tapping into it,” Teifel points out.

Supporting the transformation are disruptive technologies. “Everything is now digital with data being key to a high-value supply chain. Flexibility and complexity drives the way we now have to work – and we will have to do this just to stay alive.

“It’s a new way of thinking: The environment is adaptive and external factors drive us, not internal ones. It’s outside in as opposed to inside out. But in this environment, we are still required to deal with all the market permutations. Nobody is prepared to pay more. We all want it cheaper, faster and better,” he notes.

The 4IR disruption process has started in South Africa. It has hit the country in different waves and its impact can already be seen in industries such as mining, agriculture, media, banking and retail services, hospitality, health, consumer products and so much more. “So even if you haven’t been caught up in the first wave yet, the next waves are coming,” Teifel says.

Data differentiates

All areas of improvement depend on the value of the data collected. Why do modern day cars almost never break down? “Because the data collected over the years and in real time on the car itself enables design improvements and accurate problem prediction.

“Data is the differentiator: starting with collection and visualisation and then using analytics to link the cyber and the physical worlds. This can now be used to write automated self-optimising command and control routines. Humans no longer need to be involved in controlling every step. Machines can take care of the standard stuff,” suggests Teifel.

In a further step, he says that further analysis can be used to control and learn from the past – and for the future. This is about Artificial Intelligence (AI) and machine learning. In addition, data from a host of similar events can be collated so as to learn from them too, which is the ultimate goal of machine learning and AI – “and the fastest to implement will be the winners”.

From an implementation point of view, he cites six important dimensions to look at: the industry/business model; the business focus for the roll-out; the technologies involved; the IT solutions; the implementation strategy; and the change management solution.

“The 4IR model chosen for every company will be different,” he says. “A front-end company that deals with customers directly will focus on consumer and customer data, while a back-end company such as a mine will focus on its processes and performance. Organisations are not the same and the emphasis needs to be different depending on the nature of the business. In some cases, a company’s reputation may be more valuable than its assets, for example, so this risk must be carefully managed,” he advises.

In terms of technology for manufacturing companies, he says that autonomous robots, 3D printing and all the way to process automation using Internet-connected devices are all available. “Not all will be useful to everyone and incorrect adoption may kill a business. In terms of data, the rollout should be done so that whatever is needed on the evolutionary path can be usefully collected now without limiting future expansion.

“This rollout is the biggest challenge. Do we explore areas aligned to our traditional business and implement something that we know will work now? Do we undertake a radical transformation of the organisation into a 4IR company? Do we create a brand new Greenfield organisation or do we buy in solutions? Or all of the above? The decision has massive implications!” he warns.

Teifel suggests focusing on the data evolution goal: to inform our specific business and industrial environment: “It’s about collecting, bundling and leveraging data relevant to one’s business environment,” he suggests. “Connecting sensible things from all parts of the spectrum, while maintaining complete flexibility to respond to the changing environment.”

Most importantly: “It is not about taking existing hierarchy’s and translating them. The evolution to 4IR requires a holistic and fundamental systems engineering rethink via upwardly scalable platforms that can harness the likes of Augmented Reality (AR), AI and Industrial Internet of Things (IIoT) capabilities,” he surmises.

4IR success requires flexibility

What does this mean for organisations embarking on a Digital Transformation journey? “The biggest reality is that in most cases companies don’t know what they don’t know. This means long-term planning is out. Instead, companies need to provide for complete and multi-dimensional flexibility going forward, both in terms of the evolution of how data is deployed; as well as how collaboration is accommodated.

“It is in this context that solutions such as PTC’s ThingWorx and Creo are vital to allow organisations this potential in an unchartered world going forward,” Teifel concludes.

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Peter Middleton
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