Digital Transformation In Manufacturing – Key Learning Points From The Automotive Industry

The manufacturing industry is positioned to take advantage of the possibilities offered by artificial intelligence, automation, and industry 4.0. To get an idea of the benefits and challenges that lie ahead, it’s a good idea for manufacturers to look towards the automotive manufacturers, which are perhaps further along the journey than other manufacturers.

As a product, cars are evolving rapidly. Combustion engines are being replaced by batteries, connected cars carry an ever-growing array of hardware and software applications, and fully autonomous cars are not too far down the road. To cope with the changes to their operations and processes that this fast-paced evolution has made necessary, car manufacturers have established themselves as pioneers when it comes to tackling the challenges of digitization.

As well as adapting to new technological requirements, it has also been necessary for automotive manufacturers to anticipate and align their offerings with changing consumer behaviors. This includes demand for more sustainable and less environmentally damaging products and new ways of thinking about how we use cars, such as carpooling and ride-sharing.

 To get an idea of what the wider manufacturing industry can learn from automotive manufacturers, I spoke to Aniello Pepe, Oracle’s global director for automotive within its Industry Strategy Group.

Pepe told me, “Automotive is an exciting place today – no other manufacturing industry is going through such challenges … the product is completely changing … it’s a product that’s becoming more digital, more software, more electronics … and that implies that the suppliers are changing.

“There are new suppliers because they can provide new components – batteries, for example.

“As well as this, customers are changing – this is affecting everything, the way products are conceived, designed, tested, sold – there are new ownership trends and new financial models.”

The period we are going through right now is particularly critical, as automotive manufacturers have to balance their need to innovate and look towards the new era in electric, connected, and autonomous driving with the fact that, for now, the majority of vehicles they sell and service are still built around internal combustion engines. This will be equally true in other manufacturing industries, where it won’t be the case that all of their customers will be ready to switch to using new, smart, and automated versions of their products overnight.

The automotive industry is anticipating and reacting to trends that just about every other field of manufacturing will experience soon. So, what are the lessons that can be learned?

Firstly, it’s critical to understand the migration taking place towards platforms. Manufacturers use software platforms in the design and creation of new vehicles and to gather test data on how they will perform in the real world (such as crash testing). Manufacturing is done through platforms – connecting the IoT sensors and devices that make up a modern assembly plant.

Platforms exist for the vehicles themselves to enable them to be connected and work together effectively as edge nodes for a cloud platform. Platforms have been built out into sales and customer service operations, allowing manufacturers to predict, based on data, the “next best action” in sales or service that should be taken to achieve an optimal outcome.

And customers themselves interact with the vehicle manufacturers via yet more platforms that allow information on their experience to be collected and analyzed for insights into how things could be done better or more efficiently.

Volkswagen Group, for example, has established its own software company, CARIAD, which works on creating platform-based solutions for challenges faced by manufacturers, as well as software solutions for customer problems.

This is in line with the wider trend of companies in many industries reimagining themselves as tech companies to better position themselves to use technology to solve problems. Currently, just 10% of the software platforms used by Volkswagen are created in-house. By establishing Cariad, it hopes to increase this to 60% by 2025.

Likewise, Renault, in the words of its recently appointed CEO Luca De Meo, intends to transform itself from a car company that works with technology to a technology company that builds cars.

Business models are changing too. Renault’s ambition is to generate 20% of its revenue from services – sold through subscriptions – by 2030.

The second element that it’s critical to understand is the importance of data. Digital services – based on collecting and analyzing data using vehicles and sensors – are expected to generate one-third of the automotive industry’s revenue – around $1.5 trillion – by 2030.

This will require finding ways to extract insights from data that customers will be willing to pay for through subscription services “bolted on” to their car purchases (or leases). Finding new ways to collect this data, mine it for insights, and package it back to the consumer in return for subscription fees will be a core driver of revenue for automotive manufacturers – and eventually most other manufacturers too.

Pepe tells me that he sees three key challenges that automotive manufacturers are tackling to make this vision a reality. Firstly, they need to develop the capability to manage software at scale. This includes dealing with the diverse range of markets and jurisdictions that they operate in, which can involve a complex web of regulations and legislation – particularly about the use of data.

Secondly, it requires a new approach to product life cycles. Software and electronics – which make up 50% of the value of the typical car sold today – require management and updates, and new functionality can be added by creating new applications for existing hardware – such as the range of sensors and cameras that many new cars are equipped with. This enables the creation of new services that can be paid for via subscription (Tesla’s Autopilot being perhaps the flagship example here).

Thirdly, there’s the ever-pressing issue of skills. Automotive manufacturers are now less reliant on mechanical engineers and more reliant on software engineers and data scientists. They need people who are capable of setting up cloud platforms for gathering, storing, and analyzing data – the fuel of automation and industry 4.0 – as well as those capable of deploying cutting-edge technologies such as AI – machine learning, and neural networks.

The scale of this transformation has been immense in automotive manufacturing and will be just as massive in other manufacturing industries that are also preparing to leap.

All of this means that partnership choices are critical, and Pepe tells me that this is where companies like Oracle, or indeed SaS, or even Google – cloud hyperscalers – are a natural fit. After all, they have gone through many of the same processes themselves, building out tech solutions with multiple novel customer touchpoints and a service-focused delivery method.

He says, “Automotive manufacturers and their suppliers are still in the middle of their transformation journey. Some are progressing faster; others are plodding along with uncertainty. Winners will emerge quite soon, and I think those will be the ones that are better able to understand the implications of their transformation into software and tech companies, and service and mobility providers – they will be in a better shape to survive and prosper.

“For me, that means adopting cloud-based solutions and leveraging the power of data through artificial intelligence.”

The 5 Biggest Technology Trends In 2022

In 2022 the covid-19 pandemic will continue to impact our lives in many ways. This means that we will continue to see an accelerated rate of digitization and virtualization of business and society. However, as we move into a new year, the need for sustainability, ever-increasing data volumes, and increasing compute and network speeds will begin to regain their status as the most important drivers of digital transformation.

For many individuals and organizations, the most important lesson of the last two years or so has been that truly transformative change isn’t as difficult to implement as might have once been thought, if the motivation is there! As a society, we will undoubtedly continue to harness this newfound openness to flexibility, agility, and innovative thinking, as the focus shifts from merely attempting to survive in a changing world to thrive in it.

With that in mind, here are my predictions for the specific trends that are likely to have the biggest impact in 2022. You won’t find musings on quantum computing, neural interfaces, or nanotechnology – while they are certainly on the cards, their impact will be felt further down the line. Instead, the most important trends in 2022 are likely to focus around the convergence of technology trends, as tools emerge that let us combine them in new and amazing ways.https://www.linkedin.com/embeds/publishingEmbed.html?articleId=8858980543988388815

Artificial Intelligence everywhere

“Smart” really just used to mean connected – smartphones, smart TVs, and the plethora of other smart devices were just the same old toys but connected to the internet. Today, “smart” increasingly means powered by artificial intelligence (AI) – generally machine learning algorithms – and capable of helping us in increasingly innovative ways. Smart cars use facial recognition algorithms to detect whether we are paying attention to the road and alert us if we’re getting tired.

Smartphones use AI algorithms to do everything from maintaining call quality to helping us take better pictures, and of course, they are packed with apps that use AI to help us do just about anything. Even smart toilets are on their way – capable of helping to diagnose gastrointestinal issues by using computer vision to analyze stool samples!

AI has permeated the tools we use to carry out everyday work – from the ubiquitous voice assistants to language translation and tools that allow us to extract structured data from pictures, whiteboard scribblings, and hand-written notes.

It also powers much of the robotic process automation that has enabled workloads to be lightened in admin, logistics, accounting, and HR departments. Whatever your industry or job function, you’re likely to find there’s an AI-powered solution designed to make your life easier.

This broad trend encompasses AI, the internet of things (IoT), and newly emerging super-fast networks like 5G, all of which are coming together to augment us with capabilities we didn’t have just a few years ago.

This highlights the fact that on a longer timescale than the one we are specifically looking at here, the most impactful trend of all will be convergence. Growing data volumes, faster network and processor speeds, and the “democratization” of data (more on this below) are coming together and will affect society in a way that is much more than the sum of their parts.

Everything-as-a-service and the no-code revolution

Another increasingly powerful driver will be the ongoing democratization of data and technology. In recent years an entire industry has emerged that aims to put the skills and tools necessary for tech-led innovation in the hands of as large a proportion of society as possible, regardless of their expertise or experience.

Cloud solutions for storage, network and processing mean costs and risks of setting up expensive infrastructure to try out new ideas are heavily mitigated. Hybrid solutions – for when public cloud services aren’t entirely appropriate, for example when dealing with very private or valuable data – have matured to the point where a “best of both worlds” solution is often viable.

Innovation has been curtailed in some areas by the skills crisis, which sounds like a problem but has been a driver behind the explosion of self-service and “do-it-yourself” solutions. Not every company needs to hire an army of computer geniuses to build their own “digital brain” when they can simply lease one for the work they need doing. Ready-built AI solutions exist for everything from marketing to HR, project management, and planning and design of production processes. In 2022 we will continue to see companies deploying AI and IoT infrastructure without owning a single server or proprietary piece of cognitive code.

No-code interfaces will become more popular as a lack of programming knowledge, or a detailed understanding of statistics and data structures, will cease to become a barrier to bringing a world-changing idea into reality. OpenAI – a research group founded by Elon Musk and funded by, among others, Microsoft, recently unveiled Codex, a programming model that can generate code from natural, spoken human language. As technology like this matures – which we will start to see in 2022 – and converges with the possibilities offered by cloud infrastructure, our innovation and imagination will less frequently be held back by a lack of either resources or technical skills.  

Digitization, ratification, and virtualization

During 2020 and 2021, many of us experienced the virtualization of our offices and workplaces, as remote working arrangements were swiftly put in place. This was just a crisis-driven surge of a much longer-term trend. In 2022, we will become increasingly familiar with the concept of a “metaverse” – persistent digital worlds that exist in parallel with the physical world we live in.

Inside these metaverses – such as the one proposed recently by Facebook founder Mark Zuckerberg – we will carry out many of the functions we’re used to doing in the real world, including working, playing, and socializing. As the rate of digitization increases, these metaverses will model and simulate the real world with growing accuracy, allowing us to have more immersive, convincing, and ultimately valuable experiences within the digital realm.

While many of us have experienced somewhat immersive virtual realities through headsets, a range of new devices coming to the market will soon greatly improve the experience offering tactile feedback and even smells. Ericsson, which provided VR headsets to employees working from home during the pandemic, and is developing what it calls an “internet of senses,” has predicted that by 2030 virtual experiences will be available that will be indistinguishable from reality.

That might be looking a little further ahead than we are interested in for this article. But, along with a new Matrix movie, 2022 will undoubtedly take us a step closer to entering the matrix for ourselves.

Transparency, governance, and accountability

For technology to work, we humans need to be able to trust it. We already (rightly) see strong pushbacks against many ways that technology is currently being used that are seen as obtrusive, dangerous, or irresponsible.

AI, in particular, is sometimes portrayed as a “black box” – meaning we can’t see inside it to understand how it works. This is often due to its complexity rather than any malevolent scheme to limit our understanding, however, the effect is the same. This means that incidents where AI is shown to be damaging – for example, when Facebook recently appeared to label images of black people as “primates” – are extremely alarming. This is particularly true in a society that is starting to look towards AI for decision-making that affects lives, such as hiring and firing.

The idea of transparent and explainable AI has been growing in popularity over recent years, as it has become clear that there are segments of society that distrust it – clearly with good reason! Governments, too, clearly understand that there is a need for a regulatory framework, as evidenced by the existence of the EU’s proposed Artificial Intelligence Act.

The proposed act prohibits authorities from using AI to create social scoring systems, as well as from using facial recognition tools in public places. There is also a list of potentially dangerous effects, including “exploiting vulnerabilities” and “causing physical or psychological harm,” that AI solutions providers will have to demonstrate their systems will not cause before they can be offered for sale.

Some, however, claim that it doesn’t go far enough as, in its current state, it doesn’t contain any stipulation that people should be informed when they become the subjects of AI-driven decision-making processes. Google CEO Sundar Pichai has said that while he recognizes regulation of AI is necessary, “there is a balance to be had” to ensure innovation isn’t stifled.

This balancing act is likely to become an increasingly prominent subject of discussion during 2022 as more people become aware of the potential positive and negative effects on society that AI and other technology trends will have.    

Sustainable energy solutions

During the pandemic, renewable energy was the only form of energy that saw usage increase. In the US, renewable energy use increased by 40% during the first ten weeks of lockdown. Worldwide, all non-renewable energy usage decreased as industries shut down and people stayed at home, leading to an overall reduction in emissions of 8%. This has led to an expectation that increased investment will be put into generating energy from renewable resources in the coming years.

The International Energy Agency (IEA) estimates that 40% more renewable energy was generated and used during 2020 compared to the previous year and forecasts that this growth with continue throughout 2022. Overall, the cost of generating renewable energy from various sources, including onshore and offshore wind, solar and tidal, fell by between seven and 16%.

This will be a huge help for countries and businesses trying to hit emissions targets, such as becoming carbon neutral or even carbon negative. Additionally, exciting new emerging energy sources such as biofuels, liquid hydrogen, and even nuclear fusion are becoming more viable, even if it may be a little after 2022 when their full impact of some of them will be felt.

However, breakthroughs in all of these areas are likely to make headlines. Helion Energy – a pioneer in the field of fusion energy, which replicates the process used to create energy in the sun – expects their latest prototype fusion generator to come online during 2022. Practical applications are also expected to emerge in the field of “green hydrogen” energy.

Unlike the established processes for creating energy from hydrogen, which involve using large amounts of “dirty” fossil fuel energy to create electrolysis, separating hydrogen and oxygen without emitting carbon, this involves using renewable energy, dampening the overall environmental impact.

About The Author

Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a strategic business & technology advisor to governments and companies. He helps organizations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence, big data, blockchains, and the Internet of Things.

Related posts