The countless definitions for the Internet of Things (IoT) in textbooks and online are an indicator of the scale of its scope. It is a vast subject area of innovation and possibility.
But if you sift through all the jargon you’ll find that, at its core, the Internet of Things is simply about bridging the gap between the digital and physical worlds. It’s a gap that has blurred as technology has steadily reached further into daily life.
For example, you might not realise that you use IoT, but you might be wearing a connected device right now in the form of a smart watch or fitness tracker. This device is digitising information about your personal health, making it accessible in real time on your phone or computer.
We now spend so much of our lives – in both time and money – in the digital world (the average Australian spends more time each day in front of a screen than they do sleeping). Yet the online world is still relatively disconnected from the physical world that we live and do business in.
Digitising the world allows us to better understand it. As the old saying goes, you can’t manage what you can’t measure. That applies to businesses, communities, even the planet itself.
But digitisation is only the first step towards what the World Economic Forum calls the Fourth Industrial Revolution – a world of driverless cars, biotechnology and automated supply chains. Not only will there be less waste due to better utilised assets and resources, but new business models will also emerge, all enabled by the Internet of Things.
The Internet of Business
The global economy is estimated to already be at least 20% digital. With the Fourth Industrial Revolution progressing over the next decade, this could increase to 80% or more over time, as physical assets and processes become digitised. This is already steadily happening in key industries like manufacturing, agriculture and logistics.
A recent BI Intelligence report estimated there will be up to 22.5 billion IoT devices in 2021, up from 6.6 billion at the end of 2016. The growth in the number of devices represents a $US4.8 trillion investment from businesses and consumers across the globe.
The IoT consists of networked sensors and actuators, communicating via the Cloud or directly with each other (machine-to-machine, or “M2M”). These devices are standalone, such as soil moisture probes used in agriculture, or built into assets that were previously not smart and connected, such as cars or rubbish bins.
They can communicate thanks to Application Programming Interfaces (APIs), something most digitally-enabled businesses already use day-to-day, and they can produce large amounts of data, much of it unstructured, like video or audio. This data needs to be processed in order to be useful, meaning that Big Data and machine learning can be key enabling capabilities for businesses looking to harness IoT’s benefits.
The data being created by IoT allows people and businesses to learn more about their own strategy, operations and productivity. The issue at the moment is that most businesses don’t have the ability to process this data, so its value is unrealised.
According to IBM, up to 90 percent of the data created by IoT devices isn’t captured properly or analysed, and more than half of it isn’t stored correctly, so it can never be properly analysed. But capturing and storing the data is the first step. Guido Bartels, General Manager IBM Nordic, believes the true potential of the IoT is in using this data to form insights. He said:
Massive amounts of data that instrumented devices collect provide businesses the opportunity to learn about the environment in which they operate, gleaning insights that can be turned into actions. These insights can help formulate new delivery models and fundamentally change how a business operates.
Cisco also identified this opportunity back in 2011 tying it back to how humans have evolved through processing data, sharing that information and building on previous discoveries.
Data is the raw material that is processed into information. Individual data by itself is not very useful, but volumes of it can identify trends and patterns. This and other sources of information come together to form knowledge… Wisdom is then born from knowledge plus experience. While knowledge changes over time, wisdom is timeless, and it all begins with the acquisition of data.
(Cisco, 2011 )
Automatically turning data into wisdom is one of the great technological challenges of our time. A great example is driverless cars collecting data about the world that they drive through, processing it into useful information that they can make decisions on, and continuously learning at scale through this feedback loop until they attain “wisdom” – or the ability to drive significantly better than humans. There is evidence that this process is happening faster than some predicted.
IoT makes things searchable from anywhere in the world – in the same way that you can be anywhere in the world and search for anything on Google. In the not-too-distant future, we’ll be able to search from anywhere in the world: “What is the exact temperature in this shipping container and what condition are my goods in?”, or, “How many goods do I have in this warehouse?”
As the cost of computer chips decreases, it’s becoming more feasible to digitise assets and processes that wouldn’t normally be interconnected. The potential uses for the data generated by IoT connected devices keeps growing.
Source: Business Insider Intelligence
Every crop, every paddock
For example, for farmers that rely on a single harvest a year for their income, every crop and every paddock matters. With new IoT technology, it will be possible to monitor the precise fertiliser, pesticide and water input, and plant growth, in any individual paddock. Combining this data with financial records will allow farmers and their financial managers to make better decisions by understanding the investment and potential return in each individual paddock. This could lead to a better understanding of risk, which could enhance financial management in an industry that has high cashflow variability.
Bringing this vision to life will require improvements to data collection and analysis, system integrations, and connectivity.
However, aside from technical challenges, two big issues are holding businesses back from opportunities to access the full benefits of this new paradigm of analysis, control and automation.
The first is that businesses all over the world are grappling with trying to find the balance between cost savings through digital productivity, and value creation through inimitable human contribution. As the physical world is digitised, the gains from automation are only beneficial if they’re integrated into digital processes that can demonstrably improve on the current systems.
Second is the challenge of picking the right processes to digitise and automate, so that the flow on effect is positive for the broader economy. Machines are now able to support us in a much more efficient and effective way than in the past — freeing up time to spend doing what matters most. The proof case for this model already exists. You don’t need to look far in most businesses to identify repeatable (and often mundane) tasks that chew up the time of customer-facing staff. Automating some business processes also removes the potential for human error, introduces scalability that’s not possible without connectivity, and increases the timeliness of the data collected.
Right now, huge swathes of assets are underutilised. They meet a particular demand and then sit idle when they’re not in use by their owners. Consider: a car that sits in a garage when not being driven, a tractor that sits in a field when a farmer doesn’t need it, or a building that sits empty two-thirds of the day.
Digitising assets is the first step to increasing their productivity.
Connected sensors enable the creation of a “digital twin” – a digital representation of a physical asset. Once assets have been digitised it will be possible to track their location and performance in real time. (This is already common for certain vehicles and industrial equipment – you can read more about it here.)
Integrating operational data with financial records and other data sources will enable businesses to optimise the value that they get out of their assets over their life cycle through predictive maintenance, improved utilisation and energy efficiency.
For example, through predictive maintenance, if the data your car is generating could tell you there is an issue with a particular part, you could book the car in to replace the part before the wear and tear impacts the system around it – or you’re left stranded and inconvenienced by a break down. If this data is shareable with the manufacturer or your preferred service provider, they could even contact you in advance and offer to fix it for you on a day that their data predicts that you’re not likely to need your car.
Eventually, assets will be directly integrated into digital marketplaces, meaning they will be digitally connected to all of the services that they need – from inputs, to insurance, to an operator (i.e. the sharing economy). Advances in automation and artificial intelligence will then enable assets to manage and operate themselves, freeing up businesses to focus on value-adding activities.
New business models
Another growth opportunity lies in generating new revenue out of an existing asset, turning it into an “as a service” business model. My favourite example is a simple one. Imagine if you have a drone, and you put your drone charging station on your roof. When you’re not using that station to charge your own drone, you could rent it out to other drone owners for a fee. Other drone owners could then use their own drone – or fleet of drones – on longer operations because they know there will be another charging point on the journey and they don’t have to rely on the drone completing a job in a single trip.
This has a flow on effect for each industry the asset impacts. The car industry is an obvious example. It has already been disrupted by ride-sharing (also enabled by IoT via the phones of drivers and customers), but asset sharing is the new trend. Car Next Door – which allows people to share cars – is trading on the fact that most cars are only being driven for 5% of the time. While the security risks create an initial hesitation for some people, the commercial benefits make a compelling argument.
The cost of buying high-value assets is a huge barrier to entry for new businesses, but this could be negated as new IoT systems provide the ability to utilise existing assets. Commonwealth Bank research found that a great number of high value assets are currently underutilised by businesses, with the most commercial opportunities in the manufacturing, agriculture and logistics industries.
According to data from the IDC, the manufacturing industry spent $178 billion in 2016, but the conversation around investment is changing. Right now, if a company needs to move a lot of equipment, they’re likely to invest in a truck – or fleet of trucks – which will in turn require driving staff, maintenance, insurance and capital investment. But what they actually need is a service – to move equipment from one location to another.
BI Intelligence recently wrote about this growing IoT services industry, giving the example of Schneider Electric, a €36 billion, 180-year-old manufacturer of electrical equipment that has moved from a sale business to a service and hire model that also uses IoT data to manage predictive maintenance on their assets.
The report notes that, increasingly, “vendors aren’t selling a product, or even a set of products. They’re selling efficiency, transparency, and intelligence as a service.”
Machines as customers (and service providers)
If we follow this trend to its natural conclusion, then we can foresee autonomous assets providing services to other autonomous assets that are scheduled and purchased through digital marketplaces. In this vision of the future, asset allocation and utilisation is optimised to the nth degree, and supply chains are fully automated.
This is the machine-to-machine economy.
This is a powerful use case for connecting our physical world with the digital, and has the potential to be meaningful to the financial wellbeing of people and businesses. Commonwealth Bank’s Head of Emerging Technology, Dilan Rajasingham, describes this vision in his speech from the 2017 Everything IoT event.
As the IoT grows and networks merge and evolve, we believe businesses will be more connected with their customers, their assets and each other. If IoT data can be shared securely it will create a multiplier effect and help break down industry borders. But as we focus on digitising assets and connecting them to an IoT network, we are reminded that the greatest opportunity lies in creating value and building systems that enhance the lives of people all over the world.
Although most of these benefits will be enjoyed by the businesses of the future, there is ample evidence that the more technologically advanced businesses of today are already improving the productivity of their assets using IoT.
The technology is ready and waiting to solve meaningful business problems.
Andrew Despi is Commonwealth Bank’s Manager Emerging Technology, Enterprise Services.
This article has been prepared by Business Insider solely for informational purposes and is not to be construed as a solicitation, an offer or a recommendation by the Commonwealth Bank of Australia. This information does not have regard to your financial situation or needs and must not be relied upon as financial product advice or Investment Research. You should seek professional advice, including tax advice, before making any decision based on this information. We believe that the information in this article is correct and any opinions, conclusions or recommendations are reasonably held based on the information available at the time of its compilation but no representation or warranty, either expressed or implied, is made or provided as to accuracy, reliability or completeness of any statement made in this article. Commonwealth Bank of Australia ABN 48 123 123 124.
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