Using data to make assets and operations more efficient and competitive
"Hey Google/Siri/Alexa, what will be the impact of IoT in 2025?"
Google: "By 2025 the IoT's economic impact will be around USD11.1 trillion - 14 percent of today's global GDP."
Alexa: I, unfortunately don't know.
Siri: Here is what I found on the web for 'What is the impact of IoT'
Maybe my question was not clever enough. Or maybe there are no clever answers to this question just yet. While the common assumption is that the Internet of Things (IoT) – empowered by digitalization – will be a game changer, industry exhibitions today are dominated by IoT pilots and breakout board solutions. At conferences, visions are presented rather than actual case studies of scale.
That being said, the combination of declining prices for sensors, data transfer, storage and computational power, paired with increasing efficiency and the ambition to do more with less, leaves little doubt that IoT will indeed be a game changer. But this will most likely be an iterative journey that will see many investments into solutions that may eventually be replaced later.
The success of IoT comprises two major elements: the standardization of communication protocols and the quality of data. Since the hype around data driven decision making took off some years ago, pioneers in the field encounter a lot of issues with data formats and quality, as well as ensuring the correct interpretation of data. While it sounds intriguingly simple to place a sensor, read its output and use the data to make better decisions in theory, the reality is much harder than it sounds.
Crap in, crap out
The old saying “Crap in, crap out” has never been truer. I still remember my university professor saying, “since we have computers, we get the wrong answers in a more sophisticated way”. To prevent this happening, we cannot just hand over our operations to robots. The success of IoT requires standardization of data acquisition, data communication, data storage and data handling, as well as a thorough data screening and qualification process. Last but not least, it needs the sound subject matter expertise of human beings to properly interpret input and output and qualify the process.
Once this is in place, the next step then is an ‘AI’ basing its learnings and decisions on the data coming from IoT and then feeding its learnings back to empower IoT. It is worth noting that ‘AI’ is commonly translated as ‘artificial intelligence’, a notion that seems to be based on cinematic visions rather than reality. In the words of NASA scientist Dr. Kirk Borne, there is no such thing as artificial intelligence; instead, AI can be more accurately expanded as ‘accelerated’, ‘actionable’, ‘adaptable’, ‘amplified’, ‘assisted’, or even ‘augmented’ intelligence (source).
At its core, IoT is simply a new name for an ambition the industry has held for decades now: using data to make assets and operations more efficient and competitive. Current advancements in and dropping prices of digitalization and computational power are finally allowing us to move towards achieving this dream in an economically viable fashion. This will help us improve efficiency and tackle the imperatives of decarbonisation and urbanisation. And while it may take a temporary toll on unemployment ratios, it will also make our lives more comfortable.
Keeping all of this in mind, there is little reason to fear that our world will be taken over by robots anytime soon. So perhaps the answers Google, Siri and Alexa provide are just honest; there is no revolution ahead, only a fast evolution of our current society – one that we will be able to shape into the way we want.
Mathias Steck, Executive Vice President and Regional Manager - Digital Hub, Asia,
DNV GL - Digital Solutions
This article was first published on APAC CIO Outlook