In yesterday’s blog post regarding Cisco’s predictions for the growth of the Internet of Everything (IoE), I was clearly not impressed by some of the figures being thrown around. While I didn’t totally disagree with their calculation that M2M could result in over $14T in savings/business improvement, my issue was that they didn’t put any “meat on the bone”, and the claim came across as more of a publicity grab than anything else.
Well, if I felt that way about Cisco’s claim, wait till you hear how I feel about GE’s claim about the “Industrial Internet” – one day, I will be happy when we standardize on a name! Here is the claim statement from a GE document:
"We estimate that the technical innovations of the Industrial Internet could find direct applications in sectors accounting for more than $32.3T in economic activity."
So, I have to find this laughable, right? I mean, if I don’t like $14.4T (from Cisco's predictions), I certainly find a figure that is over 2x that amount to be even more outrageous, right?
Well, I am not going to lie to you....it is a stretch, making a lot of assumptions about the mass market deployment of M2M to get anywhere near this total. However, while I may find the total to be quite high, I see better where GE derives this total from than what Cisco mentioned, as GE uses some real-life examples to show what could be done today and down the road in the future.
The power of 1%
While the term “1%” hasn’t been a popular one, based on the headlines during most of the past US presidential election, it actually has a positive connotation here. The idea of 1% here is “we have to assume that these solutions can improve things by 1%”. The concept here is further driven home by the fact that the size of the industries are just so massive....massive enough that 1% reduction would mean millions of dollars annually, and tens (or hundreds) of millions over the next couple of decades. In the chart below, GE cleverly lists a few key industries, where the potential savings would be in that space and what the savings would be over the next 15 years. As you can see, even a 1% impact would have a major difference on the bottom lines of many companies....and, I have to think that the savings of a properly executed solution would be a lot more than 1%. This was well done.
The three waves of innovation
In the article, the authors compare the Industrial Internet revolution to two previous revolutions that have changed our lives as we know it (see the graphic from the document):
- The Industrial revolution from 1750 to 1900
- The Internet revolution from 1950 to today
The comparison to the Industrial revolution is a bit of a stretch in my mind. While I see tremendous changes being offered by M2M, I doubt that the changes are as dramatic as moving from horse/carriage to a car! However, in terms of how much the Industrial Internet could optimize the way we do business, I see what they are getting at. The savings will be enough to dramatically change some industries.
The comparison to the Internet revolution is closer in comparison to the numbers and the concept, but still is a stretch in my mind. The Internet has indeed changed life as we know it – changing how we shop (both research and buying), how we communicate with each other and even how we pay taxes. While I see the Industrial Internet revolution having a significant impact on productivity, it won’t likely have nearly the same impact.
For those under 30, here are some interesting facts about the growth of the Internet from the document:
- In 1981, there were less than 300 computers connected to the Internet. By 1996, the number was in the millions. Today it is now in the billions.
- In 1985, the best modems were transmitting at 9.6Kbps......the first iPhone transmitted at over 400x that speed....wirelessly.
Big push = reducing energy consumption
One of the main ways that GE claims the Industrial Internet will change things is by finding ways to greatly reduce the energy consumption in the world of Industrial transportation and industrial production.
Here are some estimated stats from the paper:
- Energy consumption for Heavy-Duty Transportation (trucks, buses, aircraft, marine vessels and rail engines) could be reduced by 15-20% through optimization
- 14% of global fuel usage (in the Industrial space) can be reduced....mostly by concentrating on the Heavy Industries such as Steel, metals and Petrochemical
By things that spin, do you mean my kids?
The paper adds in an interesting concept, as it mentions how important it will be to monitor “things that spin”, which is a great term by the way. The idea is that things that spin generally are powered by a motor, and since there are a lot of moving parts, these items are more prone to failure / requiring more maintenance than things that do not act the same way (same reason why solid-state hard drives on computers tend to last longer when compared to traditional drives that spin). As well, most of these motors provide great amounts of data (things such as temperature, fluids and air pressure and vibration).....things that can be monitored to better optimize usage and lengthen product life. They are a key target for M2M, and the paper hits a home run with this concept.
Among the things that spin, GE points out that there are a lot of things that can be monitored today, including:
- Estimated 100K air craft engines that will be in use by 2025, with 3 “things that spin” inside of each
- In each power plant, there are over 100 components that can be measured, resulting almost 260K parts that can be optimized/monitored
- On the 120K rail engines deployed worldwide today, there are over 2M moving parts that can be monitored, with this expected to grow by an additional 400K by 2025
- There are 655 oil refineries in the world, with a total 36K measurable components
- Many of the key pieces of equipment used in Health Care have rotating machinery, including key components in 52K CT scanners.
These numbers, which total up to over 3M machines by GE’s calculations, do not include the fact that dozens of sensors may be used on each of these devices, resulting in a huge amount of analyzable data.
Some real-life examples
While I still think that GE’s claims are quite aggressive, one can start to see how this change towards Industrial Internet will change many businesses. Based on the sheer size of many of these industries, these numbers are quite staggering.
However, these examples leave out one very important benefit to the massive deployment of this technology.....labor shortages. As I mentioned in a previous blog post, there are labor shortages in many key industries, especially on the repair side. By optimizing many pieces of equipment, many industries can help solve these shortages, many of which are expected to get worse in the next decade.
Examples of how M2M can save money:
- 5% reduction in fuel savings for the airlines = $8B annually
- $1.3B in annual reduction in capital purchases by airlines per 1% optimization of equipment usage
- $250M annual savings for every 1% optimization in airline maintenance
- $5.6B in annual savings by optimizing railroad inefficiencies by only 2.5%
- $3.3B savings in savings (per 1% optimization) of power generation plants
- 1% optimization of Oil exploration = $6B annually
- 1% optimization of US Healthcare clinical and operational efficiencies = $4.2B annually
I think the paper provides a good overview of what some of the benefits of M2M are for some industries (not surprisingly, it focuses on markets that GE is currently involved in). It also does a good job in explaining where the actual cost savings will be. For the most part, it shows the savings on a very non-aggressive method per industry, but the concept of saving $32T seems like a stretch to me. That being said, I would love to be wrong here!
As always, let Novotech know how we can help with your M2M needs, such as antenna selection. You can visit our web page @ www.novotech.com. As well, feel free to reach out to me directly ....larry(@)novotech.com. You can also follow us on Twitter (@NovotechM2M) and you can follow me personally as well (@LBNovotechM2M).