I just read CapGemini’s Smart factories @ scale report. Some of the numbers in it caught my eye.
The report is good and the methodology seems solid. And yet I believe that with such self-reported research, we need to take the findings with a grain of salt. I will be doing some critical analysis in this post.
However, here’s a disclaimer. In recent years, I’ve been investing a large portion of my time convincing manufacturers that a modern, flexible, modular and scalable MES (Manufacturing Execution System) is the essential backbone of a successful smart manufacturing transformation. So, while some may find this analysis biased, I have researched data points confirming this theory.
#1 – MES is #1 in perceived benefit potential
One of the data points I immediately seized on is in the graphic. It indicates that executives understand MES has the potential to deliver benefits. It is also one of the most widely implemented of the technologies included in this report.
#2 – 1000 respondents above $1 billion
The survey included 1,000 manufacturers, all with annual revenues above $1 billion. This data point alone shows that many larger companies are pursuing Smart Manufacturing. The future is exciting for anyone working in this area.
Details: 46% of respondents have annual revenues between $1 billion and $5 billion, 37% between $5 billion and $10 billion and 17% above $10 billion.
#3 – $4.4 billion market in 2019
“The market for Smart Manufacturing platforms alone stands at $4.4bn in 2019 and is expected to grow at a CAGR of 20% over the next five years.” They cite this from a MarketsAndMarkets forecast report.
Every day I get an e-mail about a new report forecasting a huge growth in Smart Manufacturing, manufacturing software, MES, IoT, etc. I have significant doubts about such specific numbers. Yet our experience is also that manufacturers are investing.
#4 – Investing 3.24% of revenues next 3 years
This is a huge number. If we do a very conservative estimate of the revenue figures of the respondents, by considering their revenues are in the lower limit of the interval, we get that the average size is $4.1B. This means that the 3.24% that the 1000 respondents will invest annually in smart manufacturing translates into approximately $130B per year.
This number also compares with the 1.7% of revenues these companies invested on average over the past 3 years. Why would investment double suddenly, some 8 to 9 years after the original German Industry 4.0 program was created? I’m guessing this reflects respondents’ excitement about this topic and the benefits that it will bring.
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#5 – 68% have ongoing initiatives
68% of respondents have ongoing Smart Manufacturing initiatives. This number increased from 43% in 2017.
The report says there are three key technologies involved in “smart”: connectivity (leveraging IoT); intelligent automation (e.g., advanced robotics, machine vision, distributed control, drones); and cloud-scale data management and analytics (e.g., implementing predictive analytics/AI).
By this definition, most factories can be called smart.
A) Connectivity is not new, and manufacturers frequently call their sensor data exposed via PLCs or other interfaces IoT.
B) Intelligent automation seems new, but “machine vision,” for instance, is a technology that I used when I started working in 1996…
C) Cloud-scale analytics… This is vague. If on-premises big data solutions and analytics without AI models are included, and the actual scale is not specified, companies all have analytics.
#6 – 30% have made their factories smart (!)
“Organizations have, on average, made 30% of their factories smart”. With the definition of what smart means in #5, this number is meaningless.
Yet the report adds also refers to the main characteristic of a smart factory being the “’closed-loop,’ data-driven optimization of end-to-end operations.” This is far harder. The site must use connectivity, intelligent automation and data management and analytics to analyze, and then through decision support, actually improve end-to-end operations. This is the ultimate goal. But 30% doing this today seems extremely farfetched and contradicted by some of the next data points.
#7 – 14% succeed
This is where the promises are hitting the wall of reality. According to the report, only 14% call their smart factory initiatives a success. Nearly 60% say their initiatives “are either struggling or that it is too early to comment.”
If of the 68% of companies with ongoing Smart Manufacturing initiatives, 60% have not (yet) realized the benefits, only 8% did. If 30% are already smart factories, then 22% of the smart factories have not yet realized their benefits! To me, this means that 22% are not really “smart”!
So, the million-dollar (or in this case billion-dollar) question is: why are Smart Manufacturing initiatives not paying off?
#8 – 62% have no MES/SCADA
I believe this is the answer to the million-dollar question. Nearly two-thirds lack MES – the software layer that controls the process at the factory level.
Yet it appears not to be the focus of many Smart Manufacturing initiatives. 38% using MES is a very small delta of additional MES implementations as part of Smart Manufacturing initiatives vs. previous research over the past decade that consistently shows MES is used by 30% or more.
On the other hand, newer technologies such as industrial IoT systems (32%), robotics/cobotics (32%), analytics and AI (31%), plant digital twins (24%), AR/VR (22%) are likely to having been applied only recently.
So, what does this mean? It means that many manufacturers’ Smart Manufacturing initiatives are adding new technologies without the base systems in place. Without systems such as PLM or MES to control processes and put data into context, the initiatives fall short of their promises.
#9 – 51% say technology implementation is a challenge
We fear that many companies are entering these initiatives not only without a solid technology base, but also with skewed expectations.
This becomes clear in a statement from Martin Widsing, senior manager – Virtual Methods and IT at Volvo Cars. “The biggest struggle is that there are no products and platforms available, ready to use, that we can simply purchase, implement, and then start using.”
This makes Smart Manufacturing sound like just adding a new technology. However, companies cannot jump past overall strategy for digitalization and years of progressive maturity steps.
#10 –- $1.5 trillion to $2.2 trillion add to GDP
According to the report, the estimated productivity gains from Smart Manufacturing will add something between $1.5 trillion and $2.2 trillion to the global GDP. The number is staggering, but the methodology looks quite solid.
Researchers derive it from the expected target productivity gains for each smart factory and from all gains from existing initiatives, with these coming both from “efficiency by design and operational excellence”. This is then factored on the current value-add contribution that manufacturing makes to global GDP.
There is huge enthusiasm around Smart Manufacturing and Industry 4.0 technologies and approaches. The potential benefit to companies and the global economy is enormous. Yet if not done properly, manufacturers will continue to invest significant amounts and struggle to realize the huge potential offered by smart factories.
For now, the most important take-away is: without a well-defined strategy revolving around enterprise systems that can act as the core, properly defined and implemented, the likelihood of success is very slim… no matter how much money companies throw at the problem.
CapGemini’s Smart factories @ scale is publicly available for download here: https://www.capgemini.com/research/smart-factories-at-scale/ This 40+ page report is full of charts and infographics, and with lots of food for thought.
I have shared my thoughts. I hope you will share yours with me too!
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