Simon Jacobson
The Internet of Things (IoT) is gaining plenty of hype as a game-changing way of thinking for every industry. Those in the manufacturing space view it as a revolution, offering significant improvements to manufacturing processes as a way of making productions more efficient, agile and flexible. But is this all for real? Manufacturing business leaders will want to know which business applications within Internet of Things (IoT) are having the most impact and find the proof points that these applications can deliver on the value they promise. So to what extent are manufacturing organizations adopting these solutions and approaches, how have they been able to handle added complexity, where are they finding ROI, and is this new paradigm currently feasible and cost effective for most industry players?
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Sanjog Aul [00:00:00]:
Welcome, listeners. This is Sanjog Aul, your host, and the topic for today’s conversation is What The Internet Of Things Means For Manufacturing, and I have with me Simon Jacobson. Simon is the research Vice President with Gartner. Hello, Simon. Thank you for joining us.
Simon Jacobson [00:00:16]:
Thank you. Happy to be here.
Sanjog Aul [00:00:17]:
So everyone is talking about the Internet of things and it’s a big topic with a lot of exciting possibilities, but we wanted to zone in on one industry today and that’s manufacturing. We want to find out what are some of the challenges coming up and which applications are making the most impact and the evidence out there to show this is a game changer. So Simon, as a first question, there’s a lot of hype, as we know is surrounding the Internet of things overall, but what is that specifically considered as exciting and revolutionary? And to that since we are talking in context of manufacturing, what are the manufacturer’s goals?
Simon Jacobson [00:00:57]:
That’s a great question because I agree there’s a lot of hype, but there’s
Simon Jacobson [00:01:01]:
also a lot of opportunity.
Simon Jacobson [00:01:03]:
Our own forecast data at Gartner really
Simon Jacobson [00:01:06]:
looks at some of the real positive
Simon Jacobson [00:01:07]:
economic impact, which is estimated at over 1 trillion. So you think it’s definitely going to
Simon Jacobson [00:01:12]:
be substantial, it’s going to have impact,
Simon Jacobson [00:01:14]:
but when it comes to manufacturing, there’s
Simon Jacobson [00:01:17]:
a bit of a different plant we have to look at here,
Simon Jacobson [00:01:19]:
and it’s part of the bigger picture.
Simon Jacobson [00:01:21]:
If we take a step back and
Simon Jacobson [00:01:22]:
look at the term digital manufacturing, you’ll see it’s been around for eons. However, has it really lived up to its expectation though? Over the past eight to 12 months, I’ve been working with several of our clients and also moderating multiple roundtables on the topic, and each instance, it’s very clear that the original definition of digital manufacturing, that is the usage of digital model to validate factory design and manufacturing processes, has not even lived up to a sniff of its original expectations. So when we look at this bigger picture of digitization and digitalization of the business as a whole, or the boundaries between the digital and physical worlds are blurring and the people, the businesses and
Simon Jacobson [00:02:05]:
the things in and across factory and
Simon Jacobson [00:02:07]:
company boundaries are equally as blurring, there
Simon Jacobson [00:02:10]:
is opportunity massive for CIO’s, but also for manufacturing strategists to use the Internet of things, to use big data, to use cloud computing, to really redefine and transform the role that production plays in the value chain. The challenge though, and where things will become dicey, especially for the office of the CIO, is the pace at which this is happening.
Simon Jacobson [00:02:31]:
Business and technology innovation are concurrently accelerating in manufacturing, whether it’s through connected products,
Simon Jacobson [00:02:37]:
whether it’s through new business designs. As an example, there’s one organization who
Simon Jacobson [00:02:42]:
is producing very sophisticated products where the products themselves are going to come down the assembly line and dictate how they’re going to be assembled to the equipment. This is massive. In the past, manufacturers have had a
Simon Jacobson [00:02:55]:
luxury of adopting technology at a pace
Simon Jacobson [00:02:57]:
comfortable for them, but that is significantly changing. So for the CIO and the CIO’s direct report, understanding how to in a
Simon Jacobson [00:03:04]:
very competitive environment, change the wheels on moving buck, so to speak is going
Simon Jacobson [00:03:08]:
to be an issue.
Sanjog Aul [00:03:10]:
So Simon, if M2M communication already exists and sensors and big data are already being implemented within the organization, how do the broader applications as part of IoT make an impact on the whole?
Simon Jacobson [00:03:23]:
Here at some of the technologies exist today and the question we ask about that is really what’s new,
Simon Jacobson [00:03:29]:
but also have the technologies really been leveraged to the fullest,
Simon Jacobson [00:03:33]:
bnd communication, tags and sensors, those are all coming down in cost of the barrier to entry for an organization to the participate in the Internet of things is definitely being lowered. That said for a pure IT perspective, it’s not just the way that we’re capturing the data, but also the way
Simon Jacobson [00:03:51]:
that the data is managed. Which yes, big data comes into this,
Simon Jacobson [00:03:55]:
but the reality is the term big
Simon Jacobson [00:03:57]:
data and manufacturing is a big data.
Simon Jacobson [00:04:00]:
Manufacturing environments already are producing extremely large volumes of information. This is where processed data is stored in have been used for years. So if anything, it’s more of how to put context around the information in the system. What do we understand and what do we do with it.
Simon Jacobson [00:04:18]:
If there are machines and sensors that fit into the context of a process or into a larger system, that’s nice, but is that important? Not always, but for organizations, the big thing here when looking at these technologies is how to create the appropriate system that maps
Simon Jacobson [00:04:33]:
to the end to end process, and now with the proliferation of data and information, the real change is we can now use external information to start to create these models and determine what the appropriate outcome for the business is going to be versus perhaps doing things
Simon Jacobson [00:04:48]:
at a later date or when risk has already happened.
Sanjog Aul [00:04:50]:
So why does this actually matter? Or why should this matter at all to the manufacturing CIO or business leaders?
Simon Jacobson [00:04:57]:
It matters because if we look at
Simon Jacobson [00:04:59]:
the overall macro trends in manufacturing, where we have more increasingly connected products with
Simon Jacobson [00:05:05]:
decentralized or localized factory networks, each must
Simon Jacobson [00:05:09]:
be optimized frequently to produce a customized
Simon Jacobson [00:05:12]:
product at a higher velocity in a much more sustainable fashion. What we’ve seen is a lot of
Simon Jacobson [00:05:17]:
movement towards individualization or mass customization, and if you’re going to do this in manufacturing, you still have to maintain alignment with your supply management or logistics functions as well as with your partners to ensure that all service levels are maintained, and for example, the organizations that are starting to pilot a ability for a consumer to go online and configure their own label, have it put on a can of deodorant or on shampoo and
Simon Jacobson [00:05:42]:
go pick it up later that day at a depot, means that I have
Simon Jacobson [00:05:45]:
to have knowledge of my processes and optimization of my processes at a hyper level, not just simply understanding at week’s end or at the end of a shift when I need to make adjustments and improve.
Sanjog Aul [00:05:57]:
Now, to what extent are organizations already adopting some of the business applications being offered on the road to this Internet of things? And what are some of the challenges that are coming up related to cost people, technology and security?
Simon Jacobson [00:06:11]:
I’ll be very quick in terms of the business applications because analytical applications that
Simon Jacobson [00:06:17]:
you would find under the enterprise manufacturing intelligence or EMI market or manufacturing execution systems are not new. Sensor networks and tags are not necessarily new either. In fact, what we are seeing is maybe a renaissance or a revisitation investments in industrial automation, but the bigger challenge that is going
Simon Jacobson [00:06:37]:
to have to happen here is how manufacturers want repeatability and meaning concepts with the paradox of agility, digitalization and constant change that is critical in today’s market environment, and with that we’re going to see some different challenges that we wouldn’t have seen in the past, which are really much more organizational and perhaps security oriented, and I want to take on the security one as this is very important for manufacturing and the Internet of things, and in fact they come back to
Simon Jacobson [00:07:03]:
that ITOT discussion if you consider this scenario where valve motors and other devices
Simon Jacobson [00:07:08]:
in a production facility are monitored and
Simon Jacobson [00:07:10]:
controlled by purpose built automation control systems. While these systems are really built on
Simon Jacobson [00:07:16]:
building blocks like standard IT technology, they also incorporate significantly large proprietary elements.
Simon Jacobson [00:07:21]:
So it’s not just physically securing the facilities. So security will be complex, it’s how to use a blend of approaches from mobile and cloud based architectures with this
Simon Jacobson [00:07:31]:
industrial control and automation of physical security to make sure that information and processes are managed, and this comes back to, especially in the manufacturing environment, some of the skill
Simon Jacobson [00:07:41]:
sets are going to have to be required here.
Simon Jacobson [00:07:43]:
This cultural divide that has existed between the engineers and the process control teams
Simon Jacobson [00:07:48]:
that have long been associated with OT and the IT team that are now coming in and managing the manufacturing environment means really bringing together teams that have had different approaches to security, and these combined staffs are going to have to work together to develop architecture, governance and compliance. The other things you’re going to see
Simon Jacobson [00:08:07]:
here besides this is just on a pure itot level, just the necessary ways that organizations are going to have to come together.
Simon Jacobson [00:08:14]:
The engineering skill sets are at a premium. So how do I take that knowledge or those subject matter experts that reside within individual site, get them to interact and intersect with the IT teams and scale that across the manufacturing network.
Simon Jacobson [00:08:28]:
The other challenges you’re going to start to see is really looking at some
Simon Jacobson [00:08:31]:
of the future generation of technologies. How will smart machines and cognitive computing enhance or support exist skills,
Simon Jacobson [00:08:38]:
and of course the last thing I would bring up here is really convincing the vice president of manufacturing or the manufacturing leadership that it is more than
Simon Jacobson [00:08:46]:
just a necessary evil that really has to be overcome. A lot of the vice president of
Simon Jacobson [00:08:51]:
manufacturing or business leadership of manufacturing that I work with tell me that I
Simon Jacobson [00:08:56]:
need to learn about the value of
Simon Jacobson [00:08:57]:
these technology beyond the buzzword and how do I do this without compromising at
Simon Jacobson [00:09:01]:
the utilization, quality or margin.
Simon Jacobson [00:09:03]:
For example, I mentioned big data,
Simon Jacobson [00:09:05]:
manufacturing operations have generated big data before
Simon Jacobson [00:09:08]:
it was a term.
Simon Jacobson [00:09:09]:
What does it really mean and what
Simon Jacobson [00:09:10]:
is the value of it?
Simon Jacobson [00:09:11]:
And once that value is understood and
Simon Jacobson [00:09:13]:
people start to experiment, we’ll then start
Simon Jacobson [00:09:15]:
to see perhaps a bit more of
Simon Jacobson [00:09:17]:
an uptick in more wholesale deployment or
Simon Jacobson [00:09:20]:
wider scale projects within the Internet of things.
Sanjog Aul [00:09:23]:
So what types of manufacturing organizations are adopting this the most?
Simon Jacobson [00:09:27]:
There’s going to be significant differences between industry orientation, industry industries where there is
Simon Jacobson [00:09:33]:
a high amount of very complex bills of material and complex assemblies and sub assemblies that have been digitalized for quite
Simon Jacobson [00:09:40]:
some time, or at least are increasingly digitalized.
Simon Jacobson [00:09:43]:
You’re going to see much more of
Simon Jacobson [00:09:44]:
focus here on the connected products and how to ensure that there’s going to be a different orientation of producing these
Simon Jacobson [00:09:51]:
products, ensuring there’s a more concurrent feedback loop from the market or from the production process to how these products are designed. In the process industries where you tend to run the app that’s a bit more all out, you’re going to see a higher premium being placed on things like reliability, ensuring that the assets are available in there, and it does open up the door for some of the predictive maintenance or reliability centered maintenance discussions, but more importantly in those industries it’s also going to be how to access the information to ensure how to optimize the process and perhaps produce the highest
Simon Jacobson [00:10:23]:
quality and cost product at the lowest cost to the organization.
Sanjog Aul [00:10:28]:
This is a great segue because I was just about to ask you which IoT enabled business applications such as predictive maintenance are currently making the most impact in the manufacturing industry and where are the manufacturers finding the most ROI?
Simon Jacobson [00:10:42]:
In most cases the ROI itself is going to be from pure visibility into process performance.
Simon Jacobson [00:10:48]:
If you look at the majority of
Simon Jacobson [00:10:49]:
manufacturing environment, there has always been some form of automation and control.
Simon Jacobson [00:10:55]:
Whether or not that pocket of automation or those silos are connected from an end to end perspective. For example, I might as a CNC
Simon Jacobson [00:11:03]:
device or a lathe that I use, but that’s really not connected to the factory network. So I have no idea of whether
Simon Jacobson [00:11:09]:
or not my tolerances or my processes are in control, what my process capabilities are, while a packaging line is much more
Simon Jacobson [00:11:16]:
automated and I will know what the efficiencies are, being able to connect those dots and derive context of how processes they’re performing
Simon Jacobson [00:11:24]:
is absolutely going to be where the ROI is coming from. So predictive maintenance is definitely something that
Simon Jacobson [00:11:29]:
will have an impact, and that falls into something I’d say of a bigger concept that Gartner’s research around asset performance management, which is really encompassing the capabilities of data capture, integration,
Simon Jacobson [00:11:41]:
visualization, analytics that are all bound together with the explicit purpose of really optimizing asset performance and driving that availability.
Simon Jacobson [00:11:50]:
This does not obviate the need for in some cases investments in manufacturing execution
Simon Jacobson [00:11:55]:
systems or even a pure physical process control software.
Sanjog Aul [00:11:59]:
The claim is that by the way of intelligent capture and analysis of data in the field, IoT will help with downtime minimization, pricing optimization and yield management among others, but do we have enough existing proof that these claims are accurate or are they just hype so far?
Simon Jacobson [00:12:16]:
I would definitely say these claims are accurate, but let’s look at this to the appropriate lens.
Simon Jacobson [00:12:21]:
Going back to 2001 and 2002, the term enterprise manufacturing intelligence came to be back then and that really focused on the ability to use information technology to distill specific KPIs that are generated from
Simon Jacobson [00:12:36]:
multiple data points gathered within a factory or production process, and a lot of that helped organizations within specific pocket or by asset individually minimize downtime or optimize yield. The challenge that organizations have now is tying this all together. So the ROI and the value is still there and there is proof, but with that in mind, you have to look at how this is going to tie to manufacturing ability to be evaluated. So the ROI statements and the value is going to change.
Simon Jacobson [00:13:04]:
The big thing that’s going to change
Simon Jacobson [00:13:06]:
this is how the data is collected across multiple stages of production to drive a level of transparency. This is going to enhance product process
Simon Jacobson [00:13:14]:
visibility, knowledge and process understanding, which will in turn impact downtime and asset management.
Simon Jacobson [00:13:21]:
It will impact the ability to do dynamic pricing, but also drive quality improvements.
Simon Jacobson [00:13:27]:
That is so this end to end view, if anything, is going to integrate the execution capabilities of production with the broader supply chain, and that’s going to have a specific outcome to the business of increased flexibility, improved process capabilities, as well as the continuous optimization of production rates and the locations that products are produced at. This in turn will help meet changes in demand and different product designs, while giving the business a level of agility
Simon Jacobson [00:13:53]:
to respond to other externalities. This means that some measures of product quality can be refocused and the subsequent cost savings added back into the business or to its external suppliers and partners. The savings can also be driven into
Simon Jacobson [00:14:05]:
other value added processes inconsistently aligned with varying customer segment. Absolutely, they’re going to be significant value
Simon Jacobson [00:14:13]:
here in the Internet of things really going to tie in more information to these problems.
Sanjog Aul [00:14:17]:
Predictive maintenance is an application that OEMs could actually package into their products. If you look at it in this way, it could be a revenue generating opportunity. So are there any other examples of opportunities like this who is also going to most benefit or profit out of the usage of such business applications? Let’s talk about this when we come back from the break. Please stay tuned listeners.
Speaker E [00:14:40]:
Bosch Software Innovations is proud to sponsor this program. Visit bosch-si.com connectedmanufacturing to find out how Bosch can help you improve your operational performance and become a manufacturing industry leader in a connected world. Change the way you predict, manage and produce outcomes. Bosch Connected Manufacturing. You are listening to CIO Talk Radio Analyst Corner.
Sanjog Aul [00:15:06]:
Welcome back. So let’s explore this area. Simon, you’re talking about predictive maintenance as an application which OEMs could actually package into their products. What about other types of applications? What kind of opportunities that are existing which could actually help generate revenue?
Simon Jacobson [00:15:21]:
Predictive maintenance in and of itself is
Simon Jacobson [00:15:23]:
there’s a lot of money to be made with the assets. As I mentioned earlier, there’s a bigger concept here of appetite performance management as
Simon Jacobson [00:15:31]:
reliability of athletes is being played to a higher premium these days, and as I mentioned, we’ve defined asset performance management as really the data capture, integration and analysis of information of specific assets to drive availability, minimize costs and reduce other operational risks,
Simon Jacobson [00:15:48]:
and this includes different but often complementary practices like condition based maintenance, predictive forecasting, risk based maintenance, as well as it’s also historically resided in the shadows of enterprise asset management, but being put a bit more to the forefront as reliability is further prioritized,
Simon Jacobson [00:16:05]:
and quite frankly, there already are folks generating revenue in doing this. If you were to look at the aircraft engine business in particular, where the large OEMs would sell hour by the
Simon Jacobson [00:16:15]:
hour or performance based logistics contracts on top of the app that what they’re guarantees is uptime,
Simon Jacobson [00:16:21]:
and when you guarantee these kind of outcomes to the customer, you have to look at this from two different perspectives.
Simon Jacobson [00:16:27]:
How I monetize this, but also how
Simon Jacobson [00:16:29]:
my customer monetizes it, and this is where vendors like GE, vendors like ThingWorx, who have been since acquired by PTC, Honeywell and Rockwell Automation, just to name a few, have built offerings Both for their OEMs but also for the customers directly. This really opens up the bigger question
Simon Jacobson [00:16:46]:
and the bigger issue. It’s not exactly how companies individually are going to benefit. It’s more of who’s going to profit
Simon Jacobson [00:16:53]:
from the usage of the application as part of a broader digital business scenario which is really around joint value creation
Simon Jacobson [00:17:00]:
where everyone’s making money and you’re not just saving a dollar here to spend $20 there, that have to be adrift,
Simon Jacobson [00:17:07]:
and that’s part of the whole collaboration
Simon Jacobson [00:17:08]:
aspect that asset performance management encompasses.
Sanjog Aul [00:17:11]:
Now an interconnected enterprises will likewise make the supplier and value chain network increasingly more complex. Have manufacturers been able to handle that new level of complexity in order to see the benefits of a connected enterprises? What do you think? What challenges are still remaining?
Simon Jacobson [00:17:28]:
There’s a significant amount of challenges here. First of all, complexity is not going
Simon Jacobson [00:17:34]:
to be tamed anytime soon. You asked about firing value chain network. Let’s also look at the complexity of product portfolios. There are several consumer products companies we’re
Simon Jacobson [00:17:43]:
working with who are trying to remove
Simon Jacobson [00:17:44]:
the amount of SKUs or stock keeping
Simon Jacobson [00:17:46]:
units that they have. You start to look at the aftermarket
Simon Jacobson [00:17:49]:
and trying to understand the demand, especially
Simon Jacobson [00:17:51]:
on the discrete side of the world or specific specific spare parts and how
Simon Jacobson [00:17:54]:
to forecast and build that so that the complexity is mounting. What manufacturers have to think about in order to see the benefits is really coming back to some of the basics, and this is why I like to ask clients the question of if you
Simon Jacobson [00:18:06]:
were to build a manufacturing company from the ground up, what would you need? And really what it comes back to is a couple of basic pillars.
Simon Jacobson [00:18:13]:
The first being the pure production system of codified and standard work and best practices that is going to evolve and be continually improved on over time. That way as change it to the business as an manufacturing can adapt. The second thesis going to be very how I manage my information. In some cases the need to manage product data like such as built in material. In other cases the active data and
Simon Jacobson [00:18:36]:
what you find for a lot of organizations in this case is the whole
Simon Jacobson [00:18:39]:
paradigm of manufacturing systems architecture has to be flipped upside down. We continue to perpetuate architectures that make data go to the applications, when in reality you have to start looking at applications that go to the data, and to do that, different delivery models, both from a deployment and pricing perspective need to shift.
Simon Jacobson [00:18:57]:
But also in this connected world and
Simon Jacobson [00:18:59]:
this complexity has to be a tighter
Simon Jacobson [00:19:01]:
effort on some of the information standards as well.
Sanjog Aul [00:19:03]:
Now, what’s the current market like for an IoT enabled manufacturing transformation? How effectively are providers able to help manufacturers fully leverage it and see IoT’s full potential?
Simon Jacobson [00:19:15]:
I would be very careful in claiming
Simon Jacobson [00:19:18]:
an IoT enabled or Internet of things enabled manufacturing transformation. When we look at manufacturing transformation as a whole, performance maturity of a company or individual division, depending on the organizational structure has to be taken into account.
Simon Jacobson [00:19:33]:
This is where a lot of organizations will struggle. In mature businesses where manufacturing operations are integrated with end to end supply chain, these approaches are going to start to take root. Leaders are able to transition manufacturing from a cost center asset and capability to a brand enabler,
Simon Jacobson [00:19:51]:
and they’re going to be able to connect with different value chain partners in
Simon Jacobson [00:19:55]:
their products to do so. A lot of manufacturers work so hard to optimize for today’s business environment and they’re going to struggle to successfully capitalize and they risk missing the opportunity that’s happening now and they’re going to end up playing catch up. This means from an IT perspective, and this is where I’m cautious around an
Simon Jacobson [00:20:12]:
IT driven manufacturing transformation.
Simon Jacobson [00:20:14]:
Yet while manufacturing environments generate a large amount of data and the term big
Simon Jacobson [00:20:18]:
data might not be new, the reality
Simon Jacobson [00:20:20]:
is though, a lot of these advances in technologies are also going to unmatch how deeply entrenched many factories are in
Simon Jacobson [00:20:28]:
what we’ll call a spreadsheet of things. Instead of being prone to reaping your rewards and uncomfortably high, majority of manufacturers still rely on paper, manual data capture and in many cases microsoft excel or information gathering analysis, and those instances you have to really digitize some processes before you can really drive an Internet of things.
Simon Jacobson [00:20:49]:
So what I see a lot of organizations starting to think about is let’s look internally, understand that the Internet of things doesn’t always have to be on the Internet.
Simon Jacobson [00:20:57]:
Maybe we also start to develop an intranet of things.
Simon Jacobson [00:20:59]:
That way, before manufacturers can start to
Simon Jacobson [00:21:02]:
think about multiple processes with the PI point, they can start to connect the dots within their own houses, so to speak.
Sanjog Aul [00:21:08]:
Which applications which may be difficult to integrate into today’s processes will be the most profitable and promising moving forward into the future.
Simon Jacobson [00:21:18]:
Not going to be one killer application
Simon Jacobson [00:21:20]:
there’s a lot of moving parts within the Internet of things, and when you put it in the industrial context, you have multiple moving parts because of the heterogeneous set of systems that live within every factory. So we’re going to have to look at this from a broader architecture where
Simon Jacobson [00:21:34]:
different classes of applications have to be considered.
Simon Jacobson [00:21:37]:
Whether it’s the large industrial automation providers like the GEs, the rockwells and the schneider electric of the world. Whether it’s the PLM providers who are going to help with some of the concurrent management of quantum process designs, folks like siemens and PTT, but then there’s also the entire security aspect of this, where Cisco will definitely have an impact. So we’re starting to see that multiple players sit on this landscape and this doesn’t obviate the need for traditional manufacturing intelligence or manufacturing execution systems.
Simon Jacobson [00:22:07]:
The question is going to be is how companies put together the appropriate architecture
Simon Jacobson [00:22:11]:
and how the application provider start to put together a reasonable level of open standard for everyone to adopt. The interoperability in the flow of information becomes much more streamlined and seamless. That way we can start to see things like an app store similar to iTunes for manufacturing.
Sanjog Aul [00:22:27]:
Once again, thank you Simon, for sharing your thoughts and insights on our analyst corner segment. My pleasure and listeners. I invite you to find more conversations about the Internet of things and manufacturing as part of our series@ ciotalkradio.com/Connectedmanufacturing.
