Many of these manufacturers are already taking advantage of technologies like the Internet of Things (IoT) and as we head into 2020 will find themselves early adopters of things like Artificial Intelligence (AI), 5G and 3D printing.
In a departure from past manufacturing technology adoption cycles, the focus will not be entirely on incremental improvement of existing processes.
These technologies will find their way to the core of new and innovative business models and revenue streams that will change the very nature of industrial manufacturing.
Prediction 1: 5G will have more machine than human customers
By the end of 2020 there will be more manufacturing devices connected by 5G than there will be people on 5G networks.
Bernard Marr in Forbes points out the tremendous impact 5G will have when it comes to enabling other technologies.
Streaming music, TV shows and movies in an uninterrupted way via mobile devices will indeed be easier and more affordable with 5G.
But 5G will be more transformational for devices that drive automated industrial processes than for consumer-facing smart devices.
“These advancements will enable connected cars and autonomous driving,” Marr writes.
“Smart cities with connected logistics, transport and infrastructure; enhancement in connected healthcare from robotics to blockchain use cases to wearable telemetry; industrial internet of things and smart factories; and the more extended use of augmented reality, virtual reality and mixed reality.
I predict that 5G will make its greatest impact in industrial automation.
The ultra-low-latency, will power sensors on industrial machines, enabling them to talk to each other and generate floods of data that, through machine learning, will unlock new vistas of cost savings and efficiency.
China and South Korea are already working in this way and the US and the UK are likely to spend much of the coming year ensuring they don’t get left behind.
Improved communications between machines due to 5G will not just lead to increased efficiency, but rather the ability to automate more complex manufacturing models including configure-to-order and make-to-order.
Levels of automation formerly associated only with long-run, repetitive manufacturing will now be able, thanks to the high speed of 5G, to automate multivariate production runs that may result in custom products, regional mass customization or highly configured products, all with less human involvement than is currently the case.
Prediction 2: In 2020, the B-2-B-2-C model will start to compete in earnest with the B-2-C model
The movement of manufacturers from their traditional perch at the far end of the value chain toward the consumer is underpinned by the global trend of servitization—product-oriented companies either adding services to their products or selling their products as services on a subscription basis.
As early as 2018, IFS data suggests that 62 percent of manufacturers were already benefiting from aftermarket revenue—be it through parts, warranty or proactive service contracting.
A full 16 percent of respondents were offering maintenance contracts with specific service-level agreements (SLAs), but only 4 percent of manufacturers offered products entirely as a service—full servitization.
What this means is, even if a manufacturer is selling the product through a channel of distribution, they may be supporting or servicing that product directly over its lifecycle.
The manufacturer is suddenly a business-to-business-to-consumer company.
They now have a service relationship that will drive much of their revenue and they may be responsible for delivering an outcome rather than just the product.
As an example, one of our customers is an air filter manufacturer which manufactures and sells filtration systems, historically through a standard business-to-business model.
However, through servitization, they have made the transition from selling air cleaners to selling clean air.
They work proactively with their customers to measure their existing air quality, establish an air quality goal and then maintain the filtration system to deliver that outcome.
Much of this process is automated as sensors in the equipment monitor the result and can dispatch technicians, order parts and execute on a condition-based maintenance program.
For them, however, preventative maintenance is only the beginning.
As big data manipulation and analytics becomeeasier, the opportunity to garner more information about what is happening to the air quality in particular environments will increase exponentially.
There are many other examples.
Baxi Heating, the UK leader in smart, low-carbon heating and hot water solutions (and an IFS customer), is now selling environmental temperatures to end customers rather than pallets of mechanical equipment into a distribution channel.
Its customers ask for a target temperature and Baxi will achieve this for them.
Customer experience will improve as the business-to-business-to-consumer model takes hold because there will be more direct communication between the manufacturer and the end consumer of a product.
This model will also benefit the environment as the number of items being built and resources going into them matches the requirements for a task rather than the whims of a consumer.
Prediction 3: By 2022, more than half of manufacturers will have invested in AI technology and improved productivity by over 10 percent
IFS has been working with clients to combine machine learning applications with multiple large data sets and using them to identify patterns and strategies that are beyond what the human mind is able to conceive of.
Most manufacturers already employ some level of automation—not just on the plant floor but in the front office.
Dried fruit and snack manufacturer Whitworths is a good example.
It has reached a high degree of automation in quality management, moving from period random testing of product and manual recording to a streamlined process driven directly by the shop order.
While automation streamlines processes, AI will be able to create net new processes.
So, a company like Whitworth may be able to predict quality problems before they happen, or create new AI-driven flavors to meet an individual customer’s taste, as did distiller Diageo.
Another area that will continue to develop over the coming years is AI-powered demand planning and forecasting, as I mentioned in my predictions last year.
As AIs are trained on the right data sets, manufacturers will be able to align their supply chain with demand projections to get insights that were previously unimaginable.
This in turn brings about a new mindset of the manufacturer, who is likely to only consider the manufacturing process as beginning in the factory and finishing when the goods leave the warehouse.
Just-in-time, the Toyota Production System concept, will be taken to new heights, in large part because AI allows a manufacturer to ask, “in time for what, exactly?”.
What is the event or combination of events that should trigger replenishment—a demand signal, a price drop in the component part or raw material—it could be anything and the relationship may not be apparent without AI.
In a November 2019 study from IFS, 40 percent of manufacturers said they were planning to implement AI for inventory planning and logistics, followed by production scheduling and customer relationship management, each at 36 percent.
A majority of 60 percent of total respondents said they were targeting productivity improvements with these investments.
The future will look different
2020 really should be an exciting year.
After decades of incremental productivity growth, the result of lean initiatives, automation and stern discipline, manufacturers will use technology not to optimize, but to create.
AI will let us create new ways of doing things and that means new revenue.
Photo Captions
1.) IFS Head Quarters in Sweden
2.) Antony Bourne- President IFS Industries
