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Kate Johnson, chief commercial officer at GE Digital, is alive to the opportunities created by exploiting data in the industrial sector, and believes all manufacturers must follow the digital transformation path or risk failure.
Her job is to oversee sales, marketing and services at the division, focused on transforming industrial firms into digital industrial companies through the use of software and data analytics – and business is thriving.
Johnson, who joined GE in 2013 from the consulting business at Oracle, is responsible for driving service revenue growth through the commercialisation of Predix, GE’s big data and analytics software platform, as the company seeks to exploit the industrial internet of things (IIoT).
In April, GE Digital introduced its first commercial application based on the Predix platform. The software, called GE Asset Performance Management, uses data and cloud-based analytics to improve the reliability and availability of industrial assets.
“Technology innovation is table stakes for the internet of things transformation,” she says. “We will need new, innovative ways to ingest and analyse mass quantities of data. Many companies are rising to this challenge – we are pleased with the plethora of new technology that is available.”
Innovative technology is one thing, but architecture is the root of successful transformation, and Predix is GE’s industrial cloud platform, purpose-built for the demanding safety and security needs of manufacturers, says Johnson.
“It’s not about the technology per se,” she adds. “It’s about the architecture. Cloud architecture is of critical importance to the digital industrial. It provides richer services at lower cost, a more agile environment in which changes can be made on the fly, and open standards to ensure flexibility down the road.”
At GE’s Grove City transportation plant in Pennsylvania, which remanufactures or repairs more than 2,000 locomotive engines each year, the goal was to connect data on disparate machines. There are six areas of focus for improvement: machine health, real-time plant floor visibility, increased responsiveness, customer reliability, analytics-based maintenance and overall equipment effectiveness.
Johnson points to successes such as unplanned downtime reduced by 20%, improved customer service and cycle time, and reduced facility costs.
However, the manufacturing sector is not known for its agility and digital transformation cannot happen overnight – a fact that Johnson is acutely aware of, despite ambitious predictions.
Jeff Immelt, CEO of GE, memorably claimed: “If you went to bed last night as an industrial company, you’re going to wake up today as a software and analytics company.”
“Every employee is affected when we digitise the industrial world”
Kate Johnson, GE Digital
Johnson acknowledges that this is a statement of intent and it is important to have such a board-level vision of digital transformation.
“Jeff is talking about the realisation of where we need to be to win in the next industrial revolution we’re going through,” she says. “GE is a 130-year-old, incredibly successful company, but we are not going to change without a mandate.”
As she points out, manufacturing is only one part of GE – design, engineering, security and operations are also fundamental, but the commitment to digital is essential.
Far-sighted manufacturers are using digital technologies to ensure they are in a competitive position in a global economy, but the reality is having to master a double life, she says.
“The trick is that the world – GE and all industrials – is dealing with two modes at one time, which Gartner calls ‘mode one’ and ‘mode two’. Mode one is the legacy architecture where long cycle development and inflexibility are the hallmarks. Mode two is cloud-based architecture that allows for speed, flexibility and agility that is the foundation of any digital industrial.
“We have to get used to living in two modes for some time. Those that can accelerate the migration to mode two will be best positioned to win.”
The digital industrial
If these modes are common to any company in any sector that is seeking digital transformation, the challenges are exacerbated in the transformation to become a digital industrial.
“This transformation is complex – we are talking about the world of really big, important things like power plants, oil fields and hospitals,” says Johnson. “These domains are complex and mission-critical, so any changes must be right or the consequences are vast.”
Her advice on the best way to succeed is to be highly focused on what outcomes you are chasing, and don’t chase too many in parallel.
“Unpack each one and get results, then chase the next one, and never underestimate the importance of people,” she says.
People, not just technology, are the foundation of getting transformation right, says Johnson.
“Changing people behaviour is critical to make all of this work,” she says. “Every employee is affected when we digitise the industrial world. The engineers will need to use operational data to change design; the operators will have to understand how a new design changes the service that is required.
“Even commercial people will need to understand how their company interacts with customers across the lifecycle if they are going to have a relevant conversation with the customer – much more preparation is required for a basic sales call.
“The opportunity is enormous, but navigating the complexity and properly managing the people side is significant.”
Running through all elements of the business is the “digital thread” that Johnson says connects all the disparate functions so, for example, feedback from machines can inform the design process.
“There is the recognition that every role changes in relation to the digital thread because of the drive towards analysis and insight,” she says. “We are helping the company to commercialise big data analysis.
“It is hugely important to articulate the role of digital for transformation to work. A company needs two things – vision and some sort of reason to change. For many industrial companies, the reason is they do not want to be left behind, as some companies were in the consumer internet space, and are no longer with us.”
Data gives tangible results
At GE Digital, a major focus has been on hiring the right people and creating a centre of excellence that connects streams of machine data to powerful analytics and people, for insights to manage assets and operations more efficiently.
“Data scientists and software engineers look at the issue on the front line and at all the data we have, to help understand what kind of outcomes we could achieve by working with the business to see the scope,” says Johnson.
The focus on data is yielding tangible results. Johnson points to an example of how data has given insight into overhauling aircraft engines, which is a major cost for airlines.
“Engines were overhauled based on the number of hours spent in the sky, but some engines had more wear and tear than others,” she says. “Operational flight data revealed that wear and tear is worse in a hot climate, so it is now possible to overhaul engines based on hours spent flying in hot, humid climates, which saves money.”
Pursuing a digital strategy also helps manufacturers maximise the efficiency of their existing assets when the markets are in turmoil and large capital investment is not an option, as is currently the case with the oil and gas industry, she says.
“There is enormous pressure to maximise the efficiency of existing assets with the complete shift in the market. No one is going to be drilling more holes any time soon and it is essential to take the cost out of the process in the oil fields as there is no more capital available. Operational technology needs to deliver the next wave of productivity.”
Customer expectations of how industrial firms deliver services is evolving. As Johnson says, when you digitise a power plant, you are not selling turbines, you are selling gigawatts of electricity at certain rates.
“The customer expects you to talk about outcomes and values – not the best widgets,” she says. “In the context of a digitised power plant, it is the most productivity at the least cost. Customers don’t want to talk about functionality; they want to talk about digitisation of the product and cost savings around it.
“When you design a piece of equipment, you can operate it differently according to what you learn and analyse in real time, not with hindsight.”
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Customers such as franking machine manufacturer Pitney Bowes are reaping the benefits of Predix applications. The challenge was to solve unplanned machine downtime, which was up to 20%.
Digital intelligence meant putting sensors in place for asset health visibility via real-time connectivity and the cloud, so that delays that incurred fines were dramatically reduced.
Predix applications improved machine efficiency at Pitney Bowes by up to 10%, increased machine yield by up to 20%, reduced call-centre activity by up to 20%, generated up to 15% savings on parts replacement and sparked an unprecedented improvement in customer satisfaction.
“In manufacturing, there is a cascade effect by improving machine efficiency, which has a positive impact on customer loyalty,” says Johnson. “But you can only do this with connectivity: mechanics, material and labour must all be connected.
“You have to have visibility of interactions in order to get to the nirvana of enterprise visibility, where you can truly meet and exceed customer expectations.”
Embracing digital industrial
GE Digital is showing what can be achieved by embracing digital industrial, but Johnson says others can follow if they have clear goals and a logical approach to achieve enterprise visibility.
Customer demand is hard to see and it is difficult to know how to allocate resources, but when you get to the level of having digital direct outcomes, by connecting machines to location pools, you can change what and when you manufacture, says Johnson.
Her advice to manufacturers is to be clear about the desired goals on their digital journey. “Break the problem down and be very clear of the outcome you’re chasing,” she says. “Standardise your approach.”
A simple approach starts by connecting to machines, materials, and people first, says Johnson.
“Move on to really analysing the data until you get actionable insights. Then move on to optimising your environment by actioning the insights. And then connect more.”