Digitalization is transforming how businesses use data to create value throughout their ecosystems.
To many, the proliferation of SAAS companies nimbly attacking industries which once seemed secure is unfathomable. Startups are moving into the heavy-industrial operations space and churning out solutions that analyze massive sets of data to better forecast demand needs, maintenance requirements, and production schedules. General Electric, the global industrials corporation that spans across aviation, energy, and healthcare, is at the forefront of giants learning to sprint ahead of its competition through service-led growth strategies.
‘The Industrial Internet’ is shorthand for zero unplanned downtime and asset optimization.
GE has married its capabilities as a leading-edge producer of technologies across a variety of industries with significant investment in operation technology (OT) and Internet of Things (IoT) technology. The fusion of traditional manufacturing with information technology has orchestrated a fully-integrated ecosystem connecting each piece of the supply chain and its processes – from product development to maintenance. What differentiates GE’s OT from its competitors is that it’s not simply diagnostic or monitoring, but is used to proactively meet and shape customer needs in a way that revolutionizes the supply chains effected; an attempt to reverse the productivity slowdown of industrial companies from 4% to 1% between 1990 and 2015.4
GE leveraged best practices from consumer-facing internet goliaths and optimized its data through a cloud-based software platform named Predix. The outcome was high-performance analytics that GE wraps around its core offerings and could meet an untapped market need of $225 billion for industrial companies focused analytics.4 The information flow impacted by Predix is one that shifts from a myopic to a holistic perspective; instead of readouts on individual machinery, entire systems are able to create a big picture view of actionable insights.
Within Industrials, GE’s OT moves it from selling products to selling products-as-a-service (PAAS).
Below are brief case studies of how GE is changing the delivery of its products in the short- and mid-term:
Power and Utilities Business – GE’s sale of Industrial IoT enabled infrastructure to Saudi Electricity Company. Through the OT, GE products can control the distribution of power based on demand, responding dynamically to peaks to boost productivity and reduce outages as well as optimize for fuel consumption when demand is low.6
Lighting Business – GE’s 140 year old GE Lighting business has been transformed through Predix into Current, an energy business that GE recently spun off. Current was developed to sell energy-as-a-service company that delivers dispatchable energy to customers reducing waste throughout the supply chain.1
Aircraft Engine Business – GE’s aircraft engines include sensors that measure a variety of factors and send information through usage in-flight. This data is used to predict when parts require maintenance and allow customer crews to be ready with the applicable tools to reduce the in-out time of flights. Additionally, overtime GE can reduce time in meeting performance level agreements by actively evaluating maintenance demand and anticipating part replacement needs.2
Internally, GE’s innovation has produced production efficiencies resulting it reduced downtime and defects through predictive technology and dynamic machinery settings, reduced inventory surplus through demand planning powered by real-time status for parts and product replacement. Additionally, the depth and breadth of the data analyzed by Predix now helps drive granular product development changes that improve the quality and lifetime of products reducing the need for costly tests and pilots.
GE must take protective steps to protect its new business model and digital future.
As GE continues to innovate across digitalization, it must invest in technology that reduce its data storage reliance on outside parties. An example of the sheer magnitude of data being produced is that for a single jet engine, one terabyte of data is produced during the average flight.3 Across a fleet of GE planes, the network effects are unimaginable. GE’s reputation is at stake to not only maintain its ability to quickly access and analyze this industrial-scale data but also to protect the privacy of its customers. Additionally, GE should for look for opportunities to leverage best practices from its commercial financing business. With the shift from product centered sales to product and service centered sales, GE can capitalize on how to be more effective in how to show the benefits of a service oriented product to customers used to industrial purchasing processes.
As the GE moves forward with the Industrial Internet to converge the physical and digital worlds, a few open questions remain, specifically related to the scale of the data produced across GE’s product and processes. As it continues to grow its PAAS business model, how will GE react to everchanging customer expectations in terms of complexity and flexibility? And can the company continue to innovate if governments chose to step in to use the data to drive regulation related to energy efficacy and pollution?
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- GE Staying Current By Becoming An ‘As-A-Service’ Business https://diginomica.com/2016/06/17/ge-staying-current-by-becoming-an-as-a-service-business/
- How GE Could Become The Apple Of The Industrial Internet https://www.investors.com/news/how-ge-could-become-the-apple-of-the-industrial-internet/
- GE’s Big Bet On Data And Analytics http://sloanreview.mit.edu/case-study/ge-big-bet-on-data-and-analytics/
- Building the Industrial Internet With GE http://www.industryweek.com/manufacturing-leader-week/building-industrial-internet-ge
- Defining and Sizing the Industrial Internet http://wikibon.org/wiki/v/Defining_and_Sizing_the_Industrial_Internet
- Two Technology Giants Helping to Bridge the OT-IT Divide https://www.ge.com/digital/blog/two-technology-giants-helping-bridge-ot-it-divide
- The Internet of Things (IoT) in Discrete Parts Manufacturing; Paul Korzeniowski; BCC Research