We interrupt our regularly scheduled IoT blog series to bring you an extraordinary earnings report from an industrial equipment company that highlights the significant role of smart, connected products and IoTin driving services growth.
Most, if not all, companies place growing total revenue at the top of their strategic priorities. However, the industry hasn’t quite figured out how to pull it off. In fact, the TSIA Service 50, an index that tracks the 50 largest providers of technology services, has shown declines in tech revenue of $36B, or 15%, over the last 3 years.
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Source: S50-Q1 2015 readout.
GE 2015 2nd Quarter Earnings Driven by Industrial Growth and the Industrial Internet
Meanwhile, General Electric has just delivered their quarterly earnings report that beats expectations driven by their Industrial segment. They achieved organic revenue growth of 5% vs. 0% for other industrials, and GE has enough confidence in their strategy and execution that they raised the lower end of FY earnings expectations. GE made a point of calling out the contribution of what they call their “Industrial Internet”. From their earnings presentation, first half Industrial Internet orders contributed $1.9B. Total software with solutions came in at $2.4B, and they are targeting $6B for the full year. This represents over 5% of total order volume and 30% year-over-year growth.
Nicholas Heymann, an analyst at William Blair that follows GE, says that GE has found the next big thing:
"GE's software data analytics, which could become as important early next decade as GE Capital was over the last couple of decades…Predictive analytics for them is now moving way beyond their $1 trillion installed base of industrial products. In fact, they are able to ... use their predicting software to predict what's going on all around the world with virtually all industrial equipment."
So, while traditional technology spending is decreasing, the transformational roadmap laid out in B4B is leading to services growth in the most traditional of businesses – Industrial Equipment. The catalyst: use of data analytics from smart, connected products to create adoption and outcome service offers that are focused on improving customer business results.
In earlier posts, we introduced the remote services continuum as a framework to help companies navigate this industry transformation. Listed below are examples of how GE is combining smart, connected products with smart services in two, high-growth industrial segments: Aviation and Power Generation.
GE Aviation Examples Along the Remote Services Continuum
Smart, Connected Products
- Data sensors placed on airline jets collect up to 5,000 data points per second.
- Data is downloaded from an aircraft’s “tip to tail” sensors for multiple aircraft parts, components, and systems to a central data management platform for processing.
Service Efficiency
- Analytics applied to flight data provide insights into possible maintenance issues so repairs can be scheduled at optimal times to minimize impact.
Process Optimization
- Analytics applied to airport and airline data produce optimal flight patterns for safest approaches.
- Data visualization tools that represent airline traffic patterns drive recommendations for changes around crew actions or flight patterns for greater efficiencies.
Customer Outcomes
- Detailed airspace, airport, and airline operational models evaluate efficiency of historical flight operations, predict areas for improvement, and quantify potential efficiency gains. Performance based navigation (PBN) reduces track miles and dwell time for maximum fuel usage.
- Data collected from multiple sources drive condition-based maintenance (reduce unscheduled repairs), fuel savings (flight pattern optimization), and risk reduction (safer approaches), resulting in greater bottom-line profitability.
GE Power Generation Examples along the Remote Services Continuum
Smart, Connected Products
- Turbines are outfitted with data sensors that can operate at extreme temperatures, detecting multiple operational issues.
- A “one-system” central data repository and control approach extends to all equipment monitoring to enhance operations and proactive maintenance. .
Service Efficiency
- Cohesive, intuitive user interface, advanced diagnostics, and asset management tools improve operator proficiency and situational awareness.
- Effective alarm management creates the most efficient process for troubleshooting issues.
Process Optimization
- Predictive diagnostics, root-cause analysis and analytics identify issues immediately for proactive action.
- Data trends can point to operating issue that help operations make appropriate adjustments to improve heat rates up to 2%.
Customer Outcomes
- Physics-based algorithms provide early predictive warning of more than 60 different failure mechanisms. This increases the probability of early detection while decreasing false alarms that can result in costly, unnecessary downtime and lost output.
- Advanced analytic insights enable fast start-ups, rapid ramp rates with emission controls and low and efficient turn-downs, resulting in increased output and reduced fuel burn. Scheduled maintenance at opportune times ensures maximum use of turbine resources.
As the examples show, GE has moved well beyond improving the serviceability of individual products. Even though it starts with enabling a single piece of equipment, their strategy is to use data analytics generated by the entire ecosystem to enable services that drive significant customer value.
In our next post, we’ll be taking a closer look at the capabilities you will need to make a similar transformation in your business.
Read more posts in the “Intro to IoT” series: