Covering Disruptive Technology Powering Business in The Digital Age

Everywhere we look, machines are getting smarter and more connected to our lives. Starting from simple activity-tracking wearables such as Fitbit, all the way to airlines tracking fuel efficiencies, the Internet of Things, or IoT as we often call it, offers enormous potential for the way we live, travel, and operate businesses.

Predictions on the growth of IoT in next few years are mind-boggling. A major industry analyst firm forecasts that 6.4 billion connected things will be in use worldwide in 2016, up 30 percent from 2015, and growing to 20.8 billion devices by 2020. To add perspective, the World Bank forecasts that there will be approximately 7.7 billion people in 2020. That translates to nearly three connected ‘things’ for every person.

In this rapidly growing world of IoT, Master Data Management (MDM) has an enormous role to play in making sense of the data. To better understand how these two technologies can bring immense value to organizations, let’s examine some interesting use cases within the aviation industry.

We are seeing a massive uptake of IoT in the airline sector, where companies exploit real-time sensor data to increase aircraft usage and reduce operating costs, resulting in bottom-line operational savings of $30 – 50 million over a five-year term.

In this interview with Knowledge@Wharton, Sokwoo Rhee, associate director of the Cyber-Physical Systems Program at the National Institute of Standards and Technology, sheds clear light on how companies such as GE are transforming their business model. Instead of selling jet engines at a single price, GE now is changing to a subscription model where they give engines away for free but charge a monthly or annual usage fee. If anything goes wrong, they will come in and replace the engine.

To make this model work, Sokwoo says, GE has to know exactly when its engine will fail. If they replace it too early, they risk leaving money on the table because the engine could have produced more revenue. And, if they wait too long, a disastrous situation can happen. So GE uses sensor data, combined with big data analytics, to predict exactly when a failure is likely to occur. By doing this, GE can fix issues before they happen and replace engines just before their breaking points.

Master data management is critical to achieving these analytic and predictive insights. Recently, I spoke to an IT leader at an aviation company. This organization masters its asset information in Informatica MDM so they can unlock the power of their IoT initiatives. As the “glue” that links machine analytics with enterprise data, MDM provides the business-critical asset profile, asset service history, and customer information they need to understand the complete picture. With MDM specifying the context for IoT data, they’ve built a platform that allows them to predict future machine performance. These insights will help prevent unplanned outages and machine failures as well as optimize maintenance, resulting in significant savings and increased productivity.

For an industry that operates on tight margins, small improvements in aviation can have huge profit implications. Whether it is shaving minutes from flight turnaround times or optimizing engine performance and fuel efficiency, these are the kind of improvements that enhance the customer experience and result in cold, hard-cost savings. To put this into perspective, a 1% decrease in fuel cost could translate to $30 billion of savings for the industry over 15 years. However, to make sense of all of that data spewing out of sensor devices and meters, these companies need to understand thecontext.

Just as MDM provides the contextual glue for the airline industry, it can be integrated with virtually any IoT use case to fuel clean, consistent, and connected information about your company’s business-critical data. This IoT-MDM combo lets you create a complete, comprehensive data picture, which can lead to substantial benefits in the form of cost savings, reduced energy consumption, improved efficiency, and more.

This article was originally published computerworld.com and can be viewed in full here

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