All Big Data is not created equal, writes Wikibon Big Data Analyst Jeff Kelly, and Industrial Internet data is more equal than other kinds. This data, he writes in “The Industrial Internet and Big Data Analytics: Opportunities and Challenges” “holds more potential business value on a size-adjusted basis than other types of Big Data associated with the social Web. consumer Internet, and other sources.”

The reason for this is that many industry sectors have high-value assets that create a majority of this data. To illustrate his point he presents three scenarios, one each in healthcare, energy, and transportation, based on Wikibon research.

Healthcare spending in the United States topped $2.75 trillion in 2012, 17.5% of GDP, the highest spend on healthcare in the world. Analysts estimated that as much as 43% of that spend went for unnecessary procedures and administrative waste. This creates huge opportunities for analysis of Big Data from sources ranging from high-value medical equipment such as MRI or CT scanners to patients, themselves, to create major improvements. By predicting part failures on high value assets, for instance, it can maximize both availability and useful life of the asset. By monitoring low-value assets such as hand washing stations, it can ensure that basic procedures such as washing hands between patients are followed rigorously, decreasing the spread of hospital infections such as MRSA, which costs hospitals approximately $30,000 per case. And by monitoring patients themselves it can measure their compliance with home treatment plans and minimize the times they need hospitalization.

In the energy industry a study by the University of Minnesota found that power outages and “power quality disturbances” cost the United States as much as $188 bill per year. Analysis of Industrial Internet data from sensors mounted at critical points in the generating equipment and power grid can minimize those outages by moving maintenance from a break/fix to a preemptive strategy that fixes the problem before it becomes acute.

In transportation, a new Boeing 787 creates up to a Tbyte of data per round-trip.  That data can be used for everything from increasing operational efficiencies and driving preventive maintenance to keep the plane in the air to identifying weak points in engine and airframe design and designing them out of the next generation of the plane.

All the potential upside should drive fast adoption of Industrial Internet. However, Kelly writes, it isn’t quite that easy. Several challenges need to be overcome, starting with the writing of standards for the various kinds of data involved and the creation of an open platform that provides scalability, high availability, high security, flexibility, and orchestration. Regulatory requirements also need to be worked around. For instance in healthcare, HIPAA sets fairly high standards for the security and privacy of personally identifiable medical data.

However, he concludes, “the opportunities to improve efficiencies and create valuable new business models associated with the Industrial Internet are vast.” This gives all the players involved strong impetus to work together to overcome the challenges. As with all major technology advances, the successful early adopters reap the majority of the rewards, while the laggards often face shrinking market share and competitive disadvantage.