Many manufacturers depend on a Content Management System (CMS), but for product support, the results have been, in the words of one manufacturing executive, “less than spectacular.” It turns out that CMS portals aren’t very effective for gathering and organizing information and feedback about service and support, behaving more like a dumping ground for all things service-related, which results in unmet expectations for customer support and field service.

The Challenges With IoT and CMS Portals

Why CMS Portals Aren’t Effective

The success of any CMS is directly related to the quality and utility of the data, including descriptions of components, problems, repair procedures, etc., without which product support search results are either too general (giving too many hits) or too specific (overlooking key documents and pieces of information). Making matters worse, if the information in a CMS portal is out of date, waiting for Engineering to approve the latest parts and service procedures and for service technicians to enter their notes, the portal quickly develops a reputation as being unreliable. The result is wasted time and higher costs as service/ support personnel overlook important clues and follow wrong procedures for diagnosis and repair.

The Downfall of IoT Data

To address problems with CMS portals, many manufacturers are attracted to the newly-named Internet of Things (IoT) as a cure-all for product support challenges. (Ten years ago we called it telematics, but I digress.) The hype around IoT is that diagnostic data from connected machines will solve everything from unscheduled downtime to predictive, prescriptive and condition-based maintenance. The idea is that once the diagnostic data has identified a problem the company’s CMS portal will supply information about parts procurement and repair procedures.

Unfortunately, the promise of IoT rests on a number of assumptions, about diagnostic data and CMS portals, that have often proven to be false. For example, finding patterns and (apparent) correlations in the data is not the same as finding failure modes (cause-and-effect). And while it might seem that correlations are a good place to start the troubleshooting process, customers tell us it usually just slows down the repair as customers and field technicians are forced to chase false leads. (A case in point, a medical equipment manufacturer reported that even with 100,000 diagnostic codes, statistically they still had less than a 20% chance of identifying the root cause of problems.) As manufacturers implement more and more electronics, the number of sensors, data points and diagnostic codes they collect is increasing exponentially, until they find themselves drowning in an ocean of data that goes unanalyzed, or under-utilized.

The Key To Driving Efficiency

Better solutions exist. It’s not that IoT is a bad strategy for product support, it’s just inadequate.

About the Author: ATP

ATP is the leading provider of maintenance tracking, flight operations, inventory management, repetitive defect analysis, and troubleshooting software. The company’s applications help reduce operating costs, improve aircraft reliability, and supports technical knowledge sharing and collaboration within the business aviation, military/defense, commercial aviation, and OEM industries.

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