According to analysts, the Internet of Things (IoT) is The Next Big Thing coming down the road. Sensors, mobile devices, wearables, connected machines. The list of use cases and the business projections seem endless today. A recent Gartner communication announced that in 2016, 5.5 million new “things” would get connected every day. This new flood of information forces us to review the (big) data processing architectures that we have today.
The well-known problem of entity identification will be increased by an unexpected magnitude. Before the IoT, the issue of identification typically related to business entities such as parties (people and organizations), products (SKUs) and locations. We grew accustomed to managing large volumes of customers with complex match and merge algorithms, and relatively small volumes of products for both sell and buy side.
With the IoT, the definition of a “product” evolves to include not just the product model, but each unit produced and sold. Where we used to speak of SKUs, we now speak of Serial Numbers. This trend was obvious in industries where units’ traceability was required because of their value or for regulatory purposes. The Unique Device Identifier (UDI) for medical devices, mandated by the FDA, was the perfect example of the latter case.
Well, that was just the beginning.
Present day, all the product units we send out need to be uniquely identified. We need to relate them to their product definitions, their successive owners, and trace changes for their entire lifetime. What parts were modified, what firmware was updated, what significant status changes or signals were detected, etc. We track each product that is sold as if we had owned it personally. We must know each product unit and its complexities like we strive to know each customer personally to build a greater customer experience.
These are major challenges that the MDM industry must now deal with. Managing a product catalog of a million items seemed extreme in the past, though mastering tens of millions of customers would not surprise anyone. Now that ratio could reverse. “Things” master data will easily eclipse one hundred million units, dwarfing customer data for many vendors.
MDM solutions that began their life as Customer Data Integration (CDI) solutions can handle this volume of data, but they were designed specifically to handle parties, not products. MDM solutions that began as Product Information Management (PIM) solutions absolutely didn't have these sorts of data volumes in mind. These sell-side PIM solutions could handle product hierarchies and SKUs, but they weren't intended to handle 250 million wearable devices.
The complexities of traditional product management can be combined with the data volumes created by the IoT. An MDM solution like Semarchy can be the lynchpin tying your big data stream of observations back to the critical attributes of the product master data.
Companies that wish to strategically benefit from the Internet of Things must choose an MDM platform engineered to handle these emerging requirements. Multi-vector MDM solutions like Semarchy are uniquely positioned to handle the new complexities presented by IoT and to tie the big data stream of observations back to the critical attributes of the product master data.