Selecting the right IoT Platform: 3 best practices you should adopt

IoT Platform selection: The importance of getting it right

Several thousands of enterprises are currently performing their first IoT projects – whether its smart factory, connected car, or smart energy – most of them now consider using a modular IoT software platform to manage the data flows, support application development and provide basic analytics. This promises lower cost, faster time to market and more professional support. The IoT Platform selection process is not easy, however. There are hundreds of platforms to choose from with prominent examples being Microsoft Azure IoT, Amazon AWS IoT, PTC Thingworx, Siemens Mindsphere, GE Predix, Software AG Cumulocity IoT, or C3 IoT Platform.

“Some IoT platforms do not live up to the task”

However, several instances have now been reported where the IoT Platform did not live up to the task. In one instance, the platforms data model proved to be limited to one industry specific scenario and could not be scaled to other use cases for the same company. In another instance, support for multi-cloud backends was not available and hindered the end-user to exchange important data sets between different platforms.

It is becoming crucial, for most companies even strategic, to ensure they are choosing the right IoT Platform that will seamlessly manage their IoT data flows. Not only for one use case but for most, if not all, of the planned use cases in the years to come.

IoT Analytics recently performed research and interviewed a number of customers of IoT Platforms on how they choose their platform. These are 3 of the best practices that emerged from the analysis:

Best practice 1: Pre-select platform vendors based on qualitative criteria

Almost all of the customers interviewed use some kind of criteria catalogue for pre-selecting vendors. In one extreme instance a customer used a catalogue of 130 different dimensions.

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