Early in the internet of things (IOT) adoption cycle, it’s often assumed the technologies will permeate industries in roughly the same way.
But there will be differences across major sectors of the economy — and it’s helpful to understand how those differences will influence IOT adoption.
Many believe that the core value proposition applies to different industries in the same way — more data from more sensors (things) combined with machine learning and predictive analytics will unlock significant value to tune operations. The industry-specific data is a detail that can be addressed with user interface tweaks.
There are many firms building multi-industry IOT platforms. These companies typically invest in a variety of platform components such as data sensors and hardware, data science algorithms, and a front-end user interface. This model has been successfully implemented in the past: Sales and marketing automation software solutions, among others, are designed for nearly all industries.
But there is an open question for IOT in general, and IOT for buildings specifically: Will platforms be industry-agnostic? With the IOT adoption curve in buildings mimic other industries?
Looking at the opportunity for IOT solutions within factories, agricultural facilities, and buildings indicates that the adoption curves will be significantly different. On one hand, all three of these industries have assets that are geographically distributed, a fragmented vendor landscape, sales and customer support that is dependent on relationship-driven networks, and a reliance on third-party service contractors to deliver the full solution to end users.
An IOT solution can cut out the inefficiency and transform how end users perform their jobs in a new, more data-driven way, right?