A big challenge I see is the inability to accurately measure the ROI of IoT PRIOR to putting the systems in place to derive value from the data. This is especially challenging in old-school manufacturing or other fields where they have not utilized data in their day-to-day lives. Sure, you can do some what-if scenarios but the true solution of capturing data, ETL-ing it,enriching it with other sources in a Data Lake is hard to quantify and then explain to companies who have not traditionally viewed IT projects as a value-creation driver.
To some extent, using IoT data in meaningful ways can be so pervasive throughout an organization that it should be viewed more like Microsoft Office or Email - part of the standard tools that any company needs to have in order to compete but we are still forced to create the ROI & business justification for the data consumption tools. I recently heard of a large auto maker collecting many years' worth of IoT data that is sitting on a giant S3 bucket - with nothing being done on the data consumption side.
Has anyone else experienced this or grappling with the cost justification of Data Tools?
Replies