A number of common themes continuously emerge across all of the conversations I have had with IoT vendors. One of those themes is the importance of operations and information technology teams working together to plan, implement and manage the Internet of Things. In many enterprises, this collaboration between OT and IT creates enormous organizational challenges. From stories I have heard, these are challenges even place the success of new IoT initiatives at risk from being successful. Yet, the IoT project is not simply a project to collect data traditionally the realm of IT. The value from the IoT is gained from analyzing and acting on the data which requires the insights and expertise of operations and even line-of-business staff.
A recent article published on www.b-eye-network.com, focused on the importance of “time-series data” collected through IOT sensors. As the author wrote, “Time series data, on the other hand, has forced us to look at it in a different way. It forces us to look at the data as time intervals, as time buckets, and be able to slide an analytic tool along this time series to see what is going on.” The “what is going on” in real-time enables predictive-based analytics to empower operations to make informed decisions that save money and increase productivity.
But there was another critical perspective I derived from this article that further reflected the OT and IT challenge. The article provided a specific example of how time-series data drives predictive maintenance analysis. In the course of the example though, the author stated, “So we need to think about how these two things fit together. I’ve got the analytics on one side – that’s the ability to do analysis on the time series data – but then I have to go back into production operations to take immediate action in order to get the benefit.” Here’s an excerpt from that example.
What it leads to is the ability to save money. If I can do preventive maintenance, then I don’t have to take my airplane off the route at a time when it is busiest. I anticipate that something may be likely to fail and I can make sure that I get the aircraft to the place where the component is so it can be replaced. This is where it links us back to our production analytic platform. When I start talking about decisions like that – where is the aircraft, where is the part, where are the skilled people to do the work – I’m actually talking about operational things at that stage rather than what we traditionally and typically do in business intelligence or analytics.
In the pre-IoT world, IT would handle both sides of the data gathering and the business intelligence setup to build and distribute a report. However, in post-IoT, IT only handles the first part while the real-time data analysis most leverages the domain expertise of the operations team.
The IT and OT challenge is a common theme because it’s a paradigm shift for enterprises. And it appears to be a challenge many enterprises have yet to figure out how to overcome effectively.
Are you experiencing similar challenges between IT and OT? How do you think organizational dynamics are hurting or helping the IoT initiatives in your enterprise?
