How to Achieve a True Internet of Things (IoT) Implementation

Jolene Baker, Sr. Manufacturing Intelligence Specialist, LSI Logical Systems

There is a growing number of readily available, out of the box, analytical intelligence software platforms/packages in the manufacturing industry. Some of the software packages are ready to be deployed in your IT or OT environment on microcomputers. These microcomputer mesh systems can provide industries with mass computing power and intelligence from wherever they are integrated, networked, and powered on. This trend of easy to install intelligence makes the goal of achieving a true Internet of Things (IoT) almost too easy.

…but is it?

The intention of the Internet of Things (IoT) is to create collaboration of all devices for information transfer without human intervention. The implication of IoT is that end users will gain access to data and information from anywhere in the respective network because the data is shared or housed in a common location. If IoT could be “super” simplified into an easy equation, based on the previous two sentences, it would probably look like:

The opportunity to benefit from true IoT in industry is more available than ever with these new technologies, however I am not seeing it happen. Despite my enthusiasm for the possibilities with these technologies, I am noticing a larger tendency toward Data Silo’s.

…wait, what?

Consider creating a goal/vision that aligns with your Data Governance policy so as new technology is rolled out

Data Silo’s are often birthed out of immediate need for data or small group of people requiring connectivity. They are not part of a larger technology strategy and they often elude IT and OT standardization requirements. If information technology were a garden, Data Silos would be the unsightly weeds. It is unfortunate to see that more and more of these readily available, out of the box, analytical intelligence software platforms/packages are becoming weeds.

...why?

The inundation in the manufacturing industry of readily available, out of the box, analytical intelligence software platforms/packages is almost overwhelming. There are so many incredible options to meet whatever need your industry may have. The problem is some of these package installations fail to become part of the overall equation above, creating a limited IoT:

…how to prevent or fix this?

I would encourage any Technology Department to implement a stricter standardization of implementation and/or Data Governance policies. Often the software user interface can be designed/adjusted to integrate directly into the existing Data infrastructure. Investigating some of the unseen components in a package of interest to determine if there are pre-existing technologies employed within the business that will mesh well or provide similar functionality. Consider creating a goal/vision that aligns with your Data Governance policy so as new technology is rolled out; it interfaces reliably to your Common Data Repository, all the while minimizing point to point integrations and eliminating potential silo building during implementation. Introducing any or all of these strategies will reduce the points of potential failure and data silo-ing.