In Analytics, Internet of Things

In a recent TechTarget article, Maribel Lopez of Lopez Research says that manufacturing may have a head start in implementing Internet of Things (IoT) solutions, but she still sounds skeptical about IoT in general.

IoT “is a lot of talk and not a lot of action,” she says. “First of all, the phrase ‘IoT’ is meaningless because it doesn’t talk about anybody doing anything that’s useful. Just connecting your stuff is not enough.”

How do you make IoT solutions that are more action than talk? Lopez cites three rules for user-centered analytics in the Internet of Things:

  1. Be relevant to users:  Pushing data to users just because it’s possible is not helpful. Information presented to users needs to be relevant to a task or situation that needs attention. For instance, reporting that vibration in manufacturing equipment is within acceptable limits is of little use. Such information requires no action from the user.
  2. Do the work for users: Performing analysis for users is more useful than equipping users to perform their own analysis. Business intelligence tools may make a table of vibration data  easier to manipulate and visualize, but that manipulation and visualization work takes users away from their main task of operating the equipment. As Lopez says, “Saying that the vibration [of manufacturing equipment] is out of range is interesting yet not sufficient.”
  3. Be timely for users: Presenting users with exception data in context with time to react has far more value to users. That keeps users on task and ahead of potential issues. As Lopez says, “Saying the vibration is out of range and if it continues for the next two hours, it’s going to shut down the plant — that’s more interesting.”

Situational Intelligence abides by these rules by turning big data to little data, focusing users on events or conditions that require attention. It’s not looking at all the data that counts; it’s looking at the right data at the right time.

Recommended Posts

Leave a Comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.

black-box