Step 1: Gather data
Step 1 begins with the basics: IoT data. Or more precisely, gathering the data from your devices into a usable format. When IoT first came on the scene, we were fascinated with what we could do in our homes. We discovered we could connect things – like our light bulbs – to the Internet of Things. And we could use that connectivity to turn them off and on. A cool technology, and those early connections generated a lot of hype. But to what end?
That’s why, step 1 begins with the basics: IoT data. Or more precisely, gathering the data from your devices into a usable format.
Step 2: Visualize patterns
As the technology matured, so did the expectations of businesses. That’s why, as the market developed, the focus shifted from instrumenting data to visualizing it.
Let’s take that connected light bulb in step 1 and move it into a large retail business. If all you did was turn the many light bulbs on and off via their sensors, then yes, that’s convenient. But is it useful? Or to put it another way – is it useful enough to warrant transforming all of your facilities with instrumented light bulbs? What’s more interesting – and useful – is what a connected light bulb can tell us about the way it is being used. Those insights show you energy usage. They help the retail owner manage energy consumption and understand where and how to save money and resources.
For example, perhaps there are areas that don’t have to be lit at certain times. Or you discover that on especially sunny days, you can dim your lights by 10 percent and still keep the same level of brightness. Once you begin to understand the patterns in your data, then apply the value to your business, you’re making the most of step 2.
Step 3: Advance to analytics
The next step in the IoT journey focuses on making data even smarter through analytics.
Analytics allows you to couple real-time, IoT device data with existing, longer-term and historic information. It’s a more complete picture of what’s happening with your devices and in your environment. It also allows you to spot patterns and make predictions, and adopt new practices that proactively avert risk and avoid potential problems.
To illustrate, let’s change the example from connected bulbs to more sophisticated manufacturing machines. Periodically, one of these machines fail when the torque of that machine spikes. But only sometimes. This is where analytics can help you play detective to solve the problem. In reviewing your other data, you discover that your temperature sensors record a spike two hours prior to the variance with torque. When those two things happen, your machines are 80 percent more likely to fail. Now, with information from multiple sources, you can more confidently predict the particular combination of factors that cause problems. That, in turn, enables you take more proactive measure to keep machines up and running, reducing downtime and increasing productivity.
Step 4: Infuse with Artificial Intelligence
The fourth step on the IoT journey focuses on using Artificial Intelligence to do even more with your data. Even with a refined use case on how IoT can help your business, you’ll still have too much data, especially as you combine data sets. It’s easy to become overwhelmed, so that’s where AI comes in. Machine learning will help you clean up the data you have, distil it down to the most relevant pieces, and find the seemingly desperate data sets that actually matter.
With those efforts, you’ll find even more synergy within your data. It also helps identify what data should be used and what should be thrown out, because all data is not equal. As you refine the process, you’ll be able to do more sophisticated tasks like forecast models, apply predictive maintenance and anomaly detection. In other words, you gain the right, rich context that helps make sense of what you are seeing. You’ll also be able to solve problems more easily and perhaps even identify new opportunities and business models.
How to choose your platform
Remember, your IoT journey isn’t a single thing you do. Infusing IoT into your business truly is a journey. And it’s definitely worth the effort!
If you’re interested in starting or building on your IoT efforts, I invite you to read a recent Forrester report: The Forrester Wave™: Industrial IoT Software Platforms, Q3 2018. It’s a 24-criteria evaluation of industrial Internet of Things (IIoT) software platform providers.
About the author: An engineer by training and a lifelong technology enthusiast, Jiani Zhang is the Program Director for Offering Management for the IBM Watson IoT Platform. In this role, she helps lead customer engagements and guides the development of the Platform technology, both of which help clients realize business results. Previous to this role, Jiani led an offering strategy and management team focused on Industrial IoT. And to round out her IoT expertise, she also served as an original member of the IBM IoT leadership team. Her technology expertise runs from product design and development, to management and consulting.
Jiani holds a B.S. in Electrical Engineering and Computer Science from University of California, Berkeley and an M.B.A. from UCLA Anderson with emphasis in Technology Management.