The value of any IoT deployment starts with the data. After all, that’s part of the reason we deploy IoT in the first place – to collect data. But an IoT deployment is a sizable investment, so, how do you maximize its value? Like any good analyst (I was previously at IDC and Causeway Connections), I’ve developed a “law” to help you optimize the business value of your IoT deployment: I call it “Turner’s Law of IoT Business Value.”
In a nutshell, Turner’s Law of IoT Business Value states that the business value of an IoT deployment is determined by:
- How often data is read
- How much data is read
- How soon data is read once it’s created
Let’s look at each of these factors.
How often data is read
Regardless of what industry you’re in, the value of your data increases the more you use it. For example, on a personal level, the sleep data on your FitBit has only so much value if you’re the only one monitoring it. Similarly, if a manufacturer collects data from an assembly line robot, that data has a limited amount of value if it is not regularly accessed.
You can increase the value of data by increasing the number of times the data is used. If I share my sleep data with my doctors, it’s now being read multiple times, and there’s intrinsic value in its analysis. If the manufacturer shares its data with the robot manufacturer, the value of that data increases because it’s being used and interpreted by multiple parties, multiple times.
How much data is read
The business value of your IoT deployment is also influenced by the amount of data you consume. The more data you collect, the more context you have, which can lead to faster and/or more accurate business insights. If I share my sleep and heart rate data and with my doctors, they now have another factor to consider when diagnosing my health. If the manufacturer collects the robot data as well as temperature and humidity data from the plant floor, the robot manufacturer has additional information and context to troubleshoot a malfunction.
How soon data is read once it’s created
Data is not cheese or wine – it doesn’t get better with age. If you’re going to create data, you need to use it. Otherwise, why are you creating it? Data has no business value if you’re not using it.
The speed or time by which the data is read should be determined by where the data outcome needs to be processed. In other words, where do you react to the data? At the place it was created, or elsewhere? If you want to use the data in enterprise resource planning or supply chain management applications, you will probably want the data in a hybrid cloud environment. This assumes that you have built a high-speed network infrastructure to handle these requirements. Likewise, you might want to use it right away. For example, a rogue robot may need attention as soon possible so you want its data exception to be executed fast without worrying about any network delay. In our other use case, perhaps your health metrics indicate a compromised situation and it would be critical to receive a message telling you of your condition. These actions require that the data be read close to the source and in real time.
Baby steps lead to big results
According to IDC, worldwide data will grow to 175 zettabytes by the year 2025 but conservative estimates put the use of IoT data at just 2 percent. Just 2 percent! Doubling this percentage can have a huge business impact on an enterprise. If a large automobile manufacturer were to double the use of its IoT data to drive its manufacturing costs down by just 1 percent, then models show that this change could equate to 10 percent increase in profits right to the bottom line.
Companies are currently under utilizing IoT data and therefore are extending the time to value of most IoT solutions. The three stages outlined above show the compounding business impact of using IoT in ways that are easy to identify and implement. Businesses who take advantage of the broad access to IoT data are well positioned to become leaders in their bid to become digitally transformed.
And companies can start rethinking their IoT data today. Click here for more on Cisco IoT solutions to help you make sense of your data now, and stay tuned in coming weeks to learn more about Turner’s Law and requirements for IoT at the edge.
How agile is the production control infrastructure to take advantage of the data should also be a factor.
Great question Chndramohan – if your infrastructure can’t scale then you shouldn’t be in an IoT solution. Its all about data and its volume, velocity and variety – and there are no good capacity planning models that can predict these 3 vectors into 1 accurate scenario. The short answer is that agility is a major factor!
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