By Jens Refflinghaus, Kepner-Tregoe

The last few years have seen a rapid growth in the availability and demand for limited purpose connected devices and sensors to enable process automation, data collection and monitoring in industrial applications. The ability to capture a wide variety of operational data in real time and use it to create actionable insights has a tremendous potential to drive process optimization. While the decision-making benefits of these low cost devices with easy setup make early adoption of IoT appealing to business leaders, they pose some challenges for enterprise service management processes and the IT department tasked with problem management for their organizations.

The first challenge of IoT devices is in the simplicity of the technology. To make the devices cheap and easy to use, most are lacking both the management and diagnostic capabilities necessary for technology support professionals to monitor and troubleshoot issues and failures when they occur.  Furthermore, most IoT devices do not support the addition of 3rd party management software (a common approach used for smart phones and PCs).  The impact of this limitation is that IT staff must rely on either environmental monitoring (network, cloud platform, etc.) or the limited administrative functions available from the device manufacturer to know when an issue has occurred and troubleshoot them.

The second challenge is in how the large quantity of data that IoT devices produce is consumed by business users.  Business value is not created by the capturing of data on the IoT device but rather the actionable insights derived from the data used as they inform decision making. To generate this value, the data from IoT devices is merged and put into context alongside other technology components (hardware, software, connectivity and cloud services) and the industrial processes they are supporting.

When an incident occurs that requires investigation, it is typically the user experience (or integrated set of information that includes IoT data) that is reported as having problems, not the IoT component specifically. Because of the large number of components that contribute to the data that users consume, diagnosing problems and tracing them back to their source can be difficult and slow as often the configuration is not known and may include components from a variety of suppliers. Because most IoT devices lack enterprise grade management capabilities, once a problem is finally diagnosed, the only remedy is often to remove the IoT device from the environment and wait for the supplier to develop a fix.

As technology continues to develop and mature and problem management professionals learn to adapt to the "new normal" that IoT creates, the manageability challenges will naturally be resolved. There are efforts underway to develop industry standards for security, manageability and interoperability of IoT devices that may help in this process. In the meantime, enterprises must balance the benefits and challenges of introducing IoT technology in critical roles within their industrial processes - ensuring an appropriate risk profile for their organization.  

The Kepner-Tregoe problem solving approach is used worldwide for root cause analysis and to improve IT stability.