The hottest tech trend at the moment is IoT. Both media and analysts have fueled the hype that anything and everything will be connected and able to participate in an ecosystem that enables companies to become more efficient in their operations and unlock new business opportunities. However, looking back a few years on initial predictions for IoT adoption rates, the industry has fallen short. Why is that?Content Continues Below
Digging a little deeper, most of the focus on IoT, especially for enterprises and industrial companies, has been in the form of platforms. And, there is nothing more vague than the definition of an IoT platform. There are platforms that focus on hardware and connectivity, which represent the most basic aspects of IoT. Others are positioned as application enablement platforms, effectively a set of APIs and widgets. Then, there are data-centric platforms, including analytics and logic.
In all of these examples, vendors are providing basic tools and building blocks. And that is the problem. None of these platforms can improve business outcomes on their own. Instead, they require developers to stitch together the various components into … guess what? Applications.
This is not an unfamiliar story; every new technology starts this way. The killer app drives adoption and in many cases obfuscates the details of the underlying components. The majority of users are looking for the benefits they can receive from technology rather than immersing themselves in the mechanics.
Here are a few contenders for industrial IoT’s killer app:
- Predictive failure — For operations teams, unplanned downtime is the enemy. Yet that’s the situation they most often deal with when a critical asset unexpectedly fails. By identifying the leading indicators to a failure and then applying that knowledge to the real-time data stream, it is possible to be proactive. This puts the company in a position to schedule downtime when it is less impactful to the business.
- Adaptive diagnostics — Too often, the repair process starts once a technician arrives at the equipment. This typically involves understanding what error codes are currently active and then manually determining the possible root causes using static repair steps. Instead, IoT can automate this process by factoring in sensor data and historical repair information. Not only does this reduce diagnostic time and mean time to repair, but the system can adapt and learn over time.
- Condition-based maintenance — Aside from break/fix scenarios, industrial companies have the opportunity to move beyond interval-based maintenance schedules to ones that are tailored based on actual equipment needs. Fixed intervals lead to over-servicing, which is wasteful of parts and labor — not to mention unnecessarily taking the asset offline. Conversely, under-servicing can reduce the overall lifespan of the asset.
From the perspective of an operations manager, the notion of an app that can deliver on a needed business concern is immensely more valuable than a platform that has the potential to do something useful given enough time and effort. The killer app is what will take IoT from being a proof-of-concept project in a lab to a strategic part of the business. After all, industrial companies are not in the market for IoT; they are looking for improved business outcomes.
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