IoT And Big Data: Success Comes Down To A Solid Strategy
A Verizon report highlights how big data complexity and a shortage of data science talent are hurdles for an IoT implementation, but we also have to remember the key best practice of having a business goal as part of any analytics initiative.
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Somewhere, right now, an IT professional is toiling away at connecting a temperature sensor, a security camera, or maybe a vehicle to the Internet so their company can collect data from that remote device, putting into play an Internet of Things plan.
Most likely, it is only a plan -- a standalone effort to connect a few devices to a monitoring application on a server many miles away -- and, while it can deliver value, it's not a strategy. Meanwhile, some middle manager overseeing the plan is boasting, "We're doing the IoT."
Time and again, we've read about organizations doing piecemeal, disjointed implementations of the IoT. It's a subject that is the focus of a recently released Verizon-sponsored report by Harvard Business Review, The Enterprise Lacks a Big Data Strategy for IoT Transformation.
The report says that 44% of companies "aim to use IoT to transform their business model."
Like our front-line IT pro who is web-enabling a remote device and the overly optimistic middle manager, most of those "doing the IoT" today (78%) are acting on a limited amount of IoT data or they aren't using the data at all, according to the report. Of the 306 business leaders surveyed by Verizon and HBR, 42% said their organizations lack big data skills and capabilities, and 51% said they are struggling with big data variety and complexity.
Know What You Want to Accomplish
All of that is evidence that too many organizations just have "plans" not "strategies" for the IoT. It's easy to imagine that quite a few companies have followed up on their IoT tech efforts with the question, "Now what?"
While Verizon focused on the big data challenges, those represent only part of the problem, one stage in a real strategy. If you want to transform your business -- with the IoT, big data, or any other tech concept -- you need to define a goal first, an understanding of what you want the company to be. That is a long-time best practice in IT, but also a practice that often gets overlooked. Maybe you want to keep the same lines of business and the same customer base, but you want to serve those customers better or milk greater efficiency out of a production/delivery process. Maybe you want to refresh a tired product line, or take advantage of new business opportunities or trends that might be revealed by sensors and other devices in customer-facing scenarios.
Even with such a goal your organization might find positive surprises along the way in an IoT/big data initiative -- new ways to use the data -- but if you don't have the goal you are fishing without bait in a really big ocean.
IoT isn't just a cool buzzword. It promises plenty of real and achievable benefits. A commonly cited example is how operations personnel can optimize performance and improve the uptime of factory line machines. The irony is that many of those machines have been feeding data into maintenance applications for years, but via hard-wired connections, not the web.
The "I" in IoT does offer the ability to extend data collection out to many new types of devices with new degrees of flexibility, including wireless connections. Placing analytics capabilities out near the network edge allows a restaurant chain to manage its perishables inventory or get a real-time view into the success of price changes. It can optimize routing for delivery vehicles, and can alert a retailer when a loyal customer enters the store.
However, when defining your IoT goal you also want to know before you plug in anything how the collected data will be structured, who will have access to it, how alerts to key changes are delivered, and who is assigned to take action on it.
[Read more about the need to balance speed and planning in The Strategy of Speed in IT.]
While Verizon highlights the complexity of big data and the shortage of big data talent, dealing with those is only part of a bigger picture, a big data and IoT strategy. It's the perfect example of why we have to look before we leap.
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