Hype. When it comes to the Internet of Things, there is plenty to go around. But the foundation of the vision – the inevitability of the impact – is as sound as it is profound. Connected devices and the data they produce will fundamentally transform a wide array of industries and business models, not to mention our daily lives. But when the remaining humans of this future pause to review how their world differs from the fantastic stories and bold executive prognostications of today, a single factor will stand out as the most meaningful predictor of IoT success in the enterprise.
The Whats and Hows of IoT Business Value
Poor technology decisions and team execution failures will account for some of the gap. And there will be a handful of market opportunities where the value of a connected product system is so great that delivery at any level will be sufficient to sweep aside incumbents who fail to invest in IoT at all. But the secret ingredient, the primary differentiator between those on the field with dreams today and the organizations dominating the connected landscape of tomorrow will be clear.
Did the organization confirm positive answers to the following 5 questions early enough in their move toward digital transformation?
- Do we know what insights, if achieved through IoT, would deliver significant business value?
- Do we know what we need to measure to obtain these insights?
- Do we know how to reliably obtain this data?
- Do we know how to process and clean this data to provide trustworthy insights?
- Do we know the cost to build, operate, and maintain such a system – and have a business model for new revenue streams greater than this amount over the long run?
It’s a simple formula. The news is already filled with IoT project flameouts, along with desperate attempts to pretend things are going just fine. This trend will accelerate as companies rush and skip one or more steps under the mantra of “Must. Connect. Now.” In the long run, they are correct – “Must. Connect.” But organizations who ensure they have the team, technology, and business model in place before allocating significant assets to IoT initiatives will be the ones to capture the prize.
The Spiral of Doom
Many companies launch prototype efforts to connect sensors to “things” that send data to the cloud and build simple apps to monitor and control these things as a first step, then assign a team to “scale to production.” For simple industrial applications (stationary smart lockers for example), even teams without significant IoT development experience may succeed – at delivering a system that collects and sends data from devices to the cloud along with an application to monitor and control these devices. Alas, data delivery and device control do not a profit make. A spiral pattern begins with the retroactive search for valuable insights. Failing this first test, many fall aside. Those who already know what they are looking for tend to succeed at the second test of clarifying what data will be required. They move to the third challenge – how to obtain this data, as well as the fourth of working out the processing and data “cleansing” required to enable their analytics and machine learning tools to provide the answers they seek.
It is within this “Gauntlet of How” that digital transformations get stuck. Not all data can be reliably gathered and trusted. Whether due to limitations of physics or constraints of regulatory compliance, certain insights will not be achievable on the desired schedule or budget.
Finally, there are companies who emerge from the maze technologically victorious, only to find the cost to operate their hard-won solution exceeds the business value of the insights it enables. Or conversely put a too-low fixed cost ahead of ensuring devices were sufficiently capable of gathering and transmitting the full range of data required by the system to deliver customer value. The further one heads down a dead end one way road, the harder it is to back out and try another route.
From Prototype to Production
Organization leaders should ensure their teams understand what value their proposed connected systems will unlock – and how they will obtain and process this data into the proper fuel for their analytics and machine learning tools in a cost-effective manner, before moving beyond the proof of concept phase. At Bright Wolf, we’ve helped our Fortune 1000 clients verify all 5 questions point to profitable industrial IoT solutions, and filled the gaps when their internal teams or technology could not, to enable successful global deployments of scalable, secure, and maintainable systems. We’d be happy to chat about how we could help you too.