Why IoT Fails: Best Practices for Smart Prototyping

IoT projects are taking over enterprise IT strategies.

With promises of creating new opportunities for efficiency and productivity across business units, it’s no wonder that IT leaders are going all-in on investing in connected devices. However, the potential benefits with these new technologies aren’t coming without obstacles. In fact, a recent Cisco report reveals that nearly three-quarters of enterprise IoT initiatives are considered failures by business decision-makers.

So, why are enterprises having such a hard time getting out of the proof of concept phase? It all comes down to how IoT solutions are initially integrated and incorporated into the business. In many cases, IT departments are shooting themselves in the foot by simply plugging in “ready-made” solutions that may or may not fit the unique needs and challenges of their business. Taking this approach will not only result in wasted time and money in the immediate future, but could also have long-term implications – deterring IT leaders from future investments in IoT projects and, ultimately, setting the organization back in its digital transformation.

Instead, enterprises need to create personalized solutions through smart prototyping. All successful IoT projects start with a preliminary model. By testing different sensors, their connectivity within their target surroundings, and the data transmission from device to IT apps, enterprises can better understand the different use cases and overall business value of their IoT projects. Here are two “smart” practices for going from a small-scale prototype to a full-blown global roll-out of your project (to any size or geographic reach) without having to re-architect or re-develop any existing applications.

Ensuring prototypes are managed in multi/hybrid cloud environments

Most IoT prototypes involve only a few hundred connected devices, but even a seemingly simple application can require thousands of connections between devices to generate instantaneous data updates. With so many nodes as part of a single application, managing IoT prototype data with a multi-cloud strategy is an essential first step to eventually organizing, aggregating and analyzing data from millions of fully-deployed IoT devices. This is why software architects and developers have turned to event messaging to solve commonly distributed computing woes; allowing for flexibility in hosting IoT prototypes and allowing for real-time data movement up to par with enterprise expectations.

Preparing for network disruptions and data gaps

With prototypes, there are bound to be deployment failures. Mitigating network disruptions and data gaps are where smart monitoring comes in. In order to monitor the message flow and connections within IoT prototypes itself, developing a cloud-based monitoring system is essential, as it collects information and statistics from event brokers instantaneously. This allows enterprises to determine what’s working and what isn’t in the trial phase before real deployments.

IoT deployments will always come with challenges. However, IT teams have an opportunity to mitigate potential disruptions or issues through smart prototyping. With worldwide spending on IoT expected to surpass the $1 trillion mark by 2022, it’s important enterprises take the time to effectively implement the technology and improve their chances of an impactful ROI.

About the Author

Ricardo Gomez-Ulmke is VP of IoT at Solace. We enable the smart movement of data so innovators can focus on doing what they do best—whether that’s leading IT organizations from the C-suite, architecting systems to meet ever-changing business requirements, or developing kickass enterprise, IoT and mobile applications.

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