Manage Learn to apply best practices and optimize your operations.

How to accelerate IoT adoption with faster pilot-to-production cycles

A few days back, I was at the sixth IoT Summit Chicago, an annual IoT event hosted by the Illinois Technology Association. Being part of a panel on AI, machine learning and industrial IoT, one of the pertinent questions directed at me was how enterprise IoT pilot projects can be managed better to minimize the IoT adoption cycle. Interestingly, this topic dominated most of the sessions at the summit!

IoT providers are rightfully interested to shorten the purchase cycles for their IoT products and systems and accelerate business. However, when we add buyer’s sentiments to the equation, many barriers and bottlenecks pop up that make IoT adoption slower than what we want it to be.

Anyways, while discussing that question at our panel, many useful strategies surfaced which could address the problem head on. Let me share some of those in this blog, with a caution to the readers that there’s no silver bullet to this; as an industry we still have work to do to make IoT pilots faster and smoother.

Businesses care about the bottom-line

Those of us on the technology side of the fence have indeed fascinating things to tell about IoT and digital — about how it can transform the face of businesses and industries. However for an enterprise, it is not so much about embracing digital; digital is only a means to achieve the end. The goal typically is (and should be) to solve a business problem, such as opening newer revenue streams, cutting Opex, improving customer satisfaction and so forth.

Now, when IoT is offered to solve a specific business problem, (for example, adopting predictive maintenance to reduce factory downtime), are we able to define a how-to roadmap to achieve the intended results? Identifying a clear view of the steps and challenges upfront to achieve the results is a number-one requirement of any adoption strategy. However, given the fluid nature of most IoT systems, right now that’s the piece missing in many pilot projects. In a frenzy to get ahead of the market or to do cool stuff with a trendy technology, we lose sight of the road that’ll take the enterprise to its intended goal.

Clearly defining a roadmap at the beginning of a pilot project that identifies various technical nuances, dependencies and tools is crucial to successfully reach the finishing line. This needs to happen irrespective of the size of the pilot.

Enterprise IoT is not the same as buying a smartwatch

We don’t need a pilot or proof of concept before we purchase consumer products, such as a smartwatch. But enterprise IoT products are quite the contrary as they involve considerable investment and risk. The investment is more than just in terms of Capex; people are a huge piece of the puzzle. Adopting digital and its successful deployment can impact organizations in a big way. Are we prepared to absorb and skillfully navigate through organizational barriers? The importance of communications is often underestimated.

A pilot project is not just about technical roadmap, it’s also about a people roadmap. In the case of adopting enterprise AI systems, most often workforce augmentation is part of the equation. Unless that’s addressed well at the planning stage, the pilot may never successfully execute.

Similarly, key performance indicators and scorecards need to be well-defined, not just as final exit criteria, but also for the intermediate milestones of the pilot execution.

Adoption of any digital technology impacts the organization in different degrees. A pilot must factor those in for a faster and more successful transition to production and long term success.

We’ll continue to discuss some more successful strategies in my next blog.

What are your thoughts on accelerating IoT adoption by fast-tracking pilots?

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

Data Center
Data Management