The IoT was supposed to take over society by storm and change our lives radically. Yet, we still see countless initiatives ending in the IoT project graveyard.
A combination of factors is responsible for this state of things. All too often, we see companies launching IoT solutions with unclear business objectives. These technology-driven projects usually respond to trends and other unclear incentives but do not generate real value for the company. Industry leaders should see IoT as a tool to solve real business problems, not as a marketing story.
However, having a clear business objective is only the start. Out of our experience, many IoT projects fail because of a general mismatch between IT knowledge, available budget, and the project’s technical complexity. This is true for all project sizes, from the startup to the enterprise.
IoT is a complex endeavor.
The successful implementation of a smart solution requires the interconnection of a multitude of IoT components and technologies. The initiator of the project typically needs to:
- select the suitable sensors,
- choose a connectivity technology that fits his use case,
- be sure that the network coverage is good everywhere the solution is used,
- connect the sensors and decode the raw data coming from the sensors,
- connect the IoT data to his enterprise IT infrastructure before eventually making sense of the data and generating business value.
Add to this the exposure to multiple vendors, complex contracts, and support centers, and you start to see why many startups and innovation teams are overwhelmed by the technical convolutions of the IoT stack.
What does it mean for companies wanting to launch IoT solutions?
Typically, this leads to underestimating the learning curve of such complex technological projects and overlooking the hidden costs such as setup, consulting, and administration.
In many cases, a growing number of technical specialists and consultants need to be involved in the project to solve all technical hurdles. These technical experts are responsible for uniting the different components of the IoT system. However, they often lack domain knowledge. This creates a disconnection between the people with IT knowledge and the project’s initiator with the business case knowledge.
This distance between people with domain knowledge and IT knowledge can generate delays, additional costs, and other friction points.
The need for low-code, low-complexity IoT platforms.
We need to bring innovation teams, project leaders, people with domain knowledge closer to the IoT development process. Low-code, low-complexity tools shall enable IoT innovators to set up their projects with little specialized IT knowledge and little coding.
Including innovation-, R&D- and operations teams to participate directly in the development process can dramatically accelerate the path from idea to proof of concept (PoC) while reducing the mismatch between project requirements and implementation.
A critical element to achieve this is to use low-code IoT platforms to support the development process.
During the initial stage of an IoT project, large companies often face a “make or buy” decision. For companies that decide to develop everything in-house, unforeseen challenges are quick to arise. The complexity of the task at hand is often underestimated, and the need for future maintenance is sometimes wholly overlooked. On the other hand, the benefits of using proven IoT platforms are multiple.
Low-code IoT platforms greatly facilitate the journey from the initial requirements to the final use case. Using a solid technological base allows companies to focus on their business case and not reinvent the wheel for each new IoT venture.
Low-code platforms typically make complex procedures more accessible. Data parsing of IoT devices is one of them. Decoding raw sensor telemetry into structured data is a difficult task without any type of automation. With an automated data parser, this process only takes minutes (if not seconds) instead of hours.
No-code data processing is another example. Using pre-existing visual modules to define the data processing chain from the device to the connectivity technology up to the data storage enables testing IoT setups faster than before.
Finally, low-code platforms can significantly facilitate the ability to define business logic based on the collected sensor data and trigger output actions if specific conditions are met. Previously, the implementation of business logic into the IoT project required a good dose of programming. Thanks to no-code rule engines, it is now possible to collect and process data of multiple devices simultaneously and trigger actions based on custom rules without needing a single line of code!
I believe, therefore, that the IoT ecosystem needs more low-code, low-complexity application enablement tools to improve the success rate of IoT projects and, ultimately, the broad market application of IoT.
Low-code IoT platforms will not solve all your IoT challenges, but having the right tool at hand will help you get the job done a lot faster while reducing the risk of the whole process.
