What makes these IoT initiatives so complex? When you manage your own IoT service, you are essentially building a software and hardware ecosystem that is exponentially more complex than a standard web application.
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Why underestimating complexity leads to 75% of self-initiated IoT projects failing
The IoT industry (Internet of Things) is in a time of rapid expansion. Industry experts forecast an increase in the number of connected devices from 8 billion (2017) to 20 billion (2020). As more and more companies want to enter the IoT arena, they face unprecedented challenges in building and implementing IoT projects.
According to a Cisco survey (2017), over 60% of those surveyed said they had significantly underestimated the complexity of managing their own IoT initiatives. What was even more alarming was that the same survey found that 75% of self-initiated IoT projects were considered a failure.
What makes these IoT initiatives so complex? When you manage your own IoT service, you are essentially building a software and hardware ecosystem that is exponentially more complex than a standard web application. This ecosystem requires the expertise of several technical disciplines: computers, electronics, hardware, networking, DevOps ... and the list goes on.
To start a successful iot managed services system, you first need to understand the complexity of designing, building, and maintaining such a system and decide whether it is better to build a custom platform or purchase a managed IoT solution.
Basically, it's a fully integrated service that offers everything you need to connect and deploy an IoT device. It must be able to support millions of simultaneous connections to devices and enable consumers to configure their devices for machine-to-machine communication. This means that a managed IoT service must set up bidirectional communication protocols via real-time event streams (e.g. a pub / sub-message pattern).
Although many companies often overlook the complexity of remotely managing and connecting thousands of devices at the same time, and the basics of building a cloud infrastructure that can do all of this and more.
As with any self-managed service, you need to spend a lot of time (weeks or months) creating hardware, software, network, and server requirements to run such a service. This often means that you have to hire new resources and / or use existing resources to enter the development phase. You also need to build, deploy, and test an infrastructure that is specifically designed for IoT systems and hardware management. This includes setting up a network and planning connectivity and redundancy strategies so that other devices can easily connect to that network.
According to Gartner, total infrastructure and endpoint services will reach nearly $ 2 trillion in 2017. For a managed IoT service, there are even higher costs that go beyond the normal server architecture that is required for a pure web application. A company must set up its own hosted cloud service, event-driven API infrastructure, and fault-tolerant real-time communication channels. Most of these services need to be sourced from multiple third parties, which causes many unknown costs and resources over the course of the project.
Developing an IoT service requires a wide range of expertise: embedded technologies, electrical engineering, DevOps practices, server infrastructure, manufacturing, security and more. In fact, Cisco (2017) found that most companies that consult IoT experts throughout the project lifecycle are completed on time. Self-employed companies often go beyond the original schedule and find that they lack the internal expertise to keep the project going. Unfortunately, until they realize that they need additional expertise, companies are usually deep in the development process, which makes exponential panning more expensive.
Every project is faced with scalability problems. But imagine that it expands from 100 to 10,000 or a million connected devices. If you do not scale correctly, your costs will drop and the system will fail. When scaling IoT, do not scale a single technology or a single product, but an entire one
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