Five main reasons why IIoT Projects fail at the Proof of Concept stage
Nearly 70% of IoT and implicitly IIoT initiatives fail at the Proof of Concept (PoC) stage, according to a recent study by Cisco. Though the number looks high, it resembles the past records of other new initiatives such as cloud computing, agile initiatives or likewise.
What are the main reasons for such high failure rate of the projects at an early stage? I am attempting to highlight few main factors that could lead to such a situation:
- Jumping the hype bandwagon without proper clarity on business impacts:
Typically business needs should be the driver for the technology changes. Business should drive the technology, and not vice versa. However, many times it happens so that because of the technology hype cycle, leaders gets excited and would like to be seen as the front-runner change agents. They would like their department to be the one showcasing the leading edge of projects. In such cases, the feasibility and viability aspects are not adequately studied in details and the PoC is starting with incomplete information. In such situation, parties rarely arrive at a common expectation of outcomes. Each of them has their expectation of outcome, which is documented only in their mind. As things progress, the differences in expectations start to come out in the open, leading to tussles and impact project outcome profoundly.
- Scaling roadmap is not drawn
It is important to do PoC and validate the concept before going for full-fledged implementation. It helps in validating the concept, end user desirability and creates ample room for incorporating feedback from business stakeholders. Though it is not required in detailed, a high-level roadmap which is giving a clear view of how things are to proceed from start to an end it’s a plus. This provides clarity to the mission, link the actions with the vision for the initiative, and keeps check on the timeline, cost, etc. If scaling roadmap is missing, the team carries a lot of confusion, apprehension, and doubt in their mind, leading to less than 100% of dedication.
- Missing talent and expertise for implementation
IoT is still evolving concept. Constant innovation is taking place ongoing basis. The project implementation needs very high expertise on technologies that are just arrived, or in some cases not yet arrived in the market. Finding talent, skill set, and expertise for such projects is hard. Reference implementation and the best practices may still be lacking, further leaving room for some experimentation during implementation.
- Missing integration & collaboration among various teams
IoT projects have several interdependent components, such as hardware, device software, protocol stack implementation, gateway systems, backend systems, end user application, analytics, etc. Several independent teams are working on these components, which have very high interdependency on each other. They should constantly work in perfect collaboration with each other, having concise and precise communication on a regular basis. Invariably, it happens that team collaboration doesn’t work perfectly well leading to undesired situations.
- Changing priority & missing management commitment
Any new change is expected to through rough weather. Change is supposed to face internal and external resistance, and sometimes a lot of criticism. In such situation, it is important that all important stakeholders are rightly onboard and provide their complete support. Crucial support and backing of senior management is key to the success of such initiatives in hard times. Patience is the key and outcome will follow. If there are frequent changes in the management priorities, it is bound to lead to failure.
More about Why 85% of Machine Learning Projects Fail and how to avoid this.
The article was written for IIoT World by Anil Gupta, Co-founder of Magnos Technologies LLP. He has about 23 years of experience in Connected Cars, Connected Devices, Embedded software, Automotive Infotainment, Telematics, GIS, Energy, and Telecom domain.