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Feasibility Study

Gandhi K
June 30, 2021 |

Experiments can be turned into a great innovation, new experiments will help to get a good learning experience for sure and the results of experiments may be either successful or failure.

Do you know the success rate of new tech experiments?

90% of new startups fail. 75% of venture-backed startups fail. Under 50% of businesses make it to their fifth year.

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Why do new experiments fail even after implementation?

Most of the failed experiments have bad products or market fit, no proper groundwork and feasible study made before implementation which results in poor assumptions and miscalculations

What is a Feasibility study:

Feasibility study means whether a specific use case is possible to implement or not with all factors into considerations.

When a new use case is identified the first question we have to think about is why it is needed? and how it can help the end-users? If you can get meaningful answers to these questions, the next question is how it can be implemented? will arise, here comes the role of the feasibility study

In general, we have questions like:

  • Do we have sufficient resources and technical people? (Technical perspective)
  • Can we be able to generate revenue using this solution? (Financial perspective)
  • What about competitors, potential customers, future growth, expected sales? (Marketing perspective)

A feasible study report can be generated by considering all the questions from which we can conclude whether to proceed for further implementation or any improvements can be made or not to proceed further.

It gives more clarity and saves time why because in most of the cases experiments are dropped after implementation, in such cases may be prevented with proper groundwork and feasible study before implementation.

A feasible study report must have

  • Detailed explanation about the use case
  • Implementation approach
  • Technology stack
  • Cost expectations
  • Time expectations
  • Expected results


A feasibility study is a must-do process in all tech experiments. In Vizb when we initiate an experiment we used to have detailed brainstorming sessions along with proper feasibility study before proceeding to implementation and we found it is useful.

Gandhi K

Gandhiarumugam is an AI Engineer at DCKAP. He keenly looks at ways to innovate new solutions using Data Science and Artificial Intelligence technologies. Zealously experimenting with his learnings, he participates in various tech hackathons and coding contests. He has proved himself time and again with great achievements to his credit. His recent tech crush is Blockchain and is on his way to carving out innovative use cases in this space.

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