Students’ Speak: My journey of cracking Accenture’s PI round

3 mins readUpdated on Feb 25, 2020 15:23 IST
There was only three round in the PI phase. Different companies have various selection procedure, they came up with GD+PI round after clearing Aptitude and Coding Round.

By: Jitendra Patel

There was only three round in the PI phase. Different companies have various selection procedure, they came up with GD+PI round after clearing Aptitude and Coding Round.

I am an electronics and telecommunications engineer who recently got placed at Accenture for the 2020 batch. I had applied for three companies in my campus placement of which I cleared all the rounds till Personal Interview (PI) but unfortunately, I was not selected for two of the companies. I will share my experience with these three companies in details.

The three companies where I have given the GD & PI were Capgemini, Accenture, and IBM. Let's start with the zero-day company and discuss the process of Capgemini. There were three rounds, Aptitude, Essay writing and PI. The first step to reach the PI in all companies was Aptitude. Now, Capgemini mainly focuses on Essay Writing and what not to do is frequently using backspace. With this all cautions, I cleared all the rounds. Now the time for PI and enter the room, I was a little bit nervous I did not give the proper self-introduction, but that's ok it just started but I internally I knew that I had done a mistake. They started asking me questions and I have given most of the answer. After coming out of the PI I had a chance of getting selected was around 75 per cent. However, I never made it.

Now, it was time to appear for IBM, I should say the first company who introduce the unique selection process having four rounds. The most interesting round was first round there was no aptitude it was just to play five different games which decides you Analytical Skills, Problem Solving Skills and Critical Thinking. Now that's was interesting. The other round was a psychometric test, English ability, Coding and final PI interview. The interview went well but the result, not selected. Now, this time I was more prepared and all went well. But after lot's of thinking, I realised that I had done a mistake, He asked me, “Are you comfortable working late in the night? I lied and just said yes. That turned out to be a googly for me. Hence, be genuine.

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Now, finally, it was time to appear for the Day One Company that was Accenture. There was only three round in the PI phase. Different companies have various selection procedure, they came up with GD+PI round after clearing Aptitude and Coding Round. In GD and PI round at one-time group of five students use to go. First, they ask to introduce ourself. Rather than asking about academics, we were asked random questions regarding our favourite movie, what is ergonomics. The most important is to be in listening mode when others are speaking. In our case, when I was speaking, one of the girls were not listening to me. The interviewer asked her to continue my statement and she had no clue. This made a negative impression, so be attentive.

One thing was to remember is that be genuine because they will know who is telling the truth. Another incident happens where the interviewer directly tells the girl that please don't give "Sugar-coated answer".Be yourself. The interview was going around 30-40 minutes such an amazing experience. I successfully cleared the interview. So that was my experience hope you will learn from it.

Also, I am listing some dos and don’ts:

  1. Be yourself.
  2. Be confident and don't be overconfident.
  3. Dress up informal.
  4. Answer all the questions calmly.
  5. Learn your mistake from the previous interview and improve them.

About the Author:

Jitendra Patel is pursuing a Bachelor in Engineering (BE) in Electronics and Telecommunications from Yeshwantrao Chavan College of Engineering, Nagar Yuwak Shikshan Sanstha. At present, he is undergoing a six-month internship in Pune and has received a placement offer from Accenture. He has an interest in IoT, Artificial Intelligence and Machine Learning.

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