[CAJobPortal Insights] In recruitment , how to overcome strong biases sabotaging your prospects

It was an important interview for Jaya. She wanted to get into this Financial Analyst role at marquee manufacturing major in the steel space. But she knew that, no matter, how well she would perform in the interview, she would not be selected. This was because she was working at the Hotels division of this premiere company and the interviewer had a very strong perception that people in the hotels industry have very limited exposure to finance, as hotels would entail only Accounts Receivable, Accounts Payable and Inventory. The interview lasted just 10 minutes and she was told that they would get back if she is shortlisted – the usual diplomatic way of saying no. This was her 5th consecutive interview where she was rejected because she was from this industry and people at large did not want to hire from there. So much and so that even when she removed even mention of the word “hotel” in her CV, the monster continued to chase her. She regretted joining the company as a fresher on campus, enamoured by the larger brand.
How often, in recruitment, we give more importance to our set biases rather than the individual talent of the candidate – and all sorts of them – fair or unfair , say,
a) gender ( girls will not be recruited as they will have problems working late hours or with outstation travel) or
b) attempts in an exam like CA – first attempt means abundance of IQ and second attempt means dumbness – altough it might just be an error of destiny
c) If he is an MBA, he wont stay long in the company – as MBAs are over-ambitious
d) If someone is fat, he is not fit and wont be able to work hard
e) If someone is from Kolkata, he might not be hardworking as work culture is poor there
So many IF THEN statements that can make/break someone’s career
There might be strong reasons why an individual holds such biases – we are, after all, products of our experience.
The larger question is that how can an employer prevent an individual’s biases come in the way of fair assessment ?
Will forming panels be an option here > But then , is it feasible always ?
What could be the other options here?