Zerodha encourages employees to invest in health, offers Rs10 lakh reward for losing weight

With outdoor movements being halted and lifestyles drastically changing over a large part of the past couple of year, personal fitness has come into the spotlight. Companies are also focusing more on employee wellness, with initiatives such as Meesho’s 11-day breaks to improve mental health. The latest among these is online trading platform Zerodha’s fitness challenge for its staff.

Burn calories to earn rewards

To motivate its employees to lose weight and get fit, the profitable unicorn has offered them a reward of Rs 10 lakh, among other incentives. The staff members would need to set daily goals and burn at least 350 calories a day, to earn perks. Fitness trackers will be used for chalking out plans, and those who achieve 90 per cent of the goals set in a year, will get a bonus equivalent to the monthly pay.

Announcing the challenge through his LinkedIn post, Zerodha CEO Nithin Kamath also added that people with less than 25 BMI will get half a month’s pay as reward. He also shared his personal weight loss journey through a fitness tracker to inspire employees to be active, while they work from home.

Employee wellness a new workplace trend?

Kamath’s push is among many other firms, which have laid emphasis on a healthy diet and workout during the remote working era. Some even have their own in-house nutritionists who have created weekly diet charts for employees, as per an Economic Times report. Some reportedly turned to meditation, yoga and sessions with clinical psychologists to improve mental and physical health for holistic wellness.

Zerodha had started making a profit even before it became a unicorn, thanks to tech-backed investing options, such as algo-trading. By using algorithms to manage portfolios and track markets, it allows investors to make quick returns, but the company also says that it doesn't guarantee profits. This assertion came after SEBI issued norms stating that those offering algo-trading shouldn’t refer to past performance of algorithms to promise returns.