New companies that are starting out very often do not have a person at leadership who understands data and its usage or has any past experience with data, according to Sanjeev Bikhchandani, chairman of Info Edge India. Young companies do not use data the way they can or should, either because they’re not aware of the benefits or they don’t know how to.
Explaining how Info Edge used data in the early days, he said that new startups don’t recognize the importance of data (understand it and its analytics) and often new businesses do not have enough of their own data to build an algorithm. However, “startups will be well-advised to understand and appreciate the importance of data to build smarter products”, he said, speaking at a conversation at the India Digital Summit held earlier this month.
The founding teams of startups are very often friends who went to the same college, school, or B-School. Most often than not, founders may choose a person with the same skill set simply because they are friends and factors such as moral support and trust are considered more important. This results in certain essential skills being left out of the founding team, he explained.
“We [Naukri/Info Edge] didn’t have a top tech person when we started, we ended up underinvesting in tech in the first 5-6 years. As data becomes important, its appreciation needs to be understood by the leadership,” Bikchandani said. Info Edge meets startups every month for possible investments but they are yet to meet one, Bikhchandani said, “with data expertise in the top tables. You need appreciation and understanding of data at the top table”.
How Naukri used data in the early days: Naukri was launched in 1997 but only began using data in the early 2000s. One of the data solutions used on Naukri and Jeevansathi was algorithms that improved search rankings, Bikhchandani explained. For both brands, it was important to implement “two-way matches” wherein a person is not just shown the job or partner they aspire to, but also a job that they will likely get shortlisted for, or a person who will like them back. Data was also applied to reduce applicant scam on Naukri and to push up relevant results (CVs) on Naukri to the top. Relevant and effective algorithms throw up relevant results and save customers, such as Naukri’s paid recruiter clients, time, he said.
Please note that quotes are not verbatim and have been edited for brevity.
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