With analytics gaining steam across all industry segments, we did this quick study to investigate the amount of analytics adoption at domestic Indian firms. We picked up 15 large Indian firms that utilize relatively high analytics for internal purpose and score them on basis of analytics penetration and maturity.
Indian analytics market can be thought of having three sets of players-
- Service providers: companies that provide analytics services to the end consumer of analytics; either domestic or out of India. They make up almost 80% of Indian analytics market.
- Captives: These are companies with back offices in India. A lot of analytics worldwide is being outsourced to India via these captives. They account for almost 15% of Indian analytics market.
- Domestic market: These are Indian companies that utilize analytics for internal purpose. They either have analytics teams internally or outsource them to service providers. These account for less than 5% of Indian analytics market.
The focus of this study is to assess the domestic market with internal analytics teams.
Domestic analytics market is still in very nascent stage. Companies in this segment are typically large private B2C companies in sectors like –
Banking: ICICI, HDFC, Axis, Yes Bank and Kotak Mahindra
Telecom: Bharti Airtel, Idea Cellular
Auto: TATA Motors, Mahindra&Mahindra
eCommerce: Flipkart, Snapdeal and Jabong
Other conglomerates: reliance Industries, HUL and ITC
In terms of Analytics penetration (i.e. the amount of analytics being done internally), ICICI bank ranks the highest among these 15 companies followed by Flipkart and Bharti Airtel.
For Analytics Maturity (i.e. quality and depth of analytics function), Bharti Airtel ranks highest followed by HDFC Bank.
Apart from the above 15 companies, the analytics adoption is very low within domestic Indian market. Even for these 15 companies, the analytics is below par than their western peers within same sector. It’s evident that the adoption within Indian domestic companies is poised to grow sooner than later, leading to more efficiency in data collection as well as final business decision making.