Big Data Is On The Rise In India’s Midmarket — But Without Clear Business Outcomes

As part of the research for my upcoming report on midmarket IT budgets in India, we collected responses on big data adoption trends and maturity levels from 430 midmarket businesses (those with 400 to 2,500 employees) in the country. Our research shows that around 35% of Indian midmarket firms plan to invest in big data technologies and solutions in the coming one to two years, but we also found that many of them focus on reducing costs (30%) or optimizing asset utilization (25%) as the business outcomes expected. Moreover, only 8% of midmarket CIOs who plan to invest in big data have a projected or proven ROI for their big data investments — showing that many Indian organizations are getting caught up in big data hype.

India’s weakening economic conditions have put tremendous pressure on businesses to be more competitive and drive growth. As competition in the midmarket increases, business leaders will expect new IT capabilities to respond to customer needs better, faster, and cheaper. The pressure is now firmly on CIOs to deliver clear business outcomes on their big data investments. Our survey and my discussions with Indian CIOs have led me to the following recommendations for midmarket CIOs investing in big data:

  • Set realistic expectations for the business. Business leaders can get sold on hyped-up promises of big data that vendors try to sell. One CIO of a medium-sized Indian manufacturing firm recently told me that he is concerned about the business’ expectations on transforming his firm’s sales model with big data and believes that the expectations are unrealistic. To help save IT’s reputation, CIOs must educate business leaders that big data is not a genie from Aladdin’s lamp, but a journey that will deliver incremental business results over a period of time. Setting unrealistic expectations – or allowing them to exist – is a recipe for disaster and poor career move.
  • Adopt an “outside-in” approach to defining business outcomes. Define customer-focused business outcomes (improving customer experience, customer satisfaction, or the customer acquisition rate, to name few) for big data investments that are linked with your company’s sales and revenue growth. This will help you get buy-in from business stakeholders on project funding and priorities and position IT as a business partner.  
  • Consider big data-as-a-service model to initiate progress at your organization. Mid-market organizations generally have limited budgets to invest in new technologies and skill shortages that hold back success. To counter these challenges, they can explore a cloud-based model for faster business outcomes from their big data investments. For example, Tresata, a software company focused on big data in financial services, offers a cloud-based platform to process and analyze large volumes of customer financial data, including integration with third-party data from sources such as the stock market.

Midmarket firms should view big data initiatives as business projects rather than technology projects. And for that, CIOs should focus more on driving customer loyalty and growing revenues as the potential business outcomes for their organization with their big data investments.

How are you aligning big data investments with business outcomes? I am keen to see some early examples of successful big data outcomes in India.