Ankita Gupta is the Principal Consultant and Co-founder of AnalytixLabs.…
Big data isn’t just for big enterprises anymore. Small and medium sized enterprises (SMEs) have also become active adopters of ICT. In fact, over the last couple of years, small and mid-size Indian companies have seen more big data deployments than the big competitors.
According to our study, the Big Data industry in India is expected to almost double by 2020. There is an increased adoption of SMAC amongst small and medium business verticals, owing to the increased volume of data and customer interactions. Our report pegs that the big data industry is estimated to be $2.03 billion annually in revenues and will grow at a healthy rate of 23.8% CAGR.
The data boom in India isn’t just limited to big enterprises, the growth of big data startups/technology vendors is helping SMEs in scaling up infrastructure capabilities and driving insights from data. Analytics India Industry Study \indicates that the India domestic market serves as a significant opportunity, with almost 4% of analytics revenues coming for Indian firms.
Also, the increased availability of accessible, cheap data centres delivered by cloud vendors, has brought down the costs of upfront investment for small businesses, thereby reducing the market entry barrier. Now, it is the question of choosing the right analytics vendors that fits the bill for small businesses. As more and more vendors offer competitive data-driven capabilities, what’s crucial for startups is getting started with the right infrastructure and build for scaling.
Big Data Impact in India
And behind the successful adoption of big data analytics (BDA) in SMBs is the exponential growth of market. According to our research, out of the annual inflow to analytics industry – almost 12% can be attributed to advanced analytics/ predictive modeling and Data science. And a sizeable 24% can be attributed to big data. The rise of BDA and robust analytics tools is helping small businesses accomplish their goals in a short span of time, see a higher ROI and ensure continued business success.
Big data means big business for SMBs
Even though SMBs are an early stage of big data adoption, with most small enterprises dabbling in the exploratory stage, businesses have started showing a greater interest in getting analytics platform off the ground to reap the desired outcome. Most small and mid-size enterprises are now viewing big data more as a strategic initiative and a central IT function.
Here are some of the recent big data deployments that made headlines:
- a) Fashion doyenne Ritu Kumar’s The Label team up with Manthan for advanced retail analytics: Indian fashion industry is usually regarded as a laggard in adopting technology solutions, but in a first, Ritu Kuamr’s The Label will be using Bangalore-based analytics vendor Manthan’s ready-to-use solution that provides advanced algorithms out of the box, eliminating the need for business users to rely on a team of data scientists and IT for detailed analysis. Manthan’s Advanced Retail Analytics will enable the fashion business to accurately forecast demand for new SKUs, identify opportunity areas in their existing assortment range and optimize their in-season allocation and delivery plans. The advanced analytics solution will provide granular insights that help in introducing the right products based on customer preferences, optimal in-season allocation across channels based on key attributes and insights to refine their delivery strategy.
- b) SAP is betting big on SME sector in India: With the recent GST move, the world’s leading enterprise solution provider is making a huge play in the SME marketplace. Krishnan Chatterjee, head (marketing), Indian sub-continent of SAP India, divulged that SME units make up 80% of the client base in India as it rolled out the GST software built in India for SMEs. Over the years, SAP has emerged as a dominant player in the SME ecosystem by providing the right big data solutions to improve efficiency, cut costs and boost sales.
Barriers to adoption of big data analytics
Ever wondered why so many small and mid-size businesses fail in a successful adoption of analytics. According to research, some of the key barriers limiting big data adoption is a lack of successful use cases, a lack of availability of packaged solutions, a limited understanding of technology stack and most importantly a lack of data-centric culture. Other factors include an acute shortage of in-house talent and the cost of implementing solutions. The other key challenge in big data tech is disparate data sources, high costs and infrastructure and concerns around RoI. Traditionally, most small and mid-size enterprises rely on intuition rather than data to drive decisions around pricing strategy or driving customer acquisition.
Here’s a round-up of key limitations to big data adoption:
- Concerns around the cost and complexity of big data solutions
- Lack of understanding of technology stack
- Lack of a data-centric culture is also a key challenge
- Senior management grapples to justify high investment & RoI
- Limited number of uses cases available in the Indian SME ecosystem
How to win over SMBs in the big data market
One of the key challenges for analytics vendors is to develop customizable software for SMEs that is easy to deploy and can be easily configured. Subscription based pricing models can provide flexibility to customers and help avoid vendor lock-in and lower entry barrier risk. To benefit from big data advances, small and mid-size companies should adopt a more modernized approach to IT, pivoting towards a cloud-powered platform to scale effectively. Also, before signing up for a big data analytics solution, businesses must learn how to identify the right data analytics tool.
Case in point – self-service analytics tool enables non-tech users to find patterns and drill insights and create beautiful dashboards while ETL tools help extract data at high speed for analysis. Some businesses may only require dashboard tools to present insights to management or skim over what-if scenarios through pie-charts and bar charts.
However, one of the key challenges for analytics vendors is to create flexible tools, keeping the end user in mind. Also, the DIY analytics and forecasting solutions should support different types of data.
This article first appeared on our Analytics India Industry Study 2017
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Ankita Gupta is the Principal Consultant and Co-founder of AnalytixLabs. Starting her career with McKinsey where she helped set-up the Analytics team in 2004, she has had a core focus in the Marketing Analytics area. Post almost 8 years with McKinsey, she then moved to Fidelity Investments to own the analytics for their UK client-side businesses. As a part of her work, she has worked across various industries like Healthcare, Telecom, Banking, Hi- Tech across various countries like Japan, Russia, UK, US concentrating in domains like Choice Based Modelling, Customer Life cycle Management and Pricing. By education, Ankita holds a Maths Hons degree from St Stephen’s College, Delhi University and has also completed her MBA from ISB, Hyderabad.