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Interview with Ashish Pachory, Chief Information Officer, Tata Teleservices Limited

October 29, 2014

Interview with Ashish Pachory, Chief Inf...
With the exponential growth in the volume of data, the ensuing competition and falling ARPUs, next-generation analytics provides mobile phone operators the ability to customise their offerings. In an interview with tele.net, Ashish Pachory, chief information officer, Tata Teleservices Limited (TTSL), talks about the benefits and challenges associated with big data and its potential applications...

What is the potential of big data solutions in India? What are the current trends?

Indian companies churn out large quantities of data, most of which lies untapped. Organisations are gradually gaining the ability to integrate and shape big data sets into insights that allow business leaders to make informed decisions. This could enable reduction in costs and processing times, the development of new products, and optimised offerings, ultimately leading to smarter decision-making and operations.

Several enterprises in India already have elegant predictive tools and robust data warehousing in place. While these solutions enable the leveraging of structured data, it is also crucial to effectively mine unstructured data.

With globalisation and the demands of millennial consumers, we are now entering a new era, one with the personalisation of products and services where the function of one-size-fits-all is not applicable anymore. About 65 per cent of consumers want companies to only share offers that are relevant to them. If company data is mined and analysed effectively, it can result in insights that deliver bespoke services, products and communications that guarantee customer loyalty. Telecom is at the forefront of exploiting the potential of big data, mainly because of data volumes and variety and the need for understanding and offering differentiated products to consumers. Big data solutions are also being explored in medical and manufacturing industries as they help in efficient monitoring and timely implementation of corrective steps.

How can big data help improve efficiency?

Big data analytics is a more cost-effective and accurate means of gleaning insights that help improve efficiency across business verticals, from human resource and distribution to marketing and information technology. Xerox was able to reduce the attrition rate at its call centres by 20 per cent by using big data tools to induct employees. Google, considered one of the pioneers of big data technology, has perfected its use and developed various techniques to sift through millions of web pages and petabytes of data to show search results in the relevant order and authority.

How is TTSL planning to leverage this market opportunity? How many clients do you have and what has been the customer feedback?

We are witnessing increasing adoption of big data solutions among our growing enterprise customer base. A strong communications backbone is a key factor for the success of big data implementation and in this regard we are already an enabler of this technology. There is a growing emphasis across Tata Group companies on adopting big data solutions to enhance customer experience and TTSL is an active player in this initiative. We have implemented big data solutions to understand and gather customer preferences to better serve customer needs and offer differentiated products and services.

What are the key challenges associated with big data?

Awareness of big data and its impact on businesses has just started seeping into the fundamental workings of companies. Several businesses enter the big data space without a thorough understanding of business requirements, goals and data policies. This often leads to the wastage of resources, and the insights procured fail to add much value to the company. There is a need for more big data specialists to help effectively run and manage implementation across functions.

Other barriers are the same as the ones that usually come with the adoption of any new transformational technology. These range from determining ownership within the organisation to building a business case for recommended implementation and expecting quick returns on investment. There is also the worry that the current database is too unstructured for effective automated analysis. But the fact is that it is not a limitation for big data analytics at all.

What has been the level of big data uptake by large and small enterprises?

Small and medium enterprises are following in the footsteps of larger ones by recognising the benefits of harnessing readily available data. According to research, millennial customers are willing to pay 20 per cent more for a personalised brand experience, as opposed to a standard product or service. The value-addition of using data insights to drive product and service innovations then becomes difficult to ignore across businesses of all sizes. There is no dearth of information on user behaviour as customer-brand interactions continue to transition to digital channels. The effective application of insights drawn from this data is fast becoming a key success driver for both large and small businesses.

 
 

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