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Interview

 
 



Interpreting and analyzing data is vital for successful business

Prateek Kapadia
Chief Technology Officer, Flytxt Mobile Solutions Pvt. Ltd.
 
  TT Correspondent |  | 02/12/2011

The sheer volume of information generated in the mobile age makes it difficult for legacy technologies to manage and analyze them and this is where new technology comes to the rescue. Prateek Kapadia, leading the technology innovation at Flytxt speaks to TelecomTiger about the importance of big data analytics that is driving the business decisions across the world today and setting the stage for how businesses will operate in future. Excerpts:

 

Q: How does real time data analysis and machine learning help in making better business decisions? Which are the areas where this technology can be applied?

A: There is an exponential growth in the amount of data being generated by businesses, supplier and consumers across industries. A large portion of the businesses, today, are conducted over the web with very short decision cycles. There is critical information hidden in this overwhelming amount of data that can help businesses in their strategic decision making process. This information overload, however, poses an enormous challenge for businesses and makes it impossible for the human mind alone to extract and present any timely and meaningful results out of it.  This is where data analytics and machine learning comes into the picture. Data science has the capability to sift through incredible amount of data and identify trends, patterns and predictable models that tell a story. With speed of information becoming critical to any business decision, the automation of interpreting and analyzing data assumes an essential role in improving competitive positioning of any business.

The application of this technology is far and wide. It has already proved its effectiveness in supply chain management, customer relationship management, BFSI, retail, traffic management and so on. An increasing number of businesses like travel and tourism, healthcare, governance and administrative sectors that deal with large number of people are beginning to recognize the potential of this technology.

 

Q: Social Media has already proved its importance for businesses in engaging the consumers. How does applying analytics make it better for them?

A: Social Media is a goldmine of consumer insights and an amazing source of social information. One case in point is the snack brand Hippo from Parle. Hippo was a fresh entrant into the snacking industry in India and was faced with the challenge of expanding its sales and distribution network. The brand turned to their followers on twitter to help report any incident of unavailable stock. The effort resulted in rise in sales of the brand to a whopping 76%.

Another example is a study conducted by the University of Bristol. They used machine learning algorithms to create predictive model that transformed keyword occurrences of flu in tweets into an estimate of severity of flu in that area. A little imagination is required to understand how important this information could be to a pharmaceutical company dealing in flu vaccines.

 

Q: What are the other sources of data? Can applied analytics impact the way businesses are run in coming decade?

A: Any business or outfit that deals with a large set of people and processes is a source of data. With the wide scale adoption of web, it is now one of the most important sources of data. The point of sale data for businesses, customer data, supplier’s data, logistics data, airlines data all provide a great source for data analytics. Unstructured data like files, emails, text, videos provide as a source too. It is estimated that such unstructured data will account for majority of all data created over the next decade. These sources when further combined with demographic, psychographic and behavioral data, climate and seismic data can yield highly sophisticated predictive models that can save huge money for businesses; make them more efficient and effective.

 

Q: Do you think businesses do not pay enough attention to the potential of big data analytics and its impact? What would you like more people to understand about this technology?

A: Traditionally, businesses depended more on intuition and gut feeling for making strategic decisions. With flattening of the world, businesses are expanding at great speed. Naturally, the complexity and size of businesses is far greater for them to rely on such intangible aspects. The new era demands faster and accurate insights that can guide the future course of business.

According to Gartner, enterprise data will grow 650 percent over the next five years but companies are still struggling to see the value in data analytics and its impact on business. The information age, with more and more customers and suppliers creating their digital footprint everywhere, offers an enormous opportunity for businesses to harness it to their advantage. It is important for enterprises to recognize that information is an extremely valuable asset that can serve as the driver of their growth, productivity and competitive advantage. The decision makers in the organizations need to understand that data analytics is a specialized area and investing in it could significantly increase their ROI.

 

Q: What is the role of your company in contributing to this entire ecosystem?

A: Data mining on social media and on the web made significant difference to business intelligence but it still had certain limitations. It still lacked precision on insights based on demographic, psychographic, behavioral and location data of the consumer. The technology that addresses this limitation is the cellular device – the next big thing in disruptive technology for businesses. Mobile phone embodies an all pervasive approach. It has an unprecedented reach and influence on its users. Precisely for this reason, it has a tremendous potential for brands to harness this medium for purposes of communication. By applying sophisticated statistical models and harnessing patterns, it is possible to segment consumers in various categories which could help the brands to serve the consumers with precision and relevance.

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