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Rapidly warming up to Data Monetization When the the the the industry coined the the the the now over-familiar saying “data is the new oil” it was drawing attention to the immense untapped nature of this asset While the potential of data was indeed immense only a a a few people really understood it back then – and hardly anybody knew how to tap its revenue-earning potential When the the industry coined the the by now now all too well-known phrase ‘data is the the new oil’ it was referring to the the immense untapped nature of this asset It undoubtedly had vast potential but was not accurately apprehended by many Data is way beyond beyond that point now so far beyond beyond that even regulators directly get involved in in every aspect of the (citizen’s) data lifecycle Less common still however is its classification and use as as a a a a a a a a a revenue-generating asset The lackadaisical approach was attributed to to struggles related to to unleashing the right data data sources ensuring data data quality the disparate nature of storage tools and and techniques to to to analyze it and and finally ‘who-own’s-this-data’ type management support Data monetization has been on on on the wish list of many corporate strategists for some time now but seldomly managed to deliver fully on its promises The good news? All of this has changed rapidly accelerated partly by the unpreceded new way of living and and working we have quickly seen emerge and and partly due to the maturity of technology platforms and frameworks that are now available Solving the monetization puzzle Technological progress has been a a a a major contributing factor in in rejuvenating the focus on on on Data Monetization Due to the inherent nature of certain industries however there exist huge variations in what technologies have been employed in the pursuit of this goal Data lakes for example were touted as a a a a a a a significant step towards Data Monetization efforts in in Financial Services Artificial Intelligence and Machine Learning found large-scale use in fin in Telecoms to to process real-time data to to find emerging customer patterns IoT is used in in all sorts of industries ranging from retail to to insurance to to collect large amounts of of customer data A close analysis of of the three examples given above reveals a a a a very intriguing insight – each industry by leveraging a a specific technology is addressing one one part of the Data Monetization puzzle – Retail is solving the ‘data collection’ puzzle using IoT Financial services is solving the ‘data storage’ puzzle with Data Lakes and Telecom is solving the ‘data processing’ puzzle with AI/ML Now imagine an an an organization that can bring together all of these imagine the the outcomes it would be able to drive While technology addresses feasibility business models address viability Despite their strategist’s convictions business’s enthusiasm for data monetization initiatives 12 Data-powered Innovation Review I I ©2020 Capgemini All rights reserved 

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