Wish you all a Happy New year! Value creation from data will be one of the central business themes for this decade and ultimately, it is all about data!
Blooming businesses generate data at the speed of light. Data, however, is just a starting point. It needs active harnessing and effective analysis to fuel an organization's growth. Like abundantly available sunlight can sufficiently supply energy to the entire world but is used only for specific energy requirements, data too has vast untapped potential. Businesses need to better channelize data to ensure the smooth functioning of their analytics engine, which in turn churns out the insights necessary to spearhead further advancement.
The current approach to data collection and management poses the following challenges that need to be overcome to tap into its massive potential.
Data Collection
Love at first insight.
While data may be overflowing in digital businesses like telecom, e-commerce, and banking, most conventional businesses are still struggling to collect valuable data about customers. Organizational data collection practices are either non-existent or not in order. Moreover, awareness about value-based data collection, i.e., data that can and should be collected, is lacking. Often, data from external sources, e.g., market research, competitors, and partners, is also missing. As we move forward, data needs to be treated as a strategic asset as opposed to an IT liability, and new sources of data need to be discovered and nurtured.
Data Digitization
It's all in the cloud.
While a hundred percent shift to digital might not be possible for every business, technology like intelligent automation and optical character recognition (OCR) has been a game-changer. They enable direct conversion of physical printouts, hand-written forms, invoices, receipts, etc. into usable forms. A lot of research in areas of Intelligent Automation and OCR tools has accelerated digitization. Further, there is a need to create centralized data repositories, moving away from functional and regional silos.
This has led to the creation of data lakes and data warehouses in some organizations though one needs to be careful to map out the right data to be centralized with requisite quality to ensure data value creation without burdening the IT infrastructure.
Unstructured Data
Life is messy, but data doesn't need to be.
Unstructured data in an enterprise adds up to about eighty percent of the total. This is exactly where most deep learning and neural networks are being used. Data, in the form of text and images, is finding some interesting applications in chatbots, computer vision, automation, and fraud detection, but is often overlooked. Organizations need to move beyond legacy transactions and record-keeping to fully leverage data-potential.
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