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Big Data for Retailers is an opportunity they can't afford to lose

I was watching one my company's clients Simon Hawkes, the COO AIMIA and Fiachra Woodman, the IT Director (you can watch the video here at "the future of retail analytics in a world of big data" ) talk about new trends emerging and how the world in the future will be driven by social and mobile channels more than anything else and how the data explosion will pave the way for a new way of consuming and applying analytics. The video is important and pertinent and has set me off on a serious contemplation of how 'data' is important to retailer and how Big Data opening up new opportunities for Retailers. 

Data in corporate entities traditionally stay in 'closet' , to be stored, protected and retrieved.  The IT function as we know today used to be known as EDP- 'electronic data processing'. With data being the center of universe of IT asset, corporations and service providers always tried to treat data as corporate capital attribute rather as a performing asset. The retail industry, distinct from others, has been dependent on several of kinds of data at every step of their business operations and planning. Until recently, forecasting, pricing analysis, business modeling required significant investments in sophisticated technology tools for data extraction, transformation and analysis. Extracting value out of data depended on how sophisticated i.e., expensive, the business planning needed to be. Therefore, there was always a tendency to put data into 'closet' as it was considered expensive and not necessarily an economic currency.

The emergence of unsolicited, (a.k.a 'unstructured data') and available freely outside of corporate domain engendered a market place for 'data'. These data as they reside outside of corporate domain do not require any corporate capital for processing and monetizing. Progressively, three key trends- relevance & growth of data in and outside of corporate domain, the distributed ownership, the viability of distributed computing led to emergence of market place for data. The market place led to raise of several players such as technology providers, valuers, processors, consumers, buyers and sellers. Like in any free market place, the underlying asset came to be valued and monetized by players in the market place. This led to look at data as 'performing asset'.

The growth of data in the retail space is exemplified by the oft repeated example of Wal-Mart's transaction volumes of 1 million/hour translating into 2.5 petabytes of data. In addition many of Wal-Mart consumers' authored blogs providing key pointers to business demand.  Simultaneously, the break- through technologies like (MPP) databases, search-based applications, data-mining grids, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems became main stream.

A case in point in the data economy is about an intermediary who delivered a service using client loyalty data for a very large retail grocery chain. This case involved a retailer/principal owner of structured data providing meta- data regarding consumer purchases to a service provider and the service provider playing the role of an integrator. The intermediary or service provider integrated and processed, at near real time, both retailer owned structured data and publicly authored unstructured data.  The service provider then augmented the integrated data, developed analytics and made available custom demand profiles, demographics, behavioral analytics and preferences on a subscription basis. The supply chain vendors of the principal retailer found the on-demand and near time availability of integrated data profiles very valuable. This has led to complete realization by corporations to view data as a revenue asset. This case is illustrative of realization of an economy that changed data being a passive asset to a source of revenue for multiple partners. In the above case, the retailer and owner of data was the biggest beneficiary as ownership was absolute while processing, storage and distribution costs were distributed and near zero. The realized value translates to tangible improvements in both operating margins and free cash to principal owner of data.

Retailers' upstream & downstream partners, consumers, technology partners form the data market place that provide significant positive impact to retailers operations.

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