The Retail Data Overload –Sifting through the Clutter

Retail data – Boon or bane?

Retail organizations are experiencing a phenomenal growth in data. Staying on top of the volume, variety and velocity of the data, and being able to analyze it and deploy the intelligence, is enabling organizations to create a sharp competitive edge. How retail organizations handle this avalanche of data will determine if they rise above competition or get buried. Data – Big Data as it is popularly called — is providing retailers new insights into improving customer intimacy and bringing about innovations in PLM, sourcing and supply chains, leading to improved bottom lines. 

So powerful is the ability of Big Data to influence business that a recent McKinsey Global Institute (MGI) report suggested that the use of Big Data and analytics in the US could increase annual GDP in retail and manufacturing by up to US$ 325 billion in 2020i . One recent IDC prediction suggests that “retailers will narrow and enable big data and analytics (BDA) projects in 2014 as 20%-30% of projects fell short in 2013”ii. It is evident that there is an urgent focus on data management. In reality, how are retail organizations doing? Are they capitalizing on data? What data are they able to capture? How many are able to derive timely and usable insights from the data? Which data brings them the highest ROI? How can retail organizations ensure they invest in only relevant data? 

To find the answers to these vexing questions, O2 Technologies commissioned the Economist Intelligence Unit (EIU) to examine how retailers are responding to the emerging data-rich landscape, its role in shaping customer experience, the benefits derived in delivering omni-channel commerce, enhancing corporate strategy and meeting regulatory challenges. The study, called The Data Storm – Retail and the Big Data Revolutioniii, was based on C-suite responses from retailers based in North America, Europe and Asia. Among the key findings of the study was the fact that many retailers are still floundering at the very early stages of using Big Data. Only 46% of retail CXOs said they were confi dent that their firm’s analytical abilities were keeping up with data volumes. Significantly – and this is where we need to stop and ponder a while — just 36% believed that they had a well-defined policy for analyzing the most valuable information. As many as 30 percent admitted that they are not consistently obtaining value from it. Clearly, while data is flooding every business function – from production to sales and marketing, store operations, e-commerce/ m-commerce, human resource management, back office and logistics — retailers are stumbling when it comes to leveraging the opportunities it offers.

What to do with all this data? What’s good, what’s not?

There are two key questions facing retailers:

  • What should Big Data be used for? Or, what are the priorities to be set with regard to securing Big Data and leveraging it?
  • How can technology be used to reduce and manage data overload without compromising outcomes?

Even before those questions can be answered, many retailers need to understand that their current data management strategies will not be able to scale to meet the velocity and variety of Big Data. An IDC report in 2012 said that the digital universe will double every two years – largely thanks to the availability of cheap sensors and the propensity of the “always on” generation to record, share and store every moment in great detail. Data, said the report, will grow from levels of 130 exabytes in 2005 to 40 trillion gigabytes by 2020 – or what is otherwise by a factor of 300iv. Is it worth sifting through all the available data? Which data is good for business? Which data is required today in real time? 

Growing data sources in retail

The retail industry has seen a surge in the collection of customer information, operations data and sales/ marketing data. Estimates suggest that about half this data is unstructured.

Structured Data for retail:

  • Customer transactions
  • Credit card history
  • ATMs
  • Loyalty management
  • Syndicated data
  • CRM
  • ERP
  • Supply Chains
  • RFID
  • GPS
  • Online click stream
  • Mobile interaction
  • Surveys
  • Weather and traffic updates
  • Customer location

Unstructured Data for retail:

  • Social media
  • Blogs
  • RSS feeds
  • Video
  • Audio
  • Instant messengers
  • Emails
  • Phone calls

Which data is required for strategic growth? These are the questions that the retail industry needs to ponder.

The EIU study digs into these questions to provide early pointers into the business functions that can be impacted using Big Data (see Table 1). However, according to the study, retailers are itching to build corporate strategy using Big Data (60% over the next two years as opposed to 40% in the past two years).

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