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Why is ‘big data’ such a huge issue for retailers?

Monday September 24 2012

Hosted data expert Ivan Gunatillek explores why the amount of data generated by retailers in their operations and interactions with consumers is becoming an issue that is too big to ignore

Hosted data expert Ivan Gunatillek explores why the amount of data generated by retailers in their operations and interactions with consumers is becoming an issue that is too big to ignore


Ivan Gunatillek, managing director of telecoms and hosting provider Easynet, is keen to highlight how his company’s corporate networks carry hundreds of applications which use and create vast amounts of data each day: video applications, line-of-business applications, collaboration software, customer relationship management (CRM), enterprise resource planning (ERP), cloud software-as-a-service (SaaS) applications – the list, he said, goes on and on.


‘Big data,’ and its effective management, however, does not refer purely to vast quantities of internal and external data. It is about bringing together the sheer volume of data, the diversity of types of information and using it to get the required results, all in good time. Gunatillek told Retail Technology: “For retailers, big data is a big issue but also a huge opportunity.”


Managing disparate information


Retailers have disparate locations, manage numerous suppliers, operate multiple systems, and collect huge amounts of customer data. “Now, retailers and consumers alike know the power of customer intelligence, and how it can enhance the shopping experience, increase spend, improve loyalty and drive improved stock management, as well as form the basis for an effective logistics strategy,” he continued.


“In fact, many a savvy shopper now uses scanners such as RedLaser and ShopSavvy and actively seeks out vouchers and discounts, happily exchanging personal data with a diversity of retailers or specialist voucher websites in return for money-saving offers.”


This is great news for retailers in tune with customer spending who can deliver tightly targeted, cost-effective campaigns to a more responsive customer base, but Gunatillek warned that this data is a prized possession and that retailers should treat it as such, and make sure they have the tools, systems and processes in place to manage and protect it. “A big data management strategy should be meticulously planned, revised and revisited,” he stated.


Optimising data management strategy


“The bigger and more diverse data becomes, the more important it is for us to ensure it is secured and managed appropriately; and the more important it is to understand its origin, its importance, its size, its use and its journey, then to act accordingly,” advised the Easynet chief. “Without this knowledge we are making ill-informed decisions and putting our operations, and our customers, at risk.”


Gunatillek shared his top ten tips for managing big data in retail:


1. Understand what’s going on: ensure you have visibility by monitoring those applications that flow across your corporate network and the bandwidth they consume, and act on the results.


2. Prioritise: certain kinds of data and applications – such as stock management and pricing applications – are business-critical; others are not. Give priority to business-critical applications on your network, and let other applications take a back seat.


3. Be secure: once you have an in-depth understand of application performance on your network, minimise risk, check your network SLAs and change them if necessary. Data is precious, so protect it.


4. Consider the cloud: the cloud is a perfect fit for retailers, with the flexibility to adapt to seasonal spikes in performance, to respond to unforeseen consumer demand and enabling just-in-time provisioning.


5. Futureproof your systems: make sure you have the correct tools, systems and processes in place for forecasting, pricing and behavioural data. If you can, invest in tools to ensure your data is accurate, current, clean and precise.


6. Partner up: ask the experts if you need to. Talk to infrastructure owners, cloud integrators and storage vendors – potentially different types of storage for different types of data – and consider those companies running big data analytics platforms.


7. Brief your staff and have clear guidelines in place: a social media policy could help remove the pressure from the network and contain the vast amounts of data being shared.


8. Ensure your business is compliant: keep up to date with the European Commission’s legislative proposals, use the opportunity to demonstrate best practice and aim for ISO standards.


9. Drill down into your specific industry requirement and ensure any partners demonstrate a real understanding of your sector and its challenges.


10. Finally, accept that data is going to keep on growing in size, diversity and source. Embrace the opportunity!