The 4th ‘V’ of Big Data and why it matters

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  We have recently discussed the importance of the 3 V’s of Big data, Velocity, Volume and Variety but, what about ‘the 4th V‘ which is information VALUE? A case of more haste less speed? How can we possibly embark on a Big Data project in the manner of Captain Kirk and the Starship Enterprise […]

 

We have recently discussed the importance of the 3 V’s of Big data, Velocity, Volume and Variety but, what about ‘the 4th V‘ which is information VALUE?

A case of more haste less speed?

How can we possibly embark on a Big Data project in the manner of Captain Kirk and the Starship Enterprise – ‘To boldly go where no-one has gone before’ without considering what we are trying to achieve first? Kirk was after interplanetary peace, what are you trying to achieve?

The emerging field of Big Data complete with a ‘shiny new toolkit’ for processing increasingly varied information in greater quantities and at greater speed than ever before, raises the age-old pitfalls of the corporate rush to ‘be at the technology races’ and, drives a ‘build it and they will come’ mentality to be progressive in the market place sooner rather than later. Whoa there! STOP!

Avoid ‘all of the data, all of the time’

As discussed late last year, it should be ‘Right Data not Big Data‘. Before you embark on any Big data project consider achieving value from one (or more) of the follow perspectives.

  • CEO focus on the Information that has most potential value to your organisation

This requires analysis of the current information gaps in your organisation against a MoSCoW rating to determine the priority and potential benefit of specific management information against the current business strategy. Its a case of good old fashioned hard work I am afraid, with no technology short-cuts whatsoever. It will also require agreement and buy-in from each line-of-business stakeholder.

  • CIO consideration of the key information that has most potential value in terms of customer interaction

This will require internal consideration of your perceived product/service gaps against the competition, alongside Big data analytics which take external information from the call centres, website interactions and social media feeds to determine relevant themes from a brand sentiment perspective. Combining these two perspectives should provide a potential route to your organisations ‘differentiation’ in the market place.

  • CFO priorities for the potential information value in terms of operational service efficiencies

This will require internal consideration of your process inefficiencies from an employee perspective, reconciled against external Big data analytics analysing customer experience from a customer perspective. Combining this information should identify potential changes to core processes that truly impact the customer experience and indeed the bottom-line.

Agility is a journey not a destination and its powered by Big Data!

Big data activities should be executed on an ongoing basis to keep ahead of the competition. Example Big data use cases such as ‘next best course of action‘ are intrinsically value-based in nature (and the customer is not necessarily always right!) and, at each point in the process ask the same key question:

‘What should I do next to keep to ensure I service my customer effectively?’

The future leaders in Big data adoption will embed this type of analysis into the very fabric of their customer impacting processes on a business as usual basis. Customer experience may be King but, effective Big data strategy is his armory.

Big data will have an increasingly important role to play in maintaining customer loyalty, increasing business agility and, reducing the cost to service but, don’t forget to focus on the value first.

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