Big Context Versus Big Data – Changing The Way We Examine Company Information

The CEO of ISC has been quoted as saying that “the explosion of big data is crippling,” and in a way he is quite correct. As we often see today, rather than improving your business, having too much information can leave business leaders completely unable to make a decision, faced with too many choices and too much to get their heads around.

A large part of the ‘big data’ problem lies in hiring in the skills necessary to make head or tail of the ton of information churned out on a daily basis by today’s businesses. Most businesses haven’t made a habit of hiring Math’s PhD graduates, yet that’s the level of understanding needed to ‘read the entrails’ of big data. Leadership needs to go further than this though – even if there were enough Math’s PhDs available for hire for every business – which there aren’t – translating the data they extract into actual business decisions requires a huge leap of faith from senior management.

More worryingly for me however, is the fact that the entire concept of ‘big data’ and how we examine company information is being examined wrongly. Many companies appear to be using big data as a prediction tool, and yet the ability to predict behaviour doesn’t necessarily lead to better business decisions. Big data might show you what will happen but it can’t tell you why, just that it is and will. Businesses should not be looking to track patterns of behaviour, but to see the wider context around those patterns – this is something I call ‘big context’.

The brilliance about having access to so much information is using it to understand why something is happening, how it is happening and what it means for the business. Ultimately, every business only succeeds by serving the needs of its end customer – but many companies are losing sight of this by pushing all their resources into big data warehousing.

Unfortunately, big data often neglects the individual customer. Massive volumes of information are pulled together to create “trends” that then drive a company’s business strategy. At a time when customers are demanding more personalised services, this approach gives them the exact opposite of a personalised customer experience by grouping them into “customer types” rather than treating them on a case by case basis.

So what is the solution for companies looking to turn their mountains of data into actionable information? Start small and work up. By focusing on a specific challenge and the associated ‘small data’ set, you can capture the most important bits of knowledge available – the “know-how” – and disregard unnecessary pieces of information that do not add value for the company or end-user.

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