Big Data – Extracting Value

 “Most companies only capitalise on 5% of their in-house data”

This was the message at the leading Big Data Summit 2012. In a presentation from Forrester Research it was identified that most financial organisations are unable to extract and exploit the true value from the vast amounts of information they hold.

Big Data is often used to describe the vast data sets that are too large and too complex to be processed by conventional means. In a previous post (, I defined Big Data as

Volume – from hundreds of terabytes to petabytes, where a petabyte is equivalent to 500 billion pages of standard printed text.

Velocity – up to near real time sub second delivery

Variety – including both structured and unstructured data

Volatility – hundreds of new data sources coming online from new apps, web services and social networks

The key focus for Big Data is Value in order to drive new competitive insights.

Value – the opportunity to define new operating models and products based on customer insight and intelligence

In this post we will discuss how to increase value from Big Data to enable companies to utilise more that 5% of their data assets and directly increase customer insight, intelligence and information to drive competitive advantage.

Extracting Value
At the Big Data Summit 2012, Holger Kisker (Principal Analyst, Forrester) reported that companies are unable to extract value and exploit commercial insight from the vast amounts of data they hold on products, customers, research and market trends.

Looking at this in more detail, the volume of data available is truly staggering and is measured in Zeta bytes (1021 , bytes) as illustrated in the following schematic.

Source: Sept 20, 2011, “Understanding The Business Intelligence Growth Opportunity” Forrester report

The vast majority of information available to companies is historical data. This comprises of the traditional reporting, such as structured databases and reports, as well as the unstructured data that is available both internally and external to the organisation in the form of emails, phone calls and online content. This historical information far exceeds the information being generated now and in the future.

To be successful in this new data world, financial institutions have to realise that they are in the data business and that data is their biggest asset.

Dark Data
The vast majority of information is dark data – this is data that is either under-utilised or mothballed.

In a world where we are over run by dark data, whether it is social, machine data or location data, the ability to extract value and develop new products and operating models based on deep customer insight and intelligence represents a new form of competitive advantage.

Value is focused on forecasting, trend spotting, developing new products or detecting fraud in real time. Underpinning this is the ability to build a 720◦ view of your customer.

The 720◦ Customer

To capitalise on company data, organisations need to extend the internal customer view to include an external perspective. Specifically, organisations need to build a 720◦ view of their customers to unify the internal view with the client’s external social and influencing network, such as Facebook and Twitter.

As an example, British Airways is delivering a targeted and personal touch through its “Know Me” programme by researching passengers and building a unified view of the customer. The “Know Me” programme will use Google images to find pictures of passengers so that staff can welcome them by name as they arrive at the terminal or plane. This is the kind of individual service, providing a unique and personal experience, that we all aspire to receive.

By building a 720◦ view of their customer, companies such as British Airways will drive new opportunities for revenue uplift through mass customisation, offering benefits such as individual prices and targeted offerings based on predicted behaviours and location based services.

Data Exhaust

An exciting by product of Big Data is Data Exhaust. This is the unstructured information that is a by-product of the online activities.

Google applies the principle of data exhaust to many of its services. In a world where Microsoft spent several million dollars developing a spell checker, Google developed a leading spell checker , in every language, based on the mis-spellings typed into its search engine. The Google spell checker was developed on the by product of Data Exhaust from its online search engine.

Collecting and analyzing data exhaust can provide valuable commercial insight into the behaviour, actions and aspirations of your clients. Re-using data exhaust to improve a service or create a new product will be a new form of competitive advantage for those organisations embracing Big Data.

The debate on Big Data is often focused on the underlying data volumes or the new innovative tools and techniques. As I’ve highlighted here, the real opportunity and critical success factor is VALUE – how to extract value and exploit the information to enable better informed decisions and strategic outcomes.

Only by pulling data together from different structured and unstructured sources and developing new ways of processing, such as the 720◦ Customer and Data Exhaust, can organisations successfully develop new seams of competitive advantage and harness the 95% of untapped Big Data resources.

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