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How big data is solving the biggest, industry-specific issues of the day

We are only as clever as the decisions we make. Those decisions are based on the facts and information that we have to hand at the time. Before, the data used during that process was discarded once the judgment was made.

Not any more.

And this is the key to truly understanding big data. We use the data initially and re-use over and over again to test conclusions, changing our decisions time after time if necessary. We are smarter because we can remake those decisions.

According to IDC, the market for big data will reach $16.9 billion in 2015, growing six times faster than the overall IT market. How can big data be used to solve the business problems that were previously hard to decipher? We have seen a dramatic increase in organisations undertaking digital transformation to help them get more from their data, but how is this delivering to the bottom line?

Big data is all about information. How can we apply and understand very broad, horizontal concepts of big data and apply them to specific industry issues and scenarios? How can big data be used to solve vertical-specific issues?


One of our customers in the travel sector needed to improve their margins. The amount of data needed to present a customer with a multitude of holiday options was slowing the process down.

Customers have to make a number of decisions, selecting from a choice of hotels, flights, car hire options, dates and added extras, to create their ideal holiday. For a typical holiday, there would be over 5 million combinations.

Historically, physical brochures became digital catalogues, but the visibility that the customer needs to make the decision requires a multitude of options. Customers have become much more savvy about finding competitive prices, severely diminishing the margins that the travel industry can expect.

Now travel companies can utilise big data technologies to search non-complex relationships and create dynamic pricing and recommendations with a sub-second response. This helps them take advantage of taxes, fuel and exchange rates to improve their operating margin.


For the automotive industry, big data could optimise products, repairs and maintenance, detecting and fixing issues before new models are launched.

Using diagnostic tools to gain visibility into vehicle performance is not new, but combining this information with a vehicle’s environment and driving patterns could provide an insight never accessible before.

This is transforming the industry, which is shifting from a predominately mechanical-based environment to a software-based one.

This change is reaching all parts of the automotive process from design, where data captured on existing vehicles, will influence issues such as safety, aerodynamics and performance on new vehicles; to the service department, where predictive analysis will help identify problems before they happen.


Big data is enabling us to shift from diagnosing and treating sickness to predicting and preventing illness and disease. Data related to individuals, from both their own sources (such as wearable devices, smartphones and diagnostic kits) and via the NHS and private healthcare providers, is growing exponentially.

By combining this data with genome mapping to predict disease, healthcare could enter a new frontier. Combining data and using technology to streamline it means that healthcare professionals and individuals have the information required to make better decisions Big data could not only reduce hospital visits, but anticipate illness to prevent incapacitation or even death.


It is mind boggling to think how much data there is on individual consumers’ behaviour. How can retailers use this information to ensure that on- and offline transactions are combined, along with conversations and intentions?

Being able to effectively dissect this information will give retailers much better insight into their customer base. Smart retailers successfully use analytics models to influence buying decisions, better understand the supply chain, develop products, set pricing, improve customer retention strategies and cultivate more effective product promotions. Sounds good, doesn’t it?

Well, only If retailers are doing it ‘right’. Set against a backdrop of rapidly changing consumer behaviour, retailers are under pressure to deliver a brilliant and highly personalised service.

The problem is that too many retailers are blinded by ‘big data’ and not planning appropriately. Architecture-led planning or a capability-led road map, developed jointly by the IT and business functions, will help retailers to get the maximum benefit from big data.

Taking this step back to not only gain an enterprise view of the business, but to ensure that every step taken delivers back to a core business function, is an inherent part of the process. Taking huge amounts of data and turning into valuable, analysis of customer behaviour is dramatically changing the retail landscape.

Organisations are increasingly using big data to create better experiences for their customers, creating digital worlds that are easier to navigate. But what big data is really delivering in successful projects is a greater insight, equipping organisations with the ability to make much smarter, data-led decisions.

Problems that were previously hard to decipher can now be solved using data analytics. This is changing the way in which businesses across all industries are understanding and responding to their customers.

Oliver Neuberger, Associate Partner at Glue Reply, is an accomplished technology strategist and consultant with over 12 years’ industry experience.