Slicing and Dicing Big Data for Opportunity

It’s recognized that Big Data not only exists, but that it has great potential to disrupt well-established vertical markets. IBM has commented on information increasing twofold while Cisco predicts that, by 2015, there will be 15 billion connected devices in circulation. While until recently the Big Data phenomenon was hype generated by the technology industry and media, it has been rapidly unfolding and growing behind the scenes.

How do we know this? Because all industries and sectors are now expected to have real-time analysis of what’s happening. In the same way that customer service has evolved to become 24/7, real-time data analysis for better opportunities and spotting anomalies is something that the majority of us take for granted.

Let’s take a couple of examples. In retail, we have come to expect Amazon and other online retailers recommending our next purchase based on prior buying habits. It’s quite telling that Amazon claims 30 percent of its sales are generated as a result of its recommendation engine: “Customers who bought this book also purchased…”

While most consumers now take it for granted that they’ll receive personalized and tailored offers in the retail, utility and telecoms industries, that use of Big Data isn’t as prevalent in other vertical sectors, such as the public sector or government-based industries.

Those industries and vertical sectors should be taking advantage of their easy and available access to customer or industry data. At a time when cost comparison and running as leanly and efficiently as possible is crucial, all companies need to be looking for opportunities where they can also benefit and find growth. And many are.

As mentioned, the retail sector in particular is doing well in analyzing customer behavior and patterns and being able to offer consumers coupons almost in real-time. Two great examples are U.K.-based sandwich shop EAT and retailer giant Sainsbury’s. Using business intelligence technology to pull together data on ingredient purchasing, weather, store visits and staffing, EAT has been able to purchase seasonally and staff according to demand. Sainsbury’s is using Big Data to help set prices nearly in real-time, and shift inventory by giving loyal shoppers customized coupons.

There are definite similarities to be drawn between the retail space and the telecoms and mobile industries. The latter has an advantage in consumer and user data. Thanks to (mostly) long-standing customer relationships, billing history can generate a huge amount of insight on an individual mobile user and his or her habits. This information is so valuable that European mobile giant Telefónica has launched a global Big Data business unit aimed at selling information on customers who use its mobile services. Such initiatives could appeal to the likes of local councils, for example, that want to measure how many people visit the high street after the introduction of free car parking, farmers’ markets or late-night shopping.

However, those initiatives can also result in major privacy concerns for customers and any major business admitting to selling off the data it analyzes. All too often, many businesses aren’t willing to risk customer relationships in return for better knowledge or the chance to further improve service and customer experience.

Another sector where Big Data has huge potential, but also confronts regulatory issues, is in the financial and banking industries. While over 2,500 financial services institutions worldwide have signed up to use business intelligence software, and utilize it to manage risk, meet regulatory compliance, spot growth opportunities and increase margins, there is still far more that could be done if silos were overcome and business users given access to the data for analysis. The route to success with Big Data analysis could be made as simple as possible if it weren’t for complex regulations and an unwillingness to share what is perceived as competitive insight.

Yet it was information asymmetries that led to many utilities and retailers entering the financial services marketplace in the 1990s. They rightly argued that they had more potential information about the customers of the banks than the banks themselves. But the success of these diversification attempts remains to be seen. Recently both Vodafone and Apple claimed they had considered (or were considering) opening banking arms, but that hasn’t yet occurred.

What the Big Data potential does demonstrate, however, is an opportunity for open innovation. By empowering all the users within a business, and the possibility for change, innovative transformation should theoretically become feasible. Not only do organizations in all sectors have to remain agile and be able to adapt quickly in order to stay ahead of the competition in their specific vertical sector, they also have to keep up as companies’ traditional roles evolve. This comes back to the diversification challenge and opportunity—and several failed attempts.

But these information asymmetries also enabling technology companies such as Google and Microsoft to diversify—by moving into the healthcare market, for instance, and allowing customers to track their health and record their treatments. Asymmetries are also driving the Internet of Things: How else do we move from electronics companies creating smart fridges that speak directly to your preferred retailer to order you milk and yogurt when you’ve run out?

Before we get ahead of ourselves and move into the world of the future, let’s consider some other vertical sectors around the world, such as the utility sector, which is embracing Big Data to analyze customer sentiment online and in social networks. Here is an example of where one sector is more advanced in certain regions than others. Utility companies are using data through social media analysis more effectively in the U.S. and Europe than in the U.K. This again shows that there is still more potential to be harnessed, even if only in certain regions.

As we touched on earlier, the private sector has arguably greater license to analyze user patterns to better tailor and personalize services, because customers opt in to a brand. That said, governments and the public sectors around the world are not letting the Big Data opportunity pass them by. Police departments are using computerized mapping and analysis of variables such as historical arrest patterns, paydays, sporting events, rainfall and holidays to try to predict crime ‘hot spots’ and deploy officers there in advance. From Stockholm to the U.K. and across the U.S., police forces are being very effective in managing their resources for better deployment.

Opening up data is key to this, as is being transparent in how data is being stored and analyzed. Which bring us back to what Big Data is and where its responsibility sits. One thing Big Data giant EMC advises against in any case is treating any initiative to address Big Data as an IT issue. While the IT department and so-called data scientists have an important role to play in enabling access to data access and then drawing analysis from multiple rows of data, it is down to the business users to spot anomalies and opportunities from the data available to them. The more we can refer to information and business insights derived from Big Data tools, the better placed we will be to take advantage of what Big Data ultimately enables.

 

Anthony Deighton is CTO at QlikTech.

Image: Cio/Shutterstock.com

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