Telecom Asia: Big Data seems to be the hottest buzz phrase in the tech world, why do you think it has attracted so much attention in 2012?
Ian Watterson: The explosion of mobile data from smart handsets, mobile applications and faster networks has resulted in a really fascinating change in perception of data analysis: numbers and statistics have become interesting!
Competing successfully in today's marketplace means operators have to dive deep into their data to understand the who, why, how, when and what of their customers.
To survive in this competitive landscape, one cannot be content with taking information at face value or basing decisions on just experience or intuition. We want (and need) to be able to quantify decisions with real information and you don't get much more real than what you learn from your own customers' habits. It's not only intriguing, it also has the potential to transform business decision-making models and processes as we know it.
The likes of Google have shown how a successful business model can be built on an obsessive focus on understanding trends in customer data. Advertising spend is driving many new economy businesses like Facebook to advance new models of how to extract value from customer data. It certainly feels as though there isn't a thing in the world that can't be measured and monitored. This is exciting but has also led to degrees of uncertainty as individuals consider the impact this has on their privacy and corporations consider the ROI they will need to justify the incredible amount of time, energy and money they will need to throw at managing it. It is this combination that I think has led to Big Data gaining a significant amount of airtime in 2012.
The term Big Data is essentially used to describe data sets whose size and complexity are behind the capabilities of commonly used software tools. How does one categorise data as "big"?
Leading research on the topic from the likes of Forrester and Frost & Sullivan use a common framework to describe data as "big", i.e. measuring excessively in at least one dimension of volume, velocity and variety. These dimensions are called the "Three Vs" of Big Data.
In reality, the problems associated with Big Data are large in more than one of these dimensions.
Big Data is certainly seen as a big challenge for all communications service providers (CSPs) due to its sheer size and increasing complexity. It does, however, present big opportunities. How would you describe both these challenges and opportunities?
There is no doubt that Big Data presents enormous strategic and operational business challenges particularly when it comes to storage. Businesses are struggling to keep up with digital's staggering rate of growth.
The biggest challenge of all is not whether one should capitalize on the wealth of information that is available; it's how to be intelligent about it. How not to ‘break the bank' and how to keep your business efficient in the process of collecting and analysing data are the million dollar questions that no one seems to have adequately (or openly) answered just yet.
Importantly, this scientific approach allows companies to better understand their customers as individuals, which can facilitate smarter decisions, trim costs and increase revenue.
According to IDC, the market for Big Data solutions (including networks, servers, storage, systems and services) is growing at almost 40% annually. How much emphasis will CSPs need to place on keeping up with the pace of this rapidly growing market?
The reality is data can be monetized. If the CSPs can implement the most efficient way to do this and improve its marketing, customer satisfaction, customer experiences, partner-sharing, its profit margins will be rewarded accordingly.
Investing resources in the collection and analysis of big data is high on the priority list for the vast majority of CSPs across Asia Pacific and indeed the globe.
For many industries, Big Data has the ability to turn traditional methods of competition on its head. What are your thoughts on the competitive advantage that analyzing Big Data creates?
Analysing Big Data primarily results in a better understanding of one's customers, allowing more personalized marketing and customer service, which in turn drives new revenue and reduces churn. It can also facilitate a better understanding of supply chains, employees, suppliers and distributors. The science behind these areas of the business can, for example, optimise risk management, enhance workforce allocations, improve pricing strategies and enable better collaboration with external stakeholders.
For CSPs, above and beyond the network, Big Data means the need to manage extreme growth in subscriber data usage, carefully manage investments in expanded capacity, and ultimately find ways to process network records more efficiently to ensure that potential revenue leaks are plugged and profits maximized. CSPs really cannot afford to miss the boat on this one. The opportunity costs are far too high.
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