In all technology trends, there is always the cutting edge and the waiting majority behind them. Why would Big Data be any different?
It’s only sensible; after all, to remain a little cautious and let the early adopters test the waters and discover the difficulties first: then you can take the tried and tested route and get on-board later.
The problem is 40% of the Global 9000— the 9,000 public companies reporting a billion dollars or more in revenue per year across the world — are planning to do nothing Big Data-wise, early, late or ever.
At the end of 2012, my company commissioned an independent survey to investigate what activities the Global 9000 are carrying out around Big Data. A quarter (26%) of survey respondents said that they are working on Big Data projects, a third (34%) are in the evaluating and planning phase – but 40% say they have either not yet evaluated their Big Data needs, or have evaluated but plan not to proceed.
The research probed the rationale behind this non-adoption. Respondents say they have decided against embarking on a Big Data project or are still hesitant because of resources: ‘not enough staff with expertise’ and the ‘expected cost of Big Data initiatives’. These perceived obstacles aside, what’s highly concerning is that there are a wide range of advantages – in particular an exponential leap in understanding customers, which at a stroke should bring an end to wasted marketing efforts – that seem to have evaded the ‘40%’. Why are they unconvinced?
After all for the majority of the Global 9,000 surveyed, who are well advanced in their Big Data preparation, the key motivation is to gain better customer experience analysis. So customer insights, fraud prevention and analysis, market targeting, behavioural analysis, customer lifecycle analysis and operations improvement were all listed by our sample as Big Data aims. In terms of technology, the Big Data apps in use cover customer experience analysis, customer insights, market targeting/decision, capacity forecasting, customer lifecycle management, fraud prevention and analysis, plus network monitoring.
The main point to take from this is that understanding customers better is clearly the major impetus for these first-adopters. The data highlights a set of benefits around this issue for Big Data pioneers, including increased competitive advantage, superior customer targeting, improved efficiency and the ability to make better decisions faster. In short, Big Data first movers are starting to speed past their competitors.
I should add that respondents’ being so definite about what’s driving their Big Data projects is very telling. The key to Big Data success, is we believe, to start with the business problem Big Data analysis might solve – and avoid the ‘architecture for architecture’s sake’ school of thought.
Organisations with the energy and vision to engage with Big Data tell us about the huge business benefit to be gained. The benefit comes from having a far sharper and richer understanding of their customers than they would otherwise.
The competitive intelligence that becomes available about customer purchasing behaviour and personal habits (through, for example, the ability to match similar profiles from social networking sites, as well as to mine sentiments from social media sources and so on) delivers knowledge that is rich, intimate and very useful.
Businesses will be transformed through such knowledge and will be able to make products and services for their customers that are a perfect match. Junk mail and other poorly targeted sales and marketing efforts should be consigned to history. This is a powerful change and explains why Big Data is important.
We mentioned the resource issue, above. Our current listless economy makes big corporate budget commitments uncertain at best, at least for the foreseeable future. However, that doesn’t negate the fact that enterprises really do need to get on-board with Big Data. After all, any skills gap will be short-lived and there are plenty of useful products available to assist companies and to offset the development costs. No reason then to stay one of the ‘40%’ and get left behind.
The author is Vice President of Product Marketing at Actuate (www.actuate.com), an Open Source Business Intelligence (BI) software specialist and the creators of ActuateOne® business analytics and BI development software, and open source reporting platform BIRT. The research referenced was conducted on behalf of Actuate by independent research specialist King Research. Read the full report “Big Data: How Real is it?” at www.actuate.com/info/bigdataresearch