It’s a value proposition too good for organizations to pass up — taking the massive amounts of data they are accumulating inside and outside their walls, and mining for diamonds of information amidst many endless veins of coal. Unfortunately, the diamonds may be tiny and very difficult to find.
Companies are actually making progress with organizing and sifting through their internal data, such as call center interactions, sales transactions, and product levels. However, they’re not ready for external information. And, ultimately, what makes Big Data big data is external web information, especially social media. However, most organizations are leery about the validity or trustworthiness of such data.
These are the conclusions of a report just released by IBM and the Saïd Business School at the University of Oxford, based on a global survey of 1,144 business and IT professionals. Three-quarters (76%) of the respondents are currently engaged in Big Data development efforts, mostly in the early stages.
Most Big Data initiatives currently being deployed by organizations are aimed at improving the customer experience. Yet, despite the strong focus on the customer, fewer than half of the organizations engaged in active Big Data initiatives are currently collecting and analyzing external sources of data, such as social media. That’s because business leaders feel there is uncertainty inherent within certain types of data, such as the weather, the economy, or the sentiment and truthfulness of people expressed on social networks. In the survey, respondents questioned their ability to trust comments, reviews, tweets and other forms of freely offered opinions online.
As the report states: “Sentiment and truthfulness in humans; GPS sensors bouncing among the skyscrapers of Manhattan; weather conditions; economic factors; and the future. When dealing with these types of data, no amount of data cleansing can correct for it. Yet despite uncertainty, the data still contains valuable information. The need to acknowledge and embrace this uncertainty is a hallmark of Big Data.”
The second major challenge is a growing skills gap when it comes to finding people who know how to manage and mine this data, the survey finds. Only 25% of the survey respondents say they have the required capabilities to analyze highly unstructured data – a major inhibitor to getting the most value from Big Data. Big Data requires the capability to analyze semi-structured and unstructured data, including a variety of data types that may be entirely new for many organizations. Having the advanced capabilities required to analyze unstructured data – data that does not fit in traditional databases such as text, sensor data, geospatial data, audio, images and video – as well as streaming data remains a major challenge for most organizations.
Survey respondents report a range of business opportunities and benefits as a result of their Big Data projects. Nearly two-thirds (63%) of the survey respondents report that using information, including Big Data, and analytics is “creating a competitive advantage” for their organizations. This is a 70% increase from the 37% who cited a competitive advantage in a 2010 IBM study.
More than half of the survey respondents reported internal data — which is typically structured data — as the primary source of Big Data within their organizations. In more than half of the active Big Data efforts, respondents reported using advanced capabilities designed to analyze text in its natural state, such as the transcripts of call center conversations. These analytics include the ability to interpret and understand the nuances of language, such as sentiment, slang and intentions. Such data can help companies, like a bank or telco provider, understand the current mood of a customer and gain valuable insights that can be immediately used to drive customer management strategies.
In addition to customer-centric outcomes, which half (49%) of the respondents identified as a top priority, early applications of Big Data are addressing other functional objectives. Nearly one-fifth (18%) cited optimizing operations as a primary objective. Other Big Data applications are focused on risk and financial management (15%), enabling new business models (14%) and employee collaboration (4%).
(Thumbnail graphic: Joe McKendrick.)
