posted on November 01, 2012 20:40
Last week I listed a number of studies that we recently released at IBM regarding how businesses are utilizing Big Data and Advanced Analytics to realize increased business value.
Below is a quick re-cap of these studies:
• Demystifying Big Data, A Practical Guide to Transforming the Business of Government, Federal Big Data Commission; October, 2012.
• Analytics: The real world use of big data, IBM Institute for Business Value; October, 2012.
• From Data to Decisions, The Power of Analytics, Partnership for Public Service and IBM; November, 2011.
• From Data to Decision II – Building an Analytics Culture in Federal Agencies, Partnership for Public Service and IBM; October, 2012.
• Government Analytics for Dummies, Larry Miller and Robert Dolan and IBM; 2012.
In this blog, I’ll review Analytics: The real world use of big data, published last month by IBM’s Institute of Business Value and the University of Oxford’s Saïd Business School.
The study is based on a survey conducted by the authors that surveyed 1,144 businesses and IT professionals in 95 countries and interviewing more than academics, subject matter experts, and business executives.
The study defines five key findings as to how organizations are extracting business value out of big data:
1. Customer Analytics are driving big data initiatives
2. Big data is dependent upon a scalable and extensible information foundation
3. Initial big data efforts are focused on gaining insights from existing and new sources of internal data
4. Big data requires strong analytics capabilities
5. The emerging pattern of big data adoption is focused upon delivering measureable business value
In the first key finding, nearly two thirds of the study’s survey respondents reported realizing a competitive advantage out of using big data. This represents a 70 percent increase from just two years ago. And the majority of organizations said that this competitive advantage came from the use of customer analytics.
In addition, customer analytics were used to increase the customer experience. This was consistent between the private and public sector. Nonetheless, an interesting nuance of the study is that only 32 percent of public sector respondents reported that their main driver was customer experience compared to 49 percent of all organizations. That 17 percentage point gap represents the fact that public sector organizations are rallying behind using big data to increase operational efficiency, in such areas as operational optimization, risk and financial management, modifying their business model, and increasing employee collaboration.
The second key finding that big data efforts are built on a solid, flexible information management foundation indicates that organizations are generally taking the concept of information governance seriously. In addition, it was found that since organizations are taking information governance seriously, those organizations that have yet to start a big data initiative do not have a foundation in place for integrated information stores, security, and governance.
Those organizations that have started big data initiatives are also piloting a scalable infrastructure, typically based on Hadoop and NoSQL engines.
Thirdly, organizations are starting their big data initiatives by utilizing their existing stores of untapped, internal information, such as transaction, log, event, and email data. This is consistent with the fact that most organizations are starting with the goal of improving the customer experience. For this data to be useful, it is critical that organizations determine how to combine their “variety” of data.
The fourth key finding highlights that big data requires strong analytics capabilities, in terms of skills and analytics tools. These strong analytics capabilities are critical to create operational insights adequate for action and are typically found. Specifically, these top five skills include:
• Query and reporting
• Data mining
• Data visualization
• Predictive modeling
Most organizations in the study report that there is a significant skills gap in finding the required capabilities for sustainable big data efforts.
Finally, similar to the other studies that I have recently summarized, effective big data efforts focus on delivering measurable business value. Nonetheless, an interesting view of the results is that those organizations that are further along in their efforts in delivering real business value have executive sponsorship.
In connecting all five of these findings, most big data initiatives start utilizing existing data and information infrastructure, and as pilots become more effective, these pilots get the attention of senior management, enabling the final pilot results to realize real business value for organizations.