The most popular and comprehensive Open Source ECM platform
Let us know more
Big Data: Successful Big Data Projects Focus on Business Requirements
How do you measure success with Big Data? One metric clearly is whether or not the projects Big Data is used with are profitable. A recent study of Big Data projects by Capgemini found that less than one third of the projects aren’t profitable. Many of the projects studied had to do with customer satisfaction and retention. Part of the blame for the low measure of success may be with who is running the project. Executive leaders that are closer to the business rather than to the technology tend to have more success. COO and CDO-led Big Data projects tend to be twice as likely to be profitable compared to CIO-led projects.
Mark Powell, UK head of insights and data at Capgemini, said that “in order for Big Data to truly take off, businesses need to stop looking at it on a project-by-project basis and something just for the CIO to deal with. Big data needs to be integrated into every aspect of the business, helping to drive the next level of digital transformation and, more importantly, business transformation. Integrating it in the overall business strategy helps to transform the entire business and open further opportunities across the board, rather than just from an IT perspective.”
John Brahim, Head of Capgemini’s Insights and Data Global Practice, said that “clearly the key battleground is in the leadership of initiatives, echoing what we’ve witnessed in Digital Transformation… many organizations have some way to go before they become truly insights-driven, with budget constraints and integration highlighted as significant challenges in fully operationalizing Big Data.”
How can businesses turn around their Big Data projects? The Capgemini report suggests that businesses should focus on the following:
- High-level executive sponsorship of the project is crucial
- Existing data warehousing software should be modernized and new Big Data technologies should be adopted
- Data governance, security and quality should be the focus for improvement
- The business should try to adopt a data-driven culture at all levels of the organization
