Big data projects that revolve around exploiting data for business optimization and business development are top of mind for most executives. However, up to 85% of big data projects fail, often because executives cannot accurately assess project risks at the outset. We argue that the success of data projects is largely determined by four important components — data, autonomy, technology, and accountability — or, simply put, by the four D.A.T.A. questions. These questions originate from our four-year research project on big data commercialization.
Use This Framework to Predict the Success of Your Big Data Project
Up to 85% of big data projects fail, often because executives cannot accurately assess project risks at the outset. But a new research project offers some guidelines and questions to ask yourself before launching a new big data initiative to help predict its success. Access to data is obviously a precondition for any initiative focused on data-driven growth. However, not all available data is useful, nor is it unique and exclusive. Moreover, not all data is available. The question executives need to ask is “Can we access data that is valuable and rare?”. If the answer is yes, you then need to ask: “Can employees use data to create solutions on their own?” and “Can our technology deliver the solution?” And finally, “Is our solution compliant with laws and ethics?” Little value can be created if your solution breaks the law. Moreover, if users think of the solution as “creepy,” you might face a media backlash. Try this structured approach to predict the success of your next big data project.