If companies are to maximize the benefits of D&A, then the process of collecting and analyzing data has to be integrated into the business. The managers of the business cannot be expected to know how to collate and analyze terabytes of data, but they need to know what business questions can best be answered by D&A. From a myriad of possible questions, the business needs to select which ones are likeliest to lead to business improvements and which questions are likely to produce a lot of usable data. D&A has developed quickly in recent years, particularly in the analysis of unstructured data, but there are many areas of business where the data is patchy and expensive to gather.
Optimizing the use of D&A requires business managers to work closely with D&A specialists, formulating the best questions and then using the answers supplied by D&A to make better business decisions. By continually improving the way D&A initiatives are carried out, the better the results and the greater the level of support from senior management. Without encouragement from a well-informed cadre of senior executives, D&A is likely to lead to only slow improvements in the management of risk and performance, or, worse still, a series of wrong turns.
Energy companies have many of the building blocks in place to capitalize on D&A.However, they often lack the higher-order functions, such as data mining capabilities and data-focused strategies, required to realize the promise that investors and analysts believe D&A holds for the energy sector.