Generating actionable growth strategies with data at traditional banks requires agility, small data and a diverse culture.
“Data insights” generally holds a negative connation for banking executives. While they—and other business leaders—have invested in data analytics to help inform decision making and uncover new sources of growth, many wait lengthy periods of time to receive accurate results. Even then, executives lack confidence in the numbers and depend on familiar analytics methods to make decisions.
To reap the rewards of data and analytics, and to build trust in the advanced insights, banks need to implement three simple actions:
Complex problems don’t always require complex technological solutions. In agile software development, companies take advantage of sprints, or brief, intensive work phrases that deliver results fasters and with higher quality than traditional “waterfall” methods. Teams start on a single-use case, use hypothesis-driven analysis, and focus on 90 percent accuracy. By breaking the work into short-term projects—one for collecting and cleaning data, a second to identify key variables, a third to model the data, and a fourth to run analysis—teams see greater success than waiting months for higher accuracy.
Survey respondents believe 65 percent of their business problems can be solved with “small data,” which has less complexity and provides faster insights. Small-data projects deliver insights in weeks, not months, and allows banks to test more hypotheses and use cases within a year. With an increased number of ideas explored through data analytics with a portfolio approach to generating insights, banks can increase their economic potential and find success (as well as support) for their data efforts.
Bank executives need to trust the insights data produces in order to see and seize economic benefits, and this requires IT and the business to work side-by-side. While technological know-how would also help business executives to understand and trust in data insights, a quicker and more holistic approach is for IT and business leaders to solve problems together with data analysis. While IT leaders capture the necessary insights, business leaders become familiar with the approach and how to draw conclusions and actionable items from them. Each successful project generates significant momentum, and each cycle fosters additional value.
By approaching data analytics in a different way—smaller, more agile, faster and scalable—banks and other organizations can start to get the benefits of advanced analytics without having to wait for big data projects to deliver. But how do you start? Our Growth Strategy project is agile and can be completed in six weeks or less.
KPMG’s Banking Strategy mobilizes small squads of highly skilled professionals in data, analytics, and business domains to deliver strategic insights projects. Our data scientists utilize proprietary machine learning/analytics tools that have been refined through more than 2,500 client engagements to uncover deeper insights at deal speed from more than 250 sources.
Learn how to think fast, small, and agile to achieve big wins with your analytics projects in “Banking on data analytics? Think fast.”