Getting big results with small data
Over the past few years, much has been written and discussed regarding “Big Data” – how to get it and how to use it. While the concept of “Big Data” is relatively straightforward, the practical application is anything but.
The concept behind Big Data is to consolidate information from a myriad of sources to provide insight on an individual’s needs, attitudes and behaviors to facilitate highly focused sales and marketing activities. While this is not a new approach – marketers have been using available data for years to inform their programs – the amount and type of data available has expanded exponentially as has the technology capable of collecting, storing and analyzing this vast amount of information.
Without a doubt, these new information technology capabilities offer exciting opportunities to obtain a deeper and more sophisticated understanding of customer behavior, develop highly targeted business strategies, and inform financial and risk management decisions. However, Big Data programs do not come without significant costs and risk. For example, these programs entail a significant investment of money and manpower that exceeds the resources and capabilities of most institutions. Moreover, the effectiveness of these programs relies primarily on the validity of the assumptions used to build algorithms to create predictive models. Yet, the sheer number and diversity of the types of data points used in these models make them extremely difficult to validate.
Fortunately, such an extensive undertaking is not necessary to obtain meaningful insights that executives can utilize to improve business performance. The resources of most banks should be devoted instead to more manageable and cost-effective data analytics that will yield more immediate benefits and measurable results.
Improved analytics are crucial to profitability and growth. The key is to develop simple but powerful analytics that provide meaningful and actionable information on the major components of a bank’s operations: financial performance, customer and market profiles and opportunities, operational efficiency and delivery channel optimization. Importantly, these types of analytics do not require sophisticated algorithms, new technology systems, and excessive burdens on IT resources. Further, this data can be augmented with industry benchmarks and market demographics that are readily obtained from third-party providers.
Here are five of these key Small Data analytics:
Financial performance. Many bank executives use peer group financial data to compare performance against peers, set high-level financial targets and establish contribution targets for individual business strategies and investments. However, the comparison must go beyond high-level performance measures such as return on equity or net interest margin. To be most effective, it must also include the drivers of performance, such as deposit mix and growth, the composition of earning assets and operational efficiency metrics. A separate comparison should also be made to a group of high performing banks. Case studies of selected high-performing banks can be developed to fully understand their business strategies, market focus and operating environments.
Customer. The customer franchise is a bank’s most valuable asset and most banks have a considerable amount of available information on their current consumer and commercial customer bases, such as product usage, balance levels, delivery channel activity, attrition rates and risk profiles. The challenge is to organize this data into metrics that can help identify customer acquisition, cross-selling and retention opportunities, and then use it to drive individual marketing approaches, sales activities and customer relationship management decisions. Industry benchmarks are available on a number of these customer metrics and can be used to establish realistic performance improvement objectives and targets.
Market. A bank’s strategy and performance is heavily influenced by the size, scope, composition and vitality of the markets it serves. Therefore, it is important to develop profiles of the geographic markets in which the bank competes to drive business strategies and identify growth opportunities and priorities. Ideally, the profile would include information on economic and demographic characteristics, projected growth, concentration of customers that falls within targeted segments, financial product usage behavior and the type and intensity of competition within the market. The bank’s customer base and competitive position can be compared to the profiles of each market and growth opportunities can be calculated by segment and product. This analysis highlights the markets, products, and segments where the bank may be underpenetrated and will help to inform business strategies and establish priorities for customer acquisition, cross-sell and retention programs.
Similarly, market analytics should be performed for the trade areas of each of the bank’s branch offices. This analysis may be used to inform sales goals and staffing decisions.
Operational. Improving both productivity and efficiency is essential for increasing financial performance. Fortunately, most banks have a considerable amount of existing data that can be collected, organized and analyzed to identify efficiency opportunities and track performance. This can be accomplished by calculating a limited number of metrics for each major support and customer-facing function and conducting a variance analysis to industry benchmarks. The goal of the analysis is to identify where the bank appears to have a significant unfavorable variance to industry norms and help to inform and prioritize opportunities for improvement in both productivity and efficiency.
Channel and sales. It is not only possible but necessary to analyze the performance of each branch office in the context of the characteristics of, and opportunity within, its trade area. Performance data for each branch can be gathered that measures sales and service activity, financial performance, operating expenses, staffing levels and composition and branch activity. The combination of branch performance and market analytics enables management to make informed decisions regarding the allocation of marketing spending, staffing levels and where to close, open or reconfigure offices. A separate analysis may be conducted to calculate the percentage of bank customers who are active mobile and internet banking users. These usage rates can be compared to industry norms and the analysis used to create effective marketing strategies and programs.
These five simple analytics are relatively easy to build and provide crucial information for managers, investors and merger partners. For most bankers, it makes more sense to invest in better ways to use Small Data than in extremely expensive and unproven Big Data programs.
Mr. Hanley is a partner and Mr. Johannsen a senior consulting associate with Washington, D.C.-based Capital Performance Group, LLC. They can be reached at [email protected] and [email protected] respectively.