Do you remember Buzz Lightyear, the character from the movie “Toy Story”? He was the space action figure who believed he was not a toy, but the defender of the galaxies sent to save the universe from the evil Emperor Zurg. His favorite line was “to infinity . . . and beyond.” While I may be stretching things by relating Buzz to the topic of business analytics, read on.

Banks and insurance companies are aggressively increasing the use of and emphasis on business analytics tools. The banking sector is further along on this continuum, but we are also seeing progress on the insurance side. Specific scopes and definitions vary by source, but in simple terms, business analytics is about using software tools to access, extract, and manipulate enterprise-level data to provide new insights into what is driving the performance of the organization. Other terms that overlap with or are synonymous with “business analytics” include “business intelligence,” “business performance management,” and “data mining.” The focus of business analytics can vary depending on the needs of the business. Strategic areas of focus may include improving profitability, customer service, customer retention, and operational effectiveness. Additionally, organizations are using business analytics tools to: develop new business metrics and ratios; segment markets; conduct financial planning, forecasting, and budgeting; detect fraud; and improve risk management. Many organizations are also striving for multidimensional views of costs and profitability, whether by customer, product, distribution channel, process, function, or line of business.

A range of software systems exists in the marketplace today with varying levels of sophistication and capability. Some vendors tout their systems in a “Buzz Lightyear” manner as being able to “save the universe” and take the organization “to infinity . . . and beyond” in terms of new levels of organizational performance. As with many technology investments, however, the tool alone does not automatically create results. We are seeing more and more companies make the right decision to invest in business analytics software, yet many are not effectively using those systems to improve the financial performance of the organization. While each situation is unique, we typically see companies struggle in three primary areas:

  • Not summarizing data in ways that provide clear, actionable insights.
  • Missing the deeper value of financial reporting data by not correlating it with other relevant information such as activity-based costing (ABC) data.
  • Assigning skilled and experienced people to work with business areas to take action based on insights gained from the data.Our work in the business analytics arena targets these trouble spots and implements management practices that drive action. Too often the goal of an analytics program can become “implement analytics.”  Instead, the goal must always be to positively impact operational performance and profitability using analytics as a key tool. Here’s an example of the successful approach taken by one of our large regional banking clients.

A Successful Approach

The executive management team of a super regional bank was looking to significantly improve the quality of their expense and profitability data and to gain new insights from multiple perspectives, such as customer line of business, product, process, and distribution channel. The existing cost accounting system was extremely complex, contained obsolete and incomplete ABC data, and was generally ignored or questioned by business-line leaders. As a result, a comprehensive costing system redesign effort was initiated. A redesign team was established, and a new business analytics software tool was selected. The business analytics tool was to be implemented in parallel with redesign of the costing system so that information could be shared along the way. Key goals of the redesign included:

  • Implement a simplified approach to cost allocations and ABC.
  • Allow ABC data to be gathered quickly across the organization.
  • Develop the capability to create multi-dimensional views of cost and profitability.
  • Evolve the activity-based costing function into a high-impact, activity-based management program that would support re-engineering and other performance improvement initiatives by “doing things right” and “doing the right things.”The redesign team developed functional cost categories including renaming, consolidating, and simplifying cost drivers. The team also simplified and redefined cost layers (i.e., fixed, variable, overhead, etc.). Completion of this initial redesign work provided a base for gathering ABC data that would align with cost drivers. Once this base work was completed, discussions were held to select a pilot area for implementing the new approach. Corporate banking—viewed as a high priority because it was struggling with price competitiveness, suspected overlap between roles, non-value-added work, and stalled revenue growth—was selected. It was also suspected that corporate banking account executives were performing too much administrative work. The approach included the following steps:          
  • Work activities were identified, defined, and validated in terms of elements included for account executives and support staff.
  • Volume sources were identified and volume data gathered from business systems.
  • Electronic ABC time allocation surveys were developed and designed to gather data so that unit, process, product, and function costs could be determined. Thoughtful front-end survey design was essential to achieving the desired richness of information on the back end.    
  • Account executives and support staff in all regions completed surveys, allowing region-specific data to be gathered and summarized in addition to overall data.
  • Results were shared with line-of-business and regional business leaders.The survey results provided some excellent insights. Overall time allocation within the roles was as follows:

At a high level, account executives were spending less than 20% of their time prospecting for new customers. As suspected, the majority of their time—about 55%—was spent on administrative activities, such as handling customer or service issues and transaction processing, resulting in a significant expense at account executive compensation levels. The remaining 25% was spent on underwriting and retaining existing business.

Support staff were spending 75% of their time on account servicing and transaction processing, but with additional investigation, it was determined that a significant portion of this time overlapped with time spent by account executives because of back-and-forth communication and handoffs. This base data prompted a comprehensive redesign of both roles. A “goal state” role design was developed; it had a significantly different time distribution, with account executives spending 50% of their time prospecting rather than 20%. Training was conducted and support roles became a single point of contact for existing customers, eliminating unnecessary handoffs and discussions between the roles. The implementation resulted in additional capacity with no additional staff. The extra capacity in the account executive role was devoted to new-business prospecting. This resulted in significant revenue growth over the next several months. 

Summary

Business analytics tools are providing new insights into the performance of financial services organizations. As the software systems continue to evolve, there is an opportunity for companies to reach higher levels of profitability and operational effectiveness if they have the corresponding management practices in place. Great data does not automatically translate into great results. As your organization builds its business analytics capability, plan carefully to fill the gaps that often hinder the full potential that analytics can enable.
Part II of this series, “From Analytics to Action: A Roadmap to Success,” will offer more examples of how you can effectively use business analytics to improve profitability and operational performance.

Read Part II of of Mike's Article – Beyond Data: From Analytics to Action