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Article
beyond data: getting the most from business analytics (part I)
Read Part II of of Mike's Article
– Beyond Data: From Analytics to Action
By
Mike Meyer
Senior Consultant
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:
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:
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:
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 |
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