COVER story

In today’s increasingly fast-paced business environment, companies no longer can afford a static planning process. The word that defines business today is “agile:” the ability to move or change quickly, and often quietly. This process

should not be treated as a one-time, annual event that documents the organization’s priorities and objectives; rather, it must be an evolving record of new realities.

The budgeting, planning and forecasting process provides companies with an active framework for allocating resources to achieve corporate objectives within a defined time frame. The most significant output of this process, the annual plan, sets the detailed revenue and cost benchmarks against which performance is measured during four quarters of the coming fiscal year.

The annual plan puts the corporation at the starting line with targets aligned to senior management’s objectives. By the time the annual plan is approved, however, it may no longer reflect realities at lower levels such as the plant, sales office or CPA firm. In response, management needs monthly or even weekly outlook updates that can identify operational tactics needed to capture new revenue opportunities or dampen cost overruns.

Building Your Best Performance Management Systems

Spurred in part by the unpredictability of economic turbulence,

management expects that departments will dynamically incorporate

operational and macro-economic indicators into their budgeting,

planning and forecasting processes. Strategic objectives must be

managed in a way that enables frequently updated, transparent

views of performance projections.

Company management should work to develop objectives and

detailed forecasts that support top-level strategies. Everyone

needs to be “singing from the same hymnal.” This drives the call

for a unified data platform that enables driver-based performance

management and improves decision making throughout the

enterprise.

Too often, companies’ complex financial systems scatter information

needed for effective dynamic planning across disparate silos – e.g.

multiple spreadsheets, databases, and scattered legacy mainframe

source systems. This makes the information inconsistent,

incomplete or difficult to access. Short-range forecasts, as well as

longer-term strategic plans, can be impeded when there are

22 NOVEMBER/DECEMBER 2012

By Kim E. Autrey, Tim Duning, and Chet K. Robinson

poor data links between professionals in departments such as

procurement, revenue reporting, cash management and sales

support.

Today’s CFOs are the owners of the financial budget and forecast,

and (often) the stewards of the strategic plan. They must take

a leadership role to help their companies build performance

management systems capable of dynamically driving strategic

and tactical decisions. Many financial-information technology (IT)

professionals find that the most effective response uses a financial-

data repository where data definitions and rules consistently can be

applied, and the entire enterprise can be viewed from an analytical

perspective.

Because the finance department is responsible for numerous

functional areas, financial-system complexity is inevitable. This

complexity, combined with the accelerated information flow now

required to respond nimbly to competitor actions and environmental

threats, has significantly increased the CFO’s interest in working

with IT to streamline and simplify their financial systems.

Simplification, Standardization, Consolidation1

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1 Terdata, 2012.

COVER story

To keep pace with change, companies must adjust their financial-planning processes and underlying infrastructures. A holistic approach – one that enhances the CFO’s ability to get a dynamic, integrated view of performance – is needed. It begins with a financial reference architecture that seamlessly integrates eight key components founded on a centralized financial-data repository.

1) Data Warehouse Foundation: A finance data warehouse (FDW) con-sists of the finance-specific elements of an enterprise-data environment. It is uniquely capable of serving as a systems-integration platform that links financial details to the operational data and simplifies provision of consistent data to countless applications and users.

2) Data Sourcing: Moving data from source systems into the FDW where it is transformed ensures user con-fidence. This provides a transparent audit trail needed to tie exact copies of source transactions to the transformed data in the FDW.

3) Hierarchy Management: Increas-ingly, firms need to view and manage the business at varying levels of detail, aggregated across multiple dimensions or classifications, while ensuring these different “views” reconcile and are driven from a common core data set. The ability of business users to flexibly view and manage these dimensions and hierarchies, and change the underly-ing data structures that drive reporting across the broader architecture with-out IT involvement, is an increasingly critical financial-reporting requirement.

4) Accounting Hub: To ensure FDW integrity, it must reconcile reliably to the General Ledger (GL). An accounting hub enables a layer of transparency over complex accounting rules, mappings and aggregations that turn operational system transactional data into summary automated postings in the GL. This facilitates three-way reconciliations among the FDW, GL and operational systems.

5) Financial and Human Capital Management Analytics and Data Integration: General ledger, human resource and other key enterprise resource planning (ERP) data are critical elements of financial analysis. Data integration and analytics capabilities source and organize this data in the FDW into a business context for different finance functions (e.g. GL, procurement, or payroll) to speed analysis and report generation.

6) Calculation Engines: A complete infrastructure must integrate pre-packaged software applications and calculation engines with standard business rules that deliver enterprise-wide profitability, risk, planning, forecasting and allocation capabilities.

7) Business Intelligence (BI) and Reporting Tools: To field ever-evolving information requests, analysts need an ad hoc environment that provides access to data from multiple sources. If there are several BI tools within an enterprise environment, a common data warehouse foundation

where metrics and calculations are managed helps drive consistent results across tools.

8) Data Management: To ensure that analysis recommendations are sound, transparency, data quality and applying common rules throughout the data lifecycle are critical. A well-executed data management strategy secures an auditable trail from source to final report.

By supporting data integration and data management across applications and business processes, a rational finance architecture sets the stage for executing best practices. The Hackett Group, a leader in benchmarking, has observed financial data management best practices common to world-class companies. Typically, these companies have a finance cost-to-revenue ratio that is almost half that of their peers (0.600% vs. 1.13%).2 They also produce a return on equity that is 2.4 times that of their peers.3

Hackett captured the best practices that distinguish these companies.

1. Central repositories enable world-class finance staffs fo-cused on planning and analy-sis. For improved speed, companies need to have their financial and opera-tional data in one central repository. A central repository provides a unify-ing environment where common data definitions and hierarchies are linked throughout the enterprise. Conse-quently, the procurement division sees

The word that defines business today is “agile.”

2 The Hackett Group, 2010 Finance Book of Numbers, 20103 Ibid.

24 NOVEMBER/DECEMBER 2012

the revenue impact of a sales depart-ment’s order forecast to ensure there is no lag in product availability.

2. Simplification is the name of the game. World-class companies have fewer budget line items than their peers. They free their forecasts and plans from the limits of historical financial-data results and understand the big-picture events that drive revenues and costs through the business, rather than trying to forecast each P&L line. For example, one transportation company decided that using historical trends to forecast P&L lines such as salaries, overtime, T&E and fixed-asset utilization missed the point entirely. Instead, they began asking, “Which business processes drive these costs?” The answer was “train starts.” Analysis revealed that each time a freight train was scheduled to make a run from point A to point B, a predictable set of costs were generated for fuel, salaries, T&E, overtime, etc. This discovery meant planners could base most cost forecasts on the number of expected train starts for a given period. Projecting results based on operational events vastly speeds and simplifies the forecasting process.

3. Secure business alignment and accountability by linking finan-cial results to the operational drivers that cause them. Own-ership of the inputs into the planning and re-forecasting processes belongs in the individual business units. The ability to incorporate financial data and operational drivers in a single, in-tegrated and reconciled data repository Reprinted with permission of the Florida Institute of CPAs from the November/December 2012 issue of Florida CPA Today.

is critical. Finance departments must focus on critical operational drivers, such as “projects completed/billed” in construction or “new loan accounts established” in banking. By doing this, they can escape the dangers associ-ated with “top-down” budgeting tied to targets lacking a basis in reality. By using a central-data repository, best-practice companies enable financial analysts and operations management to determine which operational levers can be pulled to move financial results in the desired direction.

The Hackett Group’s findings make clear that today’s performance-management processes cannot exist in a vacuum. CFOs and their departments must eliminate the barriers posed by complex finance-infrastructure environments where information is dispersed across disconnected systems. To do this, they need a holistic approach with unfettered and enhanced access to centralized financial-data repositories. A “next-generation” finance architecture can accomplish this by delivering a more complete, multi-dimensional view of all finance functions. The payoff: timely, live and consistent access to reliable, relevant and actionable information that enables renewable process-cost reductions and performance-enhancing business insights. FCT

Kim E. Autrey, CPA, CITP, CGMA is a senior consultant – financial transfor-mation at Teradata Corporation. Tim Duning, MBA, CMA, is a solutions de-velopment director with the Teradata Finance and Performance Manage-ment team. Chet Robinson, MBA, is a communications and deployment manager with the same team.

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