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Finance Business Intelligence – From Data to Information to Competetive Advantage

Published
  • December 01 2003, 1:00am EST

Today's competitive and challenging economic environment places further emphasis on real-time information for decision-making purposes. Without relevant, reliable information provided in a timely manner, decision-makers are forced into suboptimal decisions based on assumptions and gut instinct. This lack of fact-based decision making places the company at risk with one or more constituencies that interact with the company on a daily basis –­ the implications of which are, in aggregate, substantial and negative to the enterprise.

The time for business intelligence (BI) is now, as it can be leveraged as a competitive weapon to improve efficiencies and better manage position in the value chain. If implemented as a comprehensive solution, BI will reduce the time spent on low- to non-value-added activities across the enterprise, as well as enhance the organization's ability to make profit-enhancing decisions.

Benefit targets and categories include:

  • 20 to 30 percent reduction in period-end closing activities through application automation and process redesign. Reconciliation activities can be reduced by as much as 50 to 60 percent as well.
  • 30 to 40 percent reduction in report generation activities (which we have seen account for as much as 30 percent of the total finance organization). Report sets are rationalized and standardized, and the user communities are enabled to access and produce their analyses without ongoing finance/information technology (IT) support.
  • 50 to 60 percent reduction in budgeting, planning and forecasting activities across the enterprise. The multiple process streams involving manual spreadsheets, reconciliation, rekeying and e-mails can be substantially reduced and create the opportunity to collapse the entire planning cycle.
  • Revenue enhancement, including the information to improve gross-to-net management, tracking of sales float from sales programs, customer penetration and trending.
  • Cost management by delivering accuracy in reporting major areas of spend to support benchmarking and/or other cost reduction initiatives.
  • Profitability management by viewing contribution at the customer, channel and SKU (stock-keeping unit) levels, thereby supporting the creation of profit plans to influence margins.
  • Avoidance of misrepresentations in external reporting and related market cap impacts, as well as the ability to build investor confidence through more fact-based support of financial performance.

The Business Intelligence Pyramid

We view business intelligence through an informational/technical "pyramid" containing the following elements: legacy systems, enterprise resource planning (ERP) solutions, data warehouse/marts, analytic applications and enterprise information system (EIS)/key performance indicator (KPI) portal (see Figure 1).


Figure 1: Business Intelligence Pyramid

As you work your way up the pyramid, the level of information correspondingly becomes more summarized and the views of information become more strategic.

Legacy Systems

The underlying legacy systems are used to support core processes and information capture (e.g., work management, time capture, etc.). These systems may require replacement over time, but are primarily viewed as a constant in the framework.

ERP Solutions

ERP software packages drive transaction processing efficiency and consistency. A company may have multiple packages, instances and/or configurations depending upon its operating model. Organizations have begun the shift from "implement" to "optimize" in this area, increasing enterprise-wide consistency in process and data definition.

Data Warehouse/Data Marts

This layer provides for the efficient extraction of data from multiple sources, the translation of disparate data into a common, rational data model and the loading of data into the analytic applications. The data structures in this layer are optimal for extracting, transforming and loading large volumes of data values from the legacy and ERP systems. The resulting data is ready to be analyzed by power users within the organizations or further manipulated within the analytic application layer.

The "bypass" concept within the pyramid represents an important decision for any BI implementation effort. In the interest of quick solution development, the data warehousing/marts layer is often overlooked as an unnecessary step. Our experience has proven, however, that consideration must be given to this decision up front to avoid the creation of a suboptimal or even unusable BI application. Furthermore, there are significant cost and timing ramifications associated with inserting an ex post facto data warehouse layer within a BI framework.

Analytic Applications

Analytic applications are purpose-built solutions meant to satisfy a specific analytic/decision-making set of requirements. These applications could be viewed as a series of workbenches designed to provide a given group within the enterprise the tools necessary to do their jobs. Specifically within the finance function, these include financial reporting, financial planning and financial analysis (see Figure 2).


Figure 2: Analytic Applications within the Finance Function

Financial Reporting

This component could be considered the required blocking and tackling owned by the finance organization. It includes core period-end activities, legal entity/SEC (Securities and Exchange Commission), tax and other regulatory reporting requirements. The opportunities here are to aggressively automate the topside adjustments and related activities, as well as standardize/automate the data submission, reconciliation and core reporting processes. By so doing, period- end windows will collapse, lower value-added activities will be eliminated and finance will have more time to truly review the numbers as well as ensure information quality.

Financial Planning

Financial planning covers the entire planning process across the enterprise, which finance typically owns from a submission, preparation and reporting perspective. In many organizations, the planning cycle has become an exercise in futility. The budget window can span eight-plus months and is plagued by sandbagging and stretch target setting. Forecasts become a manual nightmare that may consume as much as 25 percent of the finance organization's capacity each month, yet don't provide valid predictability to future earnings per share (EPS) or other finance metrics.

Financial Analysis

This is the component that enables business partnering with the organization, supporting customer, product and channel profitability analysis, predictive EVA/SVA value reporting and process-based performance and benchmarking. These analytics provide finance with multiple views of the business and create the environment to convert operational performance to financial results.

This analytic capability, however, can only be attained if finance organizational capacity is created through efficiency gains and automation in the other two components.

EIS/KPI Portal

The EIS/KPI portal is the decision-maker's desktop view and window to the various information sets and underlying analytics. This provides the enterprise with a single means of access to the information and related reporting. This means that the user can navigate through various analytics, ERP solutions and even underlying legacy systems through the same portal, thereby eliminating the need to toggle and determine what data is where within the framework.

Historically, internal Web portal efforts have often been plagued by content focused on employee self-service regarding individual human resources benefit plans, as a vehicle for mass communications, or at best, an executive-level dashboard. Today, they have evolved into a far more effective enabler for a given user to navigate the internal technological/informational landscape and complete various types of analysis.

Factors to Ensure Success

Following are key steps that can mean the difference between the success and failure of the BI endeavor.

  1. Start with the end in mind. Lack of a clear, comprehensive BI strategy dramatically increases the implementation team's risk of failure. Dedicate anywhere from 6 to 12 weeks to complete the following strategic/vision-oriented components of a BI solution prior to detailed design and implementation.

    • Establish a clear set of conceptual requirements across multiple constituencies/functions within the organization.
    • Overtly apply the organization's strategic objectives to the business intelligence solution and communicate with key stakeholders.
    • Develop a detailed, resource-loaded and phased implementation plan.
    • Establish a solid business case and present same to executive management.
    • Assess the technical landscape, develop the technical road map, establish the short list of vendor products and develop the selection criteria process.
    • Identify the primary areas of incongruity that will require heavy analysis and decision making during the design phase (e.g., specific information standards).
    • Develop a strategy to manage the personal and organizational changes that will follow during implementation.

    Without these steps, any solution risks falling into the trap of being labeled either an accounting project or another system implementation.

  2. Prioritize and incrementalize. The implementation requirements surrounding BI solutions are inherently different from their ERP counterparts in that the implementations are far less time- and resource-consuming. This creates the ability for an organization to rapidly provide solutions for various organizational communities. However, this rapid deployment must be executed in a way that ties the core data elements of the organization together in an efficient manner.

    Once the overall BI vision for the company has been articulated, the plan of attack should be comprised of component implementations that are prioritized by the degree of information pain being experienced within different areas of the organization. Implementations are recommended to hold a 90-day benchmark and be limited in scope to a manageable array of information pain (the amount of pain addressed within each 90-day scope should increase as the team becomes more experienced with the tools and processes). The benefits of an incremental approach to BI include:

    • Focusing on specific component information pains allows the implementation team to adequately address the complex functional and technological pieces of each implementation. When the entire organization is approached at once, the complexity of the components becomes unmanageable and the work unproductive.
    • 90-day windows provide the team with a means to demonstrate the value being created to the various constituencies on an incremental basis.
    • Momentum is maintained for the enterprise-wide deployment through a series of successes.
  3. Monitor and publish success. Implementation teams can fall prey to viewing a phased solution as complete once the application set is live and the data is converted. The team must come back to the original business case, check performance to expectations and publish examples that have created value to the organization. These might include:

    • Making a profit-enhancing decision during a major customer negotiation based upon the improved information.
    • Supporting the analysis of a capital request.
    • What-if analysis decisions regarding where to make and what to make.
    • SKU rationalization/life-cycle profitability.
    • Predictive economic analysis using the improved tools and information.
    • Pure timeliness/capacity improvements in major areas such as financial closing, management reporting and budgeting.

    While many companies have implemented some form of a BI solution, few have established organization-wide awareness of these capabilities, benefits and/or potential for future value- creation that these applications possess. By first confirming and then communicating these wins to the organization on at least a quarterly basis, the BI solution will become further indoctrinated into the organization and convert stakeholders from dreading to demanding additional BI applications for their respective areas.

Maximize the Return

In summary, remember the following:

  • Track your progress. Start with the end in mind. Don't let your organization fall prey to viewing BI as a software installation.
  • Begin smart by leveraging existing research, best practices, industry trends and diagnostics. Recognize and leverage the fact that you are not the first to travel the BI path.
  • Focus on a complete solution, but in a way that continually drives 90-day results. Assemble a strong cross-functional team that will produce a solid business case and build the trust and commitment from the organization overall.

Today, the technology has caught up. It won't be the software that prevents a company from maximizing the return on a BI solution, but rather the content, processes and people necessary to make the solution work.
All information provided is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act upon such information without appropriate professional advice after a thorough examination of the particular situation. The views and opinions are those of the author and do not necessarily represent the views and opinions of BearingPoint, Inc.

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