In today's ever-changing business environment, financial executives are exploring ways in which the financial function can bring greater value to their organizations. To this end, they are transforming their organizations from focusing primarily on regulatory reporting to most effectively providing the information that internal management needs to more effectively "run" the business.
Financial executives must now think beyond the traditional financial information contained in general ledger systems and consider how best to provide for the comprehensive measures and analytical methods needed to drive decisions throughout complex, dynamic companies.
To achieve these objectives, accounting, finance, tax and other financial areas are developing data warehouses combined with advanced analytics to serve the needs of the entire enterprise. We refer to this advanced decision support capability for finance as financial analytics. This article examines the evolution of financial analytics and its effect on the state of data warehousing.
Today's Business Environment
The evolution of financial analytics has been driven by the emergence of new business models, the changing role of the traditional finance department, modifications to business processes and advances in technology. This dynamic environment presents the finance function with tremendous opportunities and challenges.
New Business Models
With the introduction of the Internet, three new e-business models emerged: business-to-business (B2B), business-to-consumer (B2C) and business-to-employee (B2E). These new models are shaping the future of financial analytics.
These new business models, which I discussed in the August 2000 DM Review column entitled, "E-Analytics The Next Generation of Data Warehousing," require a translucent connection and fluidity of information between departments and partner organizations. Underlying these new business models is a fundamental shift in values, from physical assets to intangible assets such as patents, trademarks, franchises, computer programs, research and development, business intelligence and relationships. Consequently, the value of information is soaring (see Figure 1).
Figure 1: From Bricks-and-Mortar to Clicks-and-Mortar E-Business Changes the Focus of Financial Capital Analysis (Source: PricewaterhouseCoopers, LLP)
For instance, let's focus on the B2C model. Many "pure" B2C organizations do not develop the products or services they sell. Instead, these companies outsource their manufacturing and other non-core operations. They focus their resources on developing a brand, managing a network of customers and other differentiated aspects of running the business. That said, these objectives can only be achieved through the more effective use of information.
Financial analytics has traditionally focused on how a company utilizes tangible assets such as cash, real estate, machinery, etc. However, many companies competing in the new electronic economy are valued based on their intangible assets. These increasingly important assets are often difficult to measure and manage. As a result, dot-coms are relying on financial analytics to help them:
- Understand the overall performance of the organization,
- Identify ways to measure and maximize the value of intangible assets,
- Reduce operating costs and effectively manage enterprise-wide investments,
- Anticipate variations in the marketplace,
- Optimize the capabilities of information systems, and
- Improve business processes.
At the same time, the Internet companies that are not leveraging their information assets are struggling for survival.
Changing Role of the Finance Department
As the economy continues to evolve, so does the role of the finance function within an organization. Driven by investments in enterprise resource planning (ERP), shared services and changes in its reporting role, most finance functions are becoming more efficient requiring fewer resources to manage them and closely aligning with the company's business structure. This is especially true in the area of transaction processing where improved automation of financial transactions has enabled finance staff to expand their role and spend more time supporting decision-making processes, rather than just processing and reconciling transactions.
More and more global organizations are integrating and standardizing their business processes and systems, allowing end users with both finance and non-finance functions to update and obtain financial information from any geographic location. This has significantly improved decision support within the organization.
Consequently, the role of the finance professional will evolve into a "coaching" role responsible for transferring the appropriate analytical tools and methods to decision-makers (see Figure 2). Some CFOs have gone so far as to predict that, with time, major parts of the finance function will merge into the business as the role of finance employees continues to extend throughout the enterprise.
Figure 2: Reshaping the Finance Function (Source: PricewaterhouseCoopers, LLP)
Over time, we anticipate a convergence of the information that is communicated to the financial markets (Wall Street), the information that is used to manage the organization and the information that is reported formally in fiscal-year reports. This type of reporting will require the full integration of financial, strategic and operational analytics.
As business processes evolve and business questions become more complex, the analytics necessary to answer and act on these questions require a higher level of data integration and organizational collaboration. For in-stance, historically, finance departments were oftentimes the only departments with access to accurate information about a company's financial results. However, this information was usually at an aggregated level and wasn't available until several days, sometimes weeks, after the end of the month.
During the past decade, however, companies have been successfully integrating back-office processes and information flows across the enterprise by replacing function-based legacy systems with a single ERP system, reengineering business processes and streamlining business transactions. This has enabled executives and managers to access more accurate and consistent detailed financial, as well as non-financial, information about the organization throughout the month.
In the mid-nineties, new software products capable of maximizing the value of the Internet were introduced in the marketplace. Companies began implementing supply chain management (SCM), customer relationship management (CRM) and other sophisticated system solutions to optimize their end-to-end operations. At the same time, organizations each with its own legacy systems began strengthening their relationships with customers and suppliers. All of this contributed to the new challenge organizations are facing today: a complex information environment that forces organizations to adopt a new level of integration across the entire value chain.
Additionally, organizations realized there is an overlap in the analytical processes of the organization (see Figure 3).
Figure 3: Analytical Processes Can Overlap (Source: PricewaterhouseCoopers, LLP)
Recent developments in financial analytics have been made in these areas of "overlap." For example, by combining traditional financial measures (revenue and cost) with CRM information (customer history) and applying predictive modeling tools and techniques, companies can now project the future profitability associated with an individual customer or household. We refer to this as customer value management (CVM). CVM enables organizations to continuously monitor each customer's value to the business and act accordingly. "Value" may be measured using a weighted customer value index, which combines financial and non-financial measures and considers how many resources are used to maintain a certain type of customer. Managers need to know what value may be lost or gained before making decisions about nurturing specific customers relationships.
During the nineties, there were major advances in technology including ERP, data warehousing, portals and, of course, the Internet.
ERP systems have become more common and the Internet has expanded the sources of financial data to include up-to-date information on numerous subjects from market trends to currency fluctuations.
ERP vendors are aggressively developing financial analytic extensions to their core applications, each introducing its own version of an integrated financial architecture that covers performance measurement, planning and forecasting, management and statutory reporting, and financial consolidation. The sharing and integration of data is crucial for these ERP systems.
With portals, it is envisioned that people with finance roles will have access to critical performance information refreshed on a continuous basis and combined with relevant external sources of information such as competitor comparisons, media comments, economic indicators and benchmarks. Portals will allow the finance professional to receive personalized data through a common user interface and benefit from enhanced communication, search and team-building activities in increasingly fragmented environments.
Explosive growth in portal technology is likely to continue, fueled in part by the adoption of the extensible markup language (XML) standard to facilitate more open information sharing within and between enterprises.
The Role of the Data Warehouse
Until recently, data warehousing solutions have been primarily focused on building key analytical infrastructure components such as data stores, data marts and reporting applications. The next generation of data warehousing will leverage these data stores by incorporating rich analytical capabilities.
In early initiatives, the business needs driving data warehousing investments were often not clearly defined. It was also difficult for many financial analysts to think beyond traditional financial data. Consequently, it was frustrating for all concerned to define questions to be asked against the data or even define the analytical requirements to be supported.
The requirements driving the data warehousing implementation mainly focused on the need for specific data elements and/or necessary predefined reports. Data warehouses and online analytical processing (OLAP) tools were designed to support specific groups within the organization. Each group, including finance, used these incongruent systems to perform their business functions and store and access their own information. This resulted in redundancies and inconsistencies in data as well as a proliferation of data marts.
Decision support is most effective when the data and business processes of an organization are integrated across all business functions. Today, the benefits of this approach are easy to appreciate. And as companies come to grips with this need for consistent, integrated information, the finance function is most often at the center of this convergence. This recognizes the fact that financial information is important to help measure and manage every segment of the business and also recognizes finance's role as being the primary steward of a company's information assets. As such, finance executives can clearly see the benefits of fully integrating financial analytics with the rest of the organization's technology and processes. Data warehousing practitioners will be tasked with the challenge of developing an information architecture that delivers this new level of integration.
With integrated financial analytics, organizations will obtain the most value possible from their ERP, data warehousing and CRM investments.
Today's complex information environment is forcing organizations to reach for a new level of integrated financial analytics to stay competitive in the marketplace.
With integrated financial analytics, organizations are able to aggregate, analyze and share information from and with sources inside and outside the organization. As the role of the finance function continues to evolve, financial analytics will be actively used throughout the organization. We will see organizations strive for an environment that integrates all analytics, not just financial analytics, in order to thrive in the new economy. A data warehouse is crucial for realizing this powerful new environment.
Author's note: Valerie Brown, principal consultant, and Margaret Pommert, principal consultant, were major contributors to this article.
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