During the past decade, global companies in every industry have made significant investments to upgrade their transaction systems and processes via enterprise resource planning (ERP) software. At the same time, many of these same firms have also invested in developing data warehouses and/or data marts to provide enhanced data aggregation and delivery as well as decision support capabilities. In many cases, these projects were conducted in parallel; however, the design of the ERP solution did not consider or take advantage of the capabilities of the data warehouse.

Consequently, there are numerous companies today that have invested millions of dollars in ERP solutions, yet are frustrated by their inability to obtain aggregated, timely information from these and other transaction systems. The next generation of ERP-related initiatives must address this issue.

In this article, we will describe: the evolution of ERP investments; the role of the data warehouse within the overall ERP information architecture; and the next generation of integrated ERP/data warehouse environments, which will be focused on integrated analytics. We will also look at the advancements being made by the three largest ERP software companies (SAP, PeopleSoft and Oracle) in the areas of data warehousing and analytic applications.

The Evolving Business Environment

The 1990s was clearly the decade of ERP, a phenomenon driven by a combination of three significant market trends:

  • The importance of being Y2K compliant.
  • The adoption of business process reengineering as a strategic imperative.
  • The functional and technical advancements made by the major ERP software providers.

Prior to the 1990s, organizations purchased specialized, standalone application software to manage everything from facilities to sales and finance. Frequently, these applications (either from different vendors or the same vendor) were not well integrated. At the same time, most packaged software was designed for the mainframe and, thus, did not take advantage of distributed processing advancements offered by the maturing client/server-distributed architecture. Some companies continued to custom-develop applications that could not be integrated into their new, more complex systems environment.
With the introduction of integrated client/server-based ERP systems, many organizations began to realize greater efficiencies from their application investments. Specifically, they noticed that the cost of processing transactions began to decrease and that their ERP system was a major contributor to those efficiencies. However, the need for better information to make business decisions was not a focus of these ERP implementations. Thus, a high degree of management frustration remained, as these systems did not provide strong analysis and reporting capabilities. The term "data jails" was coined to illustrate the severe limitations of some ERP systems.

To fill this void, certain ERP vendors created alliances with established data warehouse vendors and offered their customers accelerators to develop custom data marts. Others began providing silo-reporting solutions as extensions to their core applications. The silo approach was usually based on individual ERP functional areas such as logistics, sales or management reporting. The major issue with this approach was that while the organizations had an integrated transactional environment, the reporting environment was now single-process oriented and not well suited to manage the overall enterprise.

By the late 1990s, some organizations began upgrading their ERP systems and integrating them with their existing, customized data warehouses only to discover that they required substantial modifications to maintain the data now available through the underlying ERP system. At the same time, the cost of owning multiple reporting solutions was increasing and data consistency and accuracy was becoming an issue. The performance of these ERP solutions suffered as a result of companies trying to use these systems to provide capabilities they were not optimized to perform, such as online reporting and queries.

The convergence of these market forces, along with advances in technology, created a strong demand for a more integrated approach to management reporting and analysis that involved information from across a company's complete value chain. The value of this information is then further enhanced with advanced analytics. At PwC Consulting, we call this iAnalytics (integrated analytics).

The Need for Integrated Analytics

Integrated analytics brings together information from a company's ERP, customer relationship management (CRM), human resources, financial management, supply chain and e-business systems, and enhances it with advanced analytics, empowering the company to react more quickly to a rapidly changing business environment. Integrated analytics:

  • Better integrates a company's information assets across the value chain.
  • Delivers role-based business intelligence to the information consumer in a personalized manner.
  • Includes advanced analytical models focused on decision making.

Integrated analytics allows organizations with an ERP infrastructure to provide the type of reporting and tools required by decision-makers in a way that is not limited by their ERP system. For instance, many ERP systems represent financial information in transactional form; users need the ability to easily and quickly access and analyze that data at various levels of detail. Additionally, traditional ERP systems maintain data in relational databases that are structured for efficient input processing and single-dimension access. Multidimensional access is attainable in an ERP environment, but it generally involves more technical expertise and frequently results in poor online performance.
Analytic applications allow end users to readily access that same data in multiple dimensions with relatively good response time, as these tools and applications are tuned for multidimensional reporting. Data warehousing serves this need through tools and vendor offerings separate and distinct from ERP solutions. These solutions generally have three components:

  • An extract, transform and load (ETL) layer to bring source data into the analytic data stores in the appropriate format.
  • A repository for the data to be maintained, which could include an operational data store, a data warehouse and/or data marts.
  • A reporting/analytics layer, in which end users identify the type of data needed from the repository, along with the tools to improve the analysis (sometimes referred to as analytic applications).

Until recently, it was common for companies to interface their ERP systems to standalone analytic applications. ERP vendors recognized this business need and began to provide more integration capabilities. Now, each of the major ERP vendors has incorporated analytic capabilities into its core architecture.

The Role of the Data Warehouse

If we have an ERP system, do we still need a data warehouse? The answer to this question is yes. The role of the data warehouse has become central to the overall ERP information architecture. The data warehouse is the heart of the architecture because it drives the extraction of information from source systems (what data is available) as well as user access (how one accesses that information).

Integrating financial, employee, customer and supplier data into a single data representation is a major challenge, usually involving numerous source systems. For instance, a CRM system may represent a customer service employee and the relationship to individual customers/customer groups in one way (e.g., by product line). That same information may be represented differently in the human resources (e.g., by geography) and the financial (e.g., by legal entity) systems. These types of conflicts are resolved within the data warehouse.

Once the information is stored in the data warehouse, you can experience the additional benefits of integrated analytics within an ERP environment. Some of these benefits include:

  • Integrated and consistent financial, customer, employee and supplier information.
  • The ability to establish performance measures and link actual and planned performance to those measures.
  • A common toolset and infrastructure across what were previously disparate tools.
  • Improved efficiencies through fewer systems, less reconciliation points and integrated tools.

Emerging ERP Solutions

Each ERP vendor approaches the concept of integrated analytics in a fairly different manner. Some provide toolkits and accelerators to build customized analytics for their ERP offerings. Others offer pre-packaged applications for certain core functional areas. Some embrace the concept of integrated analytics and provide content and applications for offerings beyond ERP-CRM, balanced scorecards, data visualization, planning, budgeting and scenario management. Figure 1 illustrates these different approaches.


Figure 1: Level of Predelivered Content

At the same time, many of the traditional data warehouse and business intelligence vendors have successfully created analytical offerings that are integrated with ERP solutions. Some of these vendors will be forced to change their products whenever there's a new ERP version or release; therefore, the cost of maintaining complex analytics for industry-specific processes may be prohibitive for them.

As a result, some vendor solutions, while substantially better than traditional data warehouses, tend to be considered part of the first or second generation of ERP analytics, or positioned as complementary tools for ERP offerings such as portals, ETL and presentation tools, as they strive to achieve integrated analytics status.

From an ERP vendor perspective, the products of large companies such as SAP, PeopleSoft and Oracle have greatly improved. Their offerings are mostly considered second-generation solutions and, in some specialized areas, are approaching third-generation status with predelivered, specialized analytics for specific industries or processes. In the following sections, we discuss how these ERP vendors are addressing the market demand for integrated analytics and offer a brief summary of their related offerings.

SAP

SAP entered the data warehousing marketplace when it rolled out SAP Business Information Warehouse (BW). With this product, SAP offers hundreds of predefined database schemas (InfoCubes), data extraction programs, predelivered business content in the form of interactive reports, and embedded key performance indicators (KPIs). With BW, SAP assumes responsibility for maintaining extraction codes, databases and the presentation layer for the data warehouse as well as for the analytic applications hosted on BW. Their value proposition is the reduction in the cost of ownership associated with an integrated and single-vendor-suggested solution.

Customer feedback on the initial versions of BW led SAP to increase its focus on developing business content for the product as the company realized that content is the most important part of an integrated analytics solution. We believe that the evolution of predelivered content is paramount when evaluating products in the analytic applications area.

In 1999, with its updated BW release, Version 1.2b, SAP had a basic data warehouse offering. The system did not have an operational data store (ODS) for long-term staging of detailed data, although it did have some business content and a basic presentation layer.

SAP addressed some of these architectural gaps in Version 2.0b, which offered industry-specific analytics and used its BW product to host analytics for CRM, advanced planning and optimization (APO), and strategic enterprise management (SEM). Additional content was added in the next release when the number of predelivered analytics (InfoCubes) grew to 260.

With SAP's latest release of BW in the fall of 2001, Version 3.0a, the content for analytics was increased to more than 1,400 predelivered OLAP reports covering 14 different industries. Presently, BW offers both data warehousing and analytical capabilities.

Key BW benefits are the acceleration of business content development and the proposed reduction of costs associated with the development and ownership connected with the prebuilt, complicated extraction routines that enable companies to source and maintain SAP data.

PeopleSoft

PeopleSoft began supporting the concept of integrated analytics more than four years ago when they introduced their Enterprise Performance Management (EPM) product line with Version 7.x of their PeopleSoft applications. From the outset, EPM has been integrated into PeopleSoft's application architecture, leveraging PeopleSoft's development tools and architecture standards.

PeopleSoft has steadily increased the capabilities of EPM while further developing the fundamental building blocks of their ERP architecture. Today, EPM is comprised of several key components:

  • An ETL layer.
  • An Enterprise Warehouse comprised of an ODS, data warehouse and data marts.
  • Analytic engines for data enrichment and analysis.
  • Analytic applications such as Budgeting, Planning and Balanced Scorecard.
  • Support for third-party ETL, analytic and reporting tools.

The first major components of EPM are ETL tools and an Enterprise Warehouse. PeopleSoft uses Informatica as the ETL tool that loads data from different source systems (PeopleSoft and others) and maps that information into EPM-specific tables. From the outset, PeopleSoft has provided data maps to its own applications to make integration with its own products simple and straightforward.
The Enterprise Warehouse supports financial, workforce, supply chain and customer data elements. By providing enterprise-wide support, PeopleSoft has made EPM an alternative for companies considering Enterprise Warehouse strategies in addition to providing integrated analytics. As such, it is designed to create and support analytics that span the functional boundaries of the ERP applications (e.g., a sales analysis by product, customer and geography with the underlying detail for each dimension). Such a breakdown of sales could show:

  • Sales at the product-line level by sales region and by individual salesperson.
  • Cost of goods sold by product line and salesperson.
  • Compensation costs by product line and salesperson.
  • Profitability by product line and salesperson.

By supporting a broad range of cross-functional data, PeopleSoft initially focused their analytic applications horizontally to support the broader needs of their clients across business process and industry. Two of the first such tools were Balanced Scorecard and Activity-Based Management (ABM).
PeopleSoft Balanced Scorecard allows customers to develop and manage enterprise-wide strategies and metrics such as sales, employee satisfaction, customer retention and supplier performance as well as to establish and measure employee or group performance against the Balanced Scorecard. ABM is PeopleSoft's activity-based costing engine, which is used for the sophisticated cost allocation necessary to measure profitability across various dimensions (corporate, product, customer, etc.).

Subsequently, PeopleSoft provided analytic applications in its Financials and Workforce modules. In the area of financial analytics, PeopleSoft supports Funds Transfer Pricing, Risk Weighted Capital, and Asset Liability Management. For workforce analytics, they provide Workforce Planning and Rewards. Customer and Supply Chain Analytics have recently supplemented these, rounding out PeopleSoft's integrated analytics offering.

From a reporting perspective, EPM provides capabilities through Hyperion Essbase, Cognos PowerPlay and Business Analysis Modeler (BAM), a multidimensional reporting and analytics engine.

With Version 8.3 of EPM, PeopleSoft has introduced a business planning, budgeting and forecasting application that is used for continuous short- and long-term business planning analysis. The application provides a driver-based model and generates projections of business conditions in the form of an integrated cash flow, income statement and balance sheet as well as other key financial and nonfinancial metrics. This includes an ODS to support operational reporting as well as integrating their new multi-dimensional tool (BAM).

PeopleSoft is further committing itself to its EPM capabilities; the company continues to integrate traditional ERP capabilities into EPM. For instance, like the PeopleSoft General Ledger (GL), PeopleSoft EPM now provides allocation capabilities to supplement GL; the new version of Budgeting is based on the updated EPM architecture. We expect to continue seeing more tightly integrated ERP/EPM functionality from PeopleSoft in future releases.

Oracle

In the mid-1990s, Oracle was the first ERP vendor to recognize the need for an enhanced reporting solution for their growing ERP business and started the development of Oracle Applications Data Warehouse (OADW). This solution was based on a data mapping application of the ERP system into a decision support system based on an Oracle database and the Express OLAP technology they acquired from IRI. The product offering from this initiative went to market as a bundled tool set that included Discoverer (for a managed query environment), Express (for OLAP), a database license and some predelivered reporting accelerators, namely Oracle Financial Analyzer (OFA) and Oracle Sales Analyzer (OSA).

With OFA and OSA, Oracle offered customers integrated analytic applications, based on Oracle Express technology, with their core applications. Later on, Oracle also added Performance Analyzer (for profitability and performance measurement) as part of the company's overall business intelligence tools.

Recently, Oracle created an initiative that brings these products together in a more integrated fashion. The result is the Oracle Business Intelligence System (BIS) offering. With its release of BIS version 11i, the company integrated its various offerings within its E-Business Suite and added a large number of analytics as well. Among these solutions are CRM, SEM, human resources, service, market interaction and sales intelligence applications.

A major feature of BIS 11i is the predelivery of about 650 predefined views of the ERP data through the company's managed query environment offering (Discoverer). These views are organized in 22 business areas and provide the users basic query capabilities on top of the ERP applications. Additional features include two natural language assistants that allow users to query reports for trends or keywords, or query against the views provided. Oracle has organized these business intelligence analytics in Web-enabled workbooks that are also supported by their e-business offerings (e.g., Web portals).

As part of the BIS 11i solution, Oracle has moved toward delivering integrated analytic applications that provide process-specific analytics and allow the developers to add more features based on user needs. Additionally, the company still provides tools and templates for those who prefer building their own systems rather than relying on increasingly popular predelivered applications.

Currently, Oracle is introducing their "Daily Close" strategy, which is designed to provide information consumers throughout the enterprise with the day-to-day information needed to make timely decisions without having to wait until the end of the month.

The Future of ERPs in the Analytic Applications Market

In order to survive and win in today's market, ERP vendors have recognized that they must have improved information delivery and analytics as core components of their products.

The rapid flow of information has increased the need for executives and managers to "keep their fingers on the pulse" of their companies and to be able to easily access timely, accurate information.

This will become an important competitive advantage, as ERP providers continue to struggle with differentiating products solely on the functionality associated with their transaction-processing capability. Additionally, the business case for ERP investments has shifted, from Y2K and process transformation requirements to the need for leveraging and extracting real value from the companies' information assets.

Lastly, new ERP modules such as CRM, supply chain management and interactive planning solutions have increased customer demand for accessing data in a timely and integrated fashion.

It's clear that the market is moving away from the realm of custom and nonintegrated applications and into predelivered products that are closely linked to ERP systems. Vendors in the ERP analytic applications marketplace have correctly identified the next critical path for the success of these solutions. However, any vendor who fails to provide integrated decision support systems at a reasonable cost will suffer as we move into integrated analytics, the next generation of decision support systems.

In a sense, the race is on between ERP vendors who have expanded into the analytics space and analytic applications vendors who are expanding into the ERP space. It is going to be a fun and interesting ride.

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