Trends in the market for analytic applications

By Dan Vesset

Analytic applications play a critical role in the broader knowledge management strategy as applications supporting management through quantitative data analysis. Concerned with the analysis of structured data, these applications are applied to all functional areas of the enterprise from customer behavior analysis and budgeting and planning to inventory and supplier relationship management. From the software perspective, analytic applications provide knowledge workers with structured access to relevant information, enabling more accurate and timely decision-making.

IDC, which coined the term "analytic application" in 1997, defines them as applications that must meet each of the following three conditions:

• process support—This condition relates to packaged applications software that structures and automates a group of tasks pertaining to the review and optimization of business operations (i.e. control) or the discovery and development of new business (i.e. opportunity). ;

• separation of function —This condition means the application can function independently of an organization's core transactional applications, yet it can be dependent on such applications for data and might send results back to these applications. ;

• time-oriented, integrated data from multiple sources —The application extracts, transforms and integrates data from multiple sources (internal or external to the business), supporting a time-based dimension for the analysis of past and future trends, or it accesses such a database. ;

These applications differ from generic business intelligence (BI) tools such as query and reporting, multidimensional analysis or data mining, which are used by IT departments to build analytic applications and lack the component of process support. (For more information on BI see IDC's report titled "Information Access Tools Market Forecast and Analysis.")

Analytic applications taxonomy

The definition of the term analytic applications includes business applications for planning, forecasting and modeling that relate to specific business subjects that span industries or that are specific to industries, as follows:

Financial and business performance management (BPM) analytic applications These analytic applications are designed to measure and optimize financial performance and/or establish and evaluate an enterprise business strategy. They are cross-industry applications rather than vertical-specific applications, and the major categories are as follows:

• financial-related—includes applications for financial consolidation, budgeting and planning, activity-based costing and other financial analysis, and;

• BPM—includes applications that evaluate and measure the success of an enterprise business strategy. Examples include balanced scorecard applications and BPM that spans multiple functions.;

Customer relationship management (CRM) analytic applications

These are designed to measure and optimize customer relationships. The major categories are:

• cross-industry applications for marketing analysis, Web site analysis, and multichannel CRM analysis, and;

• vertical-specific CRM analysis for verticals such as financial services, telecommunications, and retail.;

Operations and production analytic applications

They are designed to measure and optimize the production and delivery of a business' products and services. The major categories are:

• financial services, which includes operations and production improvement applications aimed at banking, insurance, and other financial services such as risk analysis, portfolio analysis and fraud detection;;

• healthcare, which includes operations and production optimization applications aimed at healthcare providers, such as outcomes analysis;;

• human resource management and payroll, which includes applications such as work force planning and optimization;;

• materials management/logistics, which includes applications such as demand planning and procurement optimization;;

• manufacturing, which includes applications aimed at manufacturers such as defect and quality analysis and supply chain trend analysis;;

• retail, which includes operations and production optimization applications aimed at retailers, such as merchandising planning and analysis and store location analysis; and;

• other vertical applications, which include operations and production improvement applications aimed at other vertical industries (e.g., telecommunications and utilities), such as network problem analysis.;

Market performance

In 2000, the market for analytic applications based on software license and maintenance revenue stood at $2.5 billion. The largest segment of the market is the operations/production analytic applications one, with approximately 42% share of the overall market.

The second larger segment is financial/BPM and the third, CRM. However, given the recent focus on CRM, that segment of the overall market is expected to experience the fastest growth.

As software users have moved to unlock their data assets from ERP, CRM, SCM and legacy systems, the demand for analytic applications has increased. Such demand is expected to continue as organizations will move increasingly from relying on software to process transactions to using it to understand their enterprise data and thus make better and faster decisions.

The increased demand for analytic applications also has the effect of producing demand for underlying BI, collaboration and workflow tools, which are often embedded in these applications.

Trends

Closed-loop application

The closed-loop applications model call for the linkage between transactional applications, such as ERP, CRM, SCM, e-commerce and analytic applications. As data is generated by transactional applications there is the opportunity to capture and store it. Once stored the data can by analyzed, modeled and then used to modify or adjust actions taken through transactional applications. Thus, a closed loop is created of constant data capture, analysis and decision refinement.

Today two major segments characterize the market for analytic applications. First are the applications for pure-play analytic applications vendors, that don't supply their own transactional applications. The second segment is occupied by ERP, CRM and SCM vendors, which supply their own transactional and analytic applications. There are benefits and drawbacks to each of these segments, and while the applications evaluation strategy is outside the scope of this article, users should as always review each option before committing to a software solution.

Verticalization

Another trend in analytic applications is the verticalization of such applications. This is most evident in the production/operation segment of the market where the needs of each industry can differ substantially. For example, the analytic needs of pharmaceutical companies in their R&D processes are different from those of a manufacturing plant or a services-oriented hotel chain or airline. However, there is verticalization also in the other two market segments. Certainly, CRM functionality is specific to industries as companies analyze customer behavior and perform segmentation, marketing analysis and predictive modeling in an effort to better target their customers. Some may be more concerned with customer service while other will look to optimize cross- and up-selling opportunities.

Functionality

In the last several year many analytic applications have become Web-enabled, thus allowing broader enterprisewide deployments and arguably easier maintenance of the software.

Besides the traditional query and reporting functionality, many analytic applications have incorporated sophisticated workflow support, which guides users through decision-making processes, while at the same time providing the opportunity to capture best practices in decision making.

Many of the CRM analytic applications have or are beginning to incorporate data mining algorithms for more in-depth customer analysis. Data visualization is another feature gaining momentum, providing users with more intuitive and interactive means of working with data.

In addition to the above mentioned exploratory data analysis functionality, analytic applications are also beginning to provide monitoring and alerting features, which push relevant information to users through various desktop and mobile devices.

Link to portals

Analytic applications are and will continue to be incorporated in broader enterprise information portals (EIP). As enablers of actionable structured data analysis to EIPs, the applications can be complemented with unstructured data management features and collaborative functionality, thus creating comprehensive portals that take advantage of the all the data assets of an organization.

The current trends point to a continued adoption of analytic applications across all three segments of this market. Already there are signs that analytic applications are taking on an increasingly strategic role as organizations continue to be inundated with larger data volumes. Operating on "gut-feel" will become unacceptable, as organizations will look to their software investments to move beyond transactions processing into business analytics.

Dan Vesset is research manager of Business Intelligence and Data Warehousing with IDC (idc.com), e-mail dvesset@idc.com.