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BAM, Real-Time and Event-Based BI: An Application Perspective

  • Henry Morris, Dan Vesset, Robert Blumstein, Kathleen Wilhide
  • September 01 2004, 1:00am EDT

BAM (business activity monitoring) is an extension of traditional business intelligence, adding event monitoring to scheduled, batch-based reporting. Early accounts suggesting "zero latency" were exaggerated, since the discrete steps in the decision cycle do not happen all at once. These steps are:

  • Track/monitor
  • Analyze
  • Hypothesize/model
  • Decide
  • Adjust/act

Businesses must accelerate the flow of information, analysis and decision making in order to be more responsive to fast-moving events. This business requirement will drive the augmentation of schedule-based technologies with event-based technologies - i.e., event-based business intelligence (BI).

Hype or Reality?

Given all the attention to "real-time" BI, one would think that this shift to event monitoring is pervasive. However, surveys of IT buyers tell a different story. Recent survey data suggests that BAM initiatives still have low priority within most organizations, with adoption currently at less than 10 percent (see Figure 1).

Figure 1: Adoption Stage for BAM Technology

It is evident that there is a healthy degree of skepticism in the marketplace on whether event-based technology is required. The reality is that most operational business processes don't require anything approaching real-time monitoring and analysis. In addition, most existing systems are not equipped to handle real-time data feeds.

The level of adoption demonstrated by the survey suggests that we are still in an early stage for event-based BI. The priority to monitor and respond to events will not affect all organizations or all business functions equally.

Benefits by Business Process

A fruitful way to look at the issue is to consider the differing requirements of applying BI (i.e., analytic applications) by business process or application. IDC segments analytic applications (that incorporate BI technologies) into three categories, by groups of business processes:

  • Operations/production analytic applications measure and optimize the production and delivery of a business' products and/or services. Examples are demand planning, manufacturing quality analysis and fraud detection.
  • Customer-related analytic applications measure and optimize customer relationships. Examples are marketing analysis, Web clickstream analysis and customer profitability analysis.
  • Business performance management/financial analytic applications measure and optimize financial performance and/or establish and evaluate an enterprise business strategy. Examples are scorecarding, budgeting/planning and financial consolidation.

Comparing the three segments, operations/ production processes are areas where managers must be able to monitor and respond to events. This drives new investments in event-based BI in support of these processes. However, there are aspects of the other two areas that are also being impacted by this shift as well. Real-time call center interaction is one target. Another example is current Sarbanes-Oxley legislation requiring C-level executives to certify financial results and day-to-day controls, driving the demand for increased visibility of events and information.

Operations/Production Analytic Applications

The primary technical challenge in executing operational analytic applications that support event-based monitoring is the task of data capture and integration. Some of the examples of current products that perform this task include Informatica's PowerCenter RT, Information Builder's iWay and Ascential's DataStage RTI. These and other similar tools enable real-time access to transactions as they are committed within the core transactional systems. In turn, such tools are often used as the data integration components in operations analytic applications.

Other prepackaged operations/production analytic applications include those for quality control, fraud detection, trading monitoring, environmental surveillance and other processes that require true real-time activity monitoring. Application examples include Fair Isaac's Falcon credit card fraud detection, OSI Soft's power plant monitoring, Mantas' trading compliance, Celequest's Activity Suite for quality control, inventory monitoring and other similar applications.

Monitoring detects exceptions or deviations from norms, alerting responsible individuals on the need to take action. Operations/production is the largest analytic applications market segment (representing $1.4 billion in total software license and maintenance revenue in 2003) and the one where real-time, event-based requirements are most evident.

Customer-Related Analytic Applications

Event-based support for customer-related analytics enables companies to optimize live interactions with their customers and prospects. In many cases, the support consists of on-the-fly scoring and decision making that leverages the results of off-line analytics, although it is also possible to use analytics to constantly evolve the constraints that are used to trigger actions on an individual basis. As an example, a retail banking customer who suddenly makes an unusually large deposit may be a prospect for another financial instrument, but the definitions of "suddenly" (the timing) as well as "unusually large" (the amount) can change over time along with other variables to alter the definition of "prospect." If the customer is determined to be a hot prospect, action must be taken very swiftly before the deposit is designated for alternate uses.

The market is still in its early stages, but individual companies are using analytics to set up decisions that can be enacted in real time or near-real time. SPSS' PredictiveCallCenter is one example. SAS Interaction Management identifies when customer behavior becomes unusual. Hosted Web analytics from companies such as NetIQ (WebTrends) and WebSideStory can be configured to offer reports in near-real time.

The live interactions are usually sales or service oriented; the decision-making rules and analytics that identify the rules can emanate from sales, service or marketing. The sales interactions (including pre-sales informational contact) can occur between the customer/prospect and a Web site, live salesperson or automated phone menu. In all cases, the "next step" decisions for guiding the sales process are fed in real time to the site, sales-person or server. Which Web page to show next, what product to cross-sell or up-sell and even the "best" price and terms of the deal can be determined with analytics. Similarly, the offer that a service center agent makes to resolve a customer complaint can be optimized in terms of variables such as the potential value of the customer, likelihood of successful resolution and specific content of the offer.

BPM/Financial Analytic Applications

Most CFOs and their teams feel pressure to deliver financial information on a timely basis. New certification requirements under Sarbanes-Oxley have taken information management processes to an entirely new level. No longer can finance teams be tied to lengthy period-end financial closing processes or cumbersome, manually intensive report preparation processes that precede actual performance reporting and analysis. CFOs recognize that current reporting processes provide the real-time visibility and centralized controls that will enable them to certify the accuracy of financial results and internal controls under tightening deadlines and increased SEC scrutiny.

The Sarbanes-Oxley Act accelerates reporting deadlines and requires all publicly held companies to formally certify results based on adequate internal controls to the SEC. This certification requires far more than annual and quarter-end reporting and audit procedures and is best facilitated by consistent, automated processes; real-time visibility into results; and proactive monitoring of potential risks. In particular, Section 409 of the Sarbanes-Oxley Act requires "real-time issuer disclosures" on a "rapid and current basis" concerning material changes to a company's financial condition or operations. These disclosures "may include trend and qualitative information along with graphic presentations" as "is necessary or useful for the protection of investors and in the public interest."

These requirements are driving finance organizations to look at the currently available accounting, consolidation and reporting applications to make a determination as to what new investments need to be made to implement quick, high-value improvements. Additionally, automation of financial and control-based business processes supported by collaborative technologies provide the most value in supporting compliance if key events can be monitored, analyzed and acted upon in a consistent manner. Therefore, event-based BI becomes a key component of achieving sustainable compliance. (See Figure 2.)

Figure 2: A Framework for Supporting Sarbanes-Oxley Section 409

To support this event-based collaborative compliance framework, data integration is a key enabling technology. Financial data alone is not sufficient, as key events that require increased visibility are part of day-to-day operations. A material change might be a loss of a key customer or a key supplier. Therefore, data from non-financial systems will need to be monitored along with financial data so that financial officers can comply with the stricter reporting requirements.


When is an investment in event-based BI justified? It depends on the business process being monitored and the cycle of decision making and review. If a decision is made once a year (as in a traditional annual budgeting process), event-based BI is a needless and expensive luxury. However, when the timing of decisions or potential reporting of corporate exposure depends on events, event-based BI is a necessity. Examples are requirements to notify shareholders when there is a material deviation anticipated from stated goals or the need to notify a contract manufacturer when the demand forecast is about to be invalidated by a rush of new orders. In such cases, scheduled reporting falls short.

Although the adoption rate for business activity monitoring is low today, expect future adoption to increase at unequal rates according to vertical industry and business process within an industry. It all depends on the needs of the application.

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