David Luckham, inventor of CEP
Professor Emeritus of Electrical Engineering, Stanford University

What is CEP?

Complex Event Processing (CEP) is an emerging technology for building and managing information systems. The goal of CEP is to enable the information contained in the events flowing through all of the layers of the enterprise IT infrastructure to be discovered, understood in terms of its impact on high level management goals and business processes, and acted upon in real time. This includes events created by new technologies such as RFID.

Visit the comprehensive CEP website.

Other articles by Dr. Luckham:

BAM And CEP: A Marriage Of Necessity Or: Why BAM Must Use CEP
BAM Providers As Online Banking Fraud Preventers
The Beginnings of IT Insight: Business Activity Monitoring
Grand Visions For e-Commerce Require Solving 'IT Blindness'
Avoiding Disasters Waiting To Happen
"/> Business Activity Monitoring and Business Intelligence- Page 2
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Operations Intelligence

Having a combination of BI and BAM technologies to get comprehensive business intelligence information from business processes is a competitive differentiator for most businesses. Staying ahead of the competition requires the ability to predict and respond to trends in the marketplace in real time, rather than react to isolated events or a set of events that have already happened. The fusion of the expertise offered by both BAM and BI technologies enables operational intelligence—in other words, the ability of a business to react to an event or process exception in real time.

The ideal use cases for operations intelligence—those that are interested in proactively catching business exceptions before or right after they occur—can’t rely solely on traditional BI systems that, in turn, run on a scheduled basis and not when exceptions occur. In some cases, it’s important to capture non-events and their impact on businesses. For example, in a call center business, if a valued customer’s call with an operator exceeds a threshold resolution time, a floor manager might be advised via a proactive alert to intervene and resolve the situation. Here, the call-ending event has not occurred and timely knowledge of this fact valuable to the business.

BAM can potentially use historic analyzed facts from a BI system as its measuring instruments to derive the described thresholds to the data it analyzes. BAM systems can integrate with data mining and OLAP tools to provide monitoring capabilities on top of the analyzed information to facilitate closed-loop analytics. For example, if a data-mining tool reports a list of suspected fraud accounts, this information can be fed into a BAM tool, and the system will make sure the accounts are frozen and the fraud detection agents are engaged. It can also make sure the accounts are fixed within a particular timeframe—and if that deadline isn’t reached, it can issue proactive alerts to interested business users.

Consider a supply-chain visibility and logistics example: A retail clothing business wants to enhance its operations intelligence infrastructure. Information analyzed by BI creates data for year-over-year consumer salary comparisons, market-basket analysis, and forecasts. This information can be passed as measuring facts to a BAM system. If the analyzed facts suggest that over the last six quarters, the average buying capacity of an area has dropped, BAM could trigger an action that intercepts a new order for purchasing certain luxury items in the order fulfillment system if the quantity is the same as previously purchased. Or, if BI-analyzed facts show that a particular item has disproportionate sales in two outlets over a period of time, BAM could issue a request to transfer more of those goods to one of the outlets.


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