Taking advantage of BAM derived business intelligence
September 29, 2006
For many years I developed real-time data distribution, display and analysis software for the financial markets front office. Traders are a great example of a human BAM. Traders watch real-time data feeds for business activity that interests them. They filter it using both their mental skills and their workstation software. They bring historical context to their analysis, doing complex event processing and running rules in their heads and in their spreadsheets. They make decisions and execute trades that affect the state of the market, altering the business activity they are monitoring. The trader is looking for opportunities with their “business”, as opposed to looking for problems. The goal of BAM is not just to know that everything is running smoothly, its to look for opportunities to improve things. It is not surprising that Business Activity Monitoring and Business Intelligence software has its origin in the financial markets.
Having a real-time view of our business operations is largely pointless if we cannot rapidly effect change to put problems right and take advantage of new opportunities. Building business processes on the agile, SOA-enabling, orchestration and services technology provided by an Enterprise Service Bus is the key to taking advantage of new opportunities and fixing problems before they cost us money. The ESB is a natural way to collect, correlate and feed the raw data required by the BAM layer, it then allows us to rapidly improve our processes in response to changing conditions.
Feeding aggregated business intelligence back into processes in real-time creates interesting possibilities. Suppose we’re orchestrating a supply chain. If we have a number of Courier services in the supply chain, that the Shipping service can request pickups from (i.e. pickup packages at the various Warehouses for delivery to customers), we can monitor the timeliness of the pickups and check for Couriers falling behind, failing to pickup on time and failing to deliver at agreed SLAs. We can feed this business intelligence back into the Shipping service, so that it favours couriers meeting their SLAs.