At a very generic level, a major reason for real time business intelligence is to allow for organizations to become nimble in their reaction to emerging market forces and capitalize on opportunities (improve market share/topline),optimize resource utilization and performance (improve bottomline) and reduce the impact of failures (costs and losses).
Business processes in manufacturing organizations are both structured and unstructured, and it is generally agreed that, typically, not more than 10% of the business processes in an organization are structured and orchestrated well by Business Process Modeling tools. Such business process modeling tools ensure that the processes are performed using best practices and there are no inefficiencies. However, even a remarkable adherence to the best practices are only going to provide marginal improvement since the overall scope of improvement is only applied on 10% of the processes.
Therefore, the major improvement has to happen in the on-going processing and orchestration of the major chunk of this 90% gap in information that lies buried in several distributed systems/applications and is not “visible” when needed but “shows up” after significant latency (by which time a costly decision could have already been taken). This is where the real time business intelligence systems using rule engines, dashboards and action agents have a major role to play.
EMG is a real time BI system (also called as Business Activity Monitoring System – BAM) in that it has all of the infrastructure to acquire real time data, trigger rules based on real time events, generate action and relate that data to a context using its “business context” infrastructure.
For example, in a typical manufacturing industry, decisions may focus on resource allocation optimization based on current demand, or waste reduction as supported by Lean Manufacturing, or even, routine monitoring of the manufacturing performance against well established metrics. Furthermore, an enterprise user of such a system would like to query about some “important events” that are occuring -while they are occurring.
Typically, EMG works by capturing user defined real time events from operational systems. Such events can range from scanning bar codes of material or products to receiving plant floor machine condition information, production orders, manual entries of production information, rejects, root causes of failures, etc-- and then correlating these events with relevant contextual data. These contextual definitions can then be presented to a rules engine that can trigger some actions based on these events.
Furthermore, EMG allows for deep visibility into operations from the corporate dashboard and can perform the event-context correlation extremely quickly. |
