System and method for applying predictive metric analysis for a business monitoring subsystem

Abstract

Predictive metric analysis for business management is divided into build time, corresponding to the business owner view of the enterprise, and run time, corresponding to the information technology view of the enterprise. The build time consists of a predictive model and a monitoring model. These models go through transformation processes to the components of the run time. The run time components are a Metric Value Prediction Service (MVPS), which receives as input predictive model transformation and outputs predicted metric values, and a monitoring engine, which receives as input monitoring model transformation, the predicted metric values and business events from the business process. Various analytical engines can be plugged in to provide the predictive capabilities. Input is provided to a framework from various business systems which results in predicting the value of the metrics across the future time horizons.

1 . A method for providing predictive modeling capabilities to allow intelligent business performance management comprising the steps of: 
 using a computer to generate a meta model consisting of business metrics organized as a hierarchy with each metric having the ability to be associated with time as a look-ahead dimension;    using a computer to transform the meta model to service interface definition and related artifacts;    using a computer to transform the meta model into performance warehouse meta-data schemas to allow persistence of historical data; and    using a computer to receive requests for metric predictions and to use analytical techniques to service the requests in real time.    
     
     
         2 . The method of  claim 1 , wherein said meta model also comprises business metrics categorized within a predictive metric context to be used as input for predictive analysis.  
     
     
         3 . The method of  claim 2 , wherein said meta model also comprises trigger conditions describing how and when said predictive analysis will be triggered.  
     
     
         4 . A system for providing predictive modeling capabilities to allow intelligent business performance management comprising: 
 a computer generating a meta model consisting of business metrics organized as a hierarchy with each metric having the ability to be associated with time as a look-ahead dimension;    a computer transforming the meta model to service interface definition and related artifacts;    a computer transforming the meta model into performance warehouse meta-data schemas to allow persistence of historical data; and    a computer receiving requests for metric predictions and using analytical techniques to service the requests in real time.    
     
     
         5 . The system of  claim 4 , wherein said meta model also comprises business metrics categorized within a predictive metric context to be used as input for predictive analysis.  
     
     
         6 . The method of  claim 5 , wherein said meta model also comprises trigger conditions describing how and when said predictive analysis will be triggered.  
     
     
         7 . A computer-readable medium for providing predictive modeling capabilities to allow intelligent business performance management, on which is provided: 
 instructions for using a computer to generate a meta model consisting of business metrics organized as a hierarchy with each metric having the ability to be associated with time as a look-ahead dimension;    instructions for using a computer to transform the meta model to service interface definition and related artifacts;    instructions for using a computer to transform the meta model into performance warehouse meta-data schemas to allow persistence of historical data; and    instructions for using a computer to receive requests for metric predictions and to use analytical techniques to service the requests in real time.    
     
     
         8 . The computer-readable medium of  claim 7 , wherein said meta model also comprises business metrics categorized within a predictive metric context to be used as input for predictive analysis.  
     
     
         9 . The computer-readable medium of  claim 8 , wherein said meta model also comprises trigger conditions describing how and when said predictive analysis will be triggered.