Method and apparatus combining control theory and business performance management

• US 8,626,544 B2
• Filed: 03/28/2008
• Issued: 01/07/2014
• Est. Priority Date: 04/29/2005
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: An, Lianjun, Ramachandran, Bala, Sourirajan, Karthik
• Primary Examiner(s): Miller, Alan S
• Application Number:
  US12/057,917
• Publication Number:
  US 20080208659A1
• Time in Patent Office: 2,111 Days
• Field of Search: 705 711- 742, 700 29-107
• US Class Current: 705/7.12
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 99/00 Subject matter not provided for in other groups of this subclass

Abstract

A control methodology and component in Business Performance Management (BPM) Systems. This enables firms to exploit control theoretic techniques for Business Performance Management. Information from BPM systems is used to calibrate models of the business process. This model is then used to assess and optimize control actions to manage business performance, on the basis of which a control action is selected for business process execution.

Claims

1. A computer implemented method for analyzing data from Business Performance management systems and determining an action to manage Business Process Performance, the computer performing the steps of:

developing, updating and calibrating a business performance model based on historical business performance metrics and control actions,

defining business objectives based on desired business performance metrics,

defining an objective function for capturing a trade-off between responsiveness and volatility of said business performance metrics,

analyzing a plurality of control policies by using the business performance model to predict responsiveness and volatility of future business performance metrics for each of said plurality of control policies, each

selecting control policy from said plurality that is an optimal trade-off between responsiveness and volatility of said business performance metrics based on the business objectives, and

deploying control actions based on the optimal control policy.

2. A method according to claim 1, wherein the control policy is chosen adaptively based on a current business environment and the desired business performance metrics.

3. A method according to claim 1, wherein the optimal control policy is chosen based on tradeoff analysis done using business guidelines on different performance objectives.

4. A method according to claim 1, wherein data from Supply Chain Management systems are analyzed and an action to manage Supply Chain Performance is determined, the computer further performing the steps of:

developing, updating and calibrating supply chain models based on supply chain data, and

defining business objectives based on desired business performance measures.

5. A method according to claim 4, the computer further performing the steps of:

analyzing control policies for placing replenishment orders by using the supply chain model to predict future supply chain performance for different control policies,

selecting an optimal control policy, and

placing supply chain orders based on the optimal control policy.

6. A computer implemented method for analyzing data from Business Performance Management systems and determining an action to manage Business Process Performance, the computer performing the steps of:

developing, updating and calibrating a business performance model based on business process data,

defining business objectives based on desired business performance metrics,

defining an objective function for capturing a trade-off between responsiveness and volatility of said business performance metrics,

analyzing a plurality of control policies by using the business performance model to predict responsiveness and volatility of future business process performance for each of said plurality of control policies,

selecting a control policy from said plurality that is an optimal trade-off between responsiveness and volatility of said business performance metrics based on the business objectives, and

deploying control actions based on the optimal control policy.

7. A method according to claim 6, wherein the steps are implemented in a controller as a component in a business performance management system.

8. A non-transitory signal-bearing medium tangibly embodying a program of machine readable instructions executable by a digital processing apparatus to perform a method for analyzing data from Business Performance Management systems and determining an action to manage Business Process Performance comprising the steps of:

developing, updating and calibrating a business performance model based on historical business performance metrics and control actions,

defining business objectives based on desired business performance metrics,

defining an objective function for capturing a trade-off between responsiveness and volatility of said business performance metrics,

analyzing control policies by using the business performance model to predict responsiveness and volatility of future business performance metrics for different control policies,

selecting a control policy that is an optimal trade-off between responsiveness and volatility of said business performance metrics based on the business objectives, and

deploying actions based on the optimal control policy.

9. A computer based system for analyzing data from Business Performance management systems and determining an action to manage Business Process Performance comprising:

input means for receiving one or more set points for metrics and outputs generated by a Business Performance Management (BPM) system based on the events and metrics that are processed by the BPM system and producing a differential metric output;

a controller receiving said differential metric output and a business objective based on desired business performance metrics and developing, updating and calibrating a business performance model based on historical business performance metrics and control actions, said controller defining an objective function for capturing a trade-off between responsiveness and volatility of said business performance metrics, analyzing a plurality of control policies by using the business performance model to predict responsiveness and volatility of future business performance metrics for each of said plurality of control policies and selecting a control policy from said plurality that is an optimal trade-off between responsiveness and volatility of said business performance metrics based on the business objective;

a business process execution means deploying actions selected by said controller based on the optimal control policy; and

means measuring events and metrics generated as a result of deploying actions by the business process execution means, which measured events and metrics are processed by the BPM system to generate feedback to the input means.