Question Asma Computing & ICT

Model Management Subsystem

Please can you write me a summary about the Model Management Subsystem?

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Answer Expert #27149

The Model Management Subsystem (also known as the MMSS) is a concept that is often encountered in the Knowledge Management (KM) and Management Information System (MIS) literature. In principle, the expression refers to a software package that includes financial, statistical and various other quantitative analytical tools to support the management in its decision making (Little and Cassettari, 1984).

In a wider context, the Model Management Subsystem is part of an organisation’s Decision Support System (DSS) (Sucar, 2012). The role of a model management subsystem is to provide a platform for organisations for the effective execution of quantitative management models. The accounting, the inventory, the finance, the production, the research and development (R&D), quality control, marketing and even the HR department can benefit from the different models used to support management decision making with real-time data (Janakiraman et al. 2004). For accounting, finance, R&D, and purchases, linear programming is used, whereas for production, marketing and personal management purposes, PERT/CPM simulations and game theory are the models which are usually applied.

To conclude, the Model Management Subsystem is a software solution to combine and manage the database for other Decision Supporting Systems utilised by the organisation. It serves as an interactive interface between the system and the user to enhance the quality of business decisions using real-time data.

References

Janakiraman, V.S., Sarukesi, K. and Surakest, K. (2004) Decision support systems. New Delhi: Prentice-Hall of India Pvt.

Little, J.D.C. and Cassettari, M.N. (1984) Decision support systems for marketing managers. New York, NY: AMA Membership Publications Division, American Management Associations.

Sucar, E.L. (2012) Decision theory models for applications in artificial intelligence: Concepts and solutions. Edited by Luis Enrique Sucar, Eduardo F. Morales, and Jesse Hoey. United States: Information Science Reference.