veloped for other purposes, apart from performance management. A very common example is the development of a customer intelligence system, in which the aim is to build customer insight in order to adopt products and services acA simple analysis of the functionality of a decision support system, is presented. In an effort to analyze the performance of a Business, and develop strategy for the future positioning in a competitive environment, the dimension of time is crucial (this is why all data warehouse systems have a time dimension and maintain historical data). In this article series, we describe three functionality categories of decision support systems:part 1. Detailed capture of performancepart 2. Performance analysis part 3. Modeling and prediction Categories are presented in an increasing complexity and business value sequence. They do not necessarily represent maturity levels, since each category is developed and matured as it is enriched with new capabilities and adopted to the dynamically changing informational and analytical Business needs. DSS systems may be developed for other purposes, apart from performance management. A very common example is the development of a customer intelligence system, in which the aim is to build customer insight in order to adopt products and services accion of time is crucial (this is why all data warehouse systems have a time dimension and maintain historical data). In this article series, we describe three functionality categories of decision support systems:part 1. Detailed capture of performancepart 2. Performance analysis part 3. Modeling and prediction Categories are presented in an increasing complexity and business value sequence. They do not necessarily represent maturity levels, since each category is developed and matured as it is enriched with new capabilities and adopted to the dynamically changing informational and analytical Business needs. DSS systems may be developed for other purposes, apart from performance management. A very common example is the development of a customer intelligence system, in which the aim is to build customer insight in order to adopt products and services ac Detailed capture of performancepart 2. Performance analysis part 3. Modeling and prediction Categories are presented in an increasing complexity and business value sequence. They do not necessarily represent maturity levels, since each category is developed and matured as it is enriched with new capabilities and adopted to the dynamically changing informational and analytical Business needs. DSS systems may be developed for other purposes, apart from performance management. A very common example is the development of a customer intelligence system, in which the aim is to build customer insight in order to adopt products and services acessarily represent maturity levels, since each category is developed and matured as it is enriched with new capabilities and adopted to the dynamically changing informational and analytical Business needs. DSS systems may be developed for other purposes, apart from performance management. A very common example is the development of a customer intelligence system, in which the aim is to build customer insight in order to adopt products and services acveloped for other purposes, apart from performance management. A very common example is the development of a customer intelligence system, in which the aim is to build customer insight in order to adopt products and services accordingly.

1. Detailed capture of business performance A basic management principle is the following: ‘you cannot manage what you cannot quantify and measure’. Within this framework, each Business aims to develop infrastructures which shall enable it, to capture detailed measurements of the current business process performance and gradually build detailed historical performance data. ‘How successful the Business was’ for a given time interval, is captured. Business performance is captured in a detailed mode for all ‘dimensions’ involved (indicatively): Business processes and activities, Products marketed, Customer touch points employed, Geography, Customer segments, Business Units involved. Data analysis that takes place at the ‘business performance capture’ level, is usually predefined. Predefined Key performance indicators (KPIs) are regularly calculated