ISYS1000 Lecture Notes - Lecture 5: Predictive Modelling, Business Cycle, Online Analytical Processing
29 May 2018
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Module 5 – Business Intelligence
LEARNING OUTCOMES
5.1 Decision making
5.2 What is business intelligence?
5.3 Business intelligence applications for data analysis
5.4 Business intelligence applications for presenting results
5.5 Business intelligence in action: corporate performance management
5.1 DECISION MAKING
THREE BASIC MANAGERIAL ROLES
Interpersonal roles: figurehead, leader, liaison
Informational roles: monitor, disseminator, spokesperson, analyser
Decisional roles: entrepreneur, disturbance handler, resource allocator, negotiator
Early IS primarily supported the informational roles. Recently however, IS have been
developed that support all three roles.
DECISION MAKING MODEL
Herbert Simon described decision making as composed of:
- Intelligence phase
- Design phase
- Choice phase
This model is generalised; in that it is intended to encompass multiple conditions that might
occur when making a decision. For some decisions, some steps or phrases may be minimal,
implicit (understood), or absent.
In the below figure, it must be noted that there is a continuous flow of information from
intelligence, to design, to choice (bold lines), but at any phase there may be a return to a
previous phase (broken lines). Modelling how decisions might be made provides a picture of
where we can strategically insert CT-driven Business Intelligence (BI) applications.
find more resources at oneclass.com
find more resources at oneclass.com
WHY MANAGERS NEED IT/ICT SUPPORT
The number of alternatives that need to be considered is always increasing. Decisions are
often made under time pressure, and are becoming more complex. Decision makers – and
the information they need – can be situated in different locations. Decision makers also
must find ways to engage expertise or conduct group decision making. ICT-driven analysis
and support can be of enormous help, which poses the question, what ICTs are available to
support managers?
A FRAMEWORK FOR COMPUTERISED DECISION ANALYSIS
This framework assumes decision-making processes fall along a continuum ranging from
highly structured to highly unstructured.
Structured decisions
Routine and repetitive problems with standard procedures and solutions.
- Phases of the decision process are laid out in a particular sequence, procedures for
obtaining the best solution are known
- These types of decisions are candidates for Business Intelligence (BI) driven decision
automation
Unstructured decisions
Fuzzy, complex problems with no cut-and-dried procedures and solutions
- Unstructured problems so there is no standardised procedure for carrying phases
- Typical e.g. hiring an executive
- BI cannot make unstructured decisions; it can provide information that assists
decision makers
Consider:
Problem Structure
Decision making processes fall along a continuum ranging from highly structured to highly
unstructured
The nature (or context) of decisions
Managerial decisions fall into one of three broad categories:
1. Operational control: specific tasks efficiently and effectively
2. Management control: using resources to accomplish org. goals
3. Strategic planning: long-range goals/policies for growth
Decision Matrix
Problem structure and decision nature are positioned at right angles to each other and the
cells below represent the problem-space/solutions specific to when a problem
type/structure is encountered in a decision context. Cells are numbered because they
represent a type/context variable that can be managed by specific staff members.
Cells 7 and 3 are blank, as operational managers do not make strategic decisions, and senior
executives are not involved in day-to-day ops.
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
5. 5 business intelligence in action: corporate performance management. Decisional roles: entrepreneur, disturbance handler, resource allocator, negotiator. Recently however, is have been developed that support all three roles. Herbert simon described decision making as composed of: This model is generalised; in that it is intended to encompass multiple conditions that might occur when making a decision. For some decisions, some steps or phrases may be minimal, implicit (understood), or absent. In the below figure, it must be noted that there is a continuous flow of information from intelligence, to design, to choice (bold lines), but at any phase there may be a return to a previous phase (broken lines). Modelling how decisions might be made provides a picture of where we can strategically insert ct-driven business intelligence (bi) applications. The number of alternatives that need to be considered is always increasing. Decisions are often made under time pressure, and are becoming more complex.
