ü Employees must be able to obtain and analyze to many different levels, formats and granularity of organizational information to make decision.
ü Successfully collecting, compiling, sorting and analyzing information can provide tremendous insight into how an organization is performing.
THE VALUE OF TIMELY INFORMATION
ü Timeliness is an aspect of information that depends on the situation:
- Real-time information – immediate up-to-date information.
- Real-time system – provides real-time information in response to query requests.
THE VALUE OF QUALITY INFORMATION
ü Business decisions are only as good as the quality of the information used to make the decisions.
ü You never want to find yourself using technology to help you make a bad decision faster.
ü Characteristic of high-quality information include:
UNDERSTANDING THE COST OF POOR INFORMATION
ü The four primary sources of low quality information include:
I. Online customers intentionally enter inaccurate information to protect their privacy.
II. Information from different systems have different entry standards and formats.
III. Call center operators enter abbreviated or erroneous by accident or to save time.
IV. Third party and external information contains inconsistencies, inaccuracies and errors.
ü Potential business effects resulting from low quality information include:
- Inability to accurately track customers.
- Difficulty identifying valuable customers.
- Inability to identify selling opportunities.
- Marketing to nonexistent customers.
- Difficulty tracking revenue due to inaccurate invoices.
- Inability to build strong customer relationship.
ü Understanding the benefits of good information:
s High quality information can significantly improve the chances of making a good decision.
s Good decision can directly impact an organization’s bottom line.
> Reasons for the growth of decision making information systems:
- People need to analyze large amounts of information.
- People must take decision quickly.
- People must apply sophisticated analysis techniques, such as modeling and foresting, to make good decisions.
- People must protect the corporate asset of organizational information.
> A simplified representation or abstraction of reality.
INFORMATION TECHNOLOGY SYSTEMS IN AN ENTERPRISE
> EXECUTIVES - EXECUTIVE INFORMATION SYSTEM (EIS).
> MANAGERS - DECISION SUPPORT SYSTEMS (DSS).
> ANALYSIS – TRANSACTION PROCESSING SYSTEMS (TPS).
EXECUTIVE INFORMATION SYSTEMS
> Executive information system (EIS) – a specialized DSS that supports senior level executives within the organization.
> Most EIS offering the following capabilities:
1. Consolidation– involves the aggregation of intelligent system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem.
2. Drill-down – enables, users to get details and details of details, of information.
3. Slice-and-dice – looks at information from different perspectives.
DECISION SUPPORT SYSTEMS
> Decision support systems (DSS) – models information to support managers and business professionals during the decision-making process.
> Three quantitative models used by DSS include:
1. Sensitively analysis – the study of the impact that changes in one (or more) parts of the model have on other parts of the model.
2. What-if analysis – checks the impact of a change in an assumption on the proposed solution.
3. Goal-seeking analysis – finds the inputs necessary to achieve a goal such as a desired level of output.
TRANSACTION PROCESSING SYSTEMS
>Moving up through the organizational pyramid users move from requiring transactional information to analytical information:
~ Transaction Processing System – the basic business system that serves the operational level (analysts) in an organization.
~ Online Transaction Processing (OLTP) – the capturing of transaction and event information using technology to (1) process the information according to defined business rules, (2) store the information, (3) update existing information to reflect the new information.
~ Online Analytical Processing (OLAP) – the manipulation of information to create business intelligence in support of strategic decision making.
> INTELLIGENT SYSTEM – Various commercial applications of artificial intelligence.
> ARTIFICIAL INTELLIGENCE (AI) – Simulates human intelligence such as the ability to reason and learn.
~ Advantages: can check info on competitor.
~ The ultimate goal of AI is the ability to build a system that can mimic human intelligence
~ Four most common categories of AI include:
1. Expert System – computerized advisory programs that imitate the reasoning processes of expert in solving difficult problems.
2. Neural Network – attempts to emulate the way the human brain works -fuzzy logic – a mathematical method of handling imprecise or subjective information.
3. Genetic Algorithm – an AI system that mimics the evolutionary, survival-if-the-fittest process to generate increasingly better solutions to a problem.
4. Intelligent Agent – special-purposed-knowledge-based information system that accomplishes specific tasks on behalf of its users.
> Data-mining software includes many forms of AI such as neural networks and expert system.
> Common forms of data-mining analysis capabilities include:
1. Cluster Analysis.
2. Association Detection.
3. Statistical Analysis.
> CLUSTER ANALYSIS – To divide an information set into mutually exclusive groups such that the members of each group are as possible to one another and the different groups are as far apart as possible.
> CRM systems depend on cluster analysis to segment customer information and identify behavioral traits.
> Association detection reveals the degree to which variables are related and the nature and frequency of these relationships in the information.
> Market basket analysis such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and services.
> STATISTICAL ANALYSIS performs such functions as information correlations, distributions, calculations and variance analysis.
> Forecast– predictions made on the basis of time-series information.
> Time-Series Information – time-stamped information collected at a particular frequency.