IT: Chapter 10: Improv9ing Decision and Managing Knowledge Flashcards
1
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Types of Decisions ABBREV
A
USS
2
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Types of Decisions
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Unstructured
Structured
Semistructured
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Unstructured decisions
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those in which the decision maker must provide judgment, evaluation and insight to solve the problem
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Structured Decisions
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repetitive and routine, and they involve a definite procedure for handling them so that they do not have to be treated each time as if they were new
5
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Semistructured
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only part of the problem has a clear-cut answer provided by an accepted procedure
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Semistructured Effects ABBREV
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DES
7
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Semistructured Effects
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- Disparate computer systems easily communicate with one another
- Lower market entry costs
- Lower consumers’ search costs
8
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Entry costs
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the costs merchants must pay simply to bring their goods to market
9
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Search costs
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the effort required to find suitable products
10
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Unstructured decisions made by
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Senior Management
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Semistructured decisions made by
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middle management
12
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Structured decisions made by
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Operational management
individual employees and teams
13
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The Decision-Making Process ABBREV
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IDCI
14
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The Decision-Making Process
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Intelligence
Design
Choice
Implementation
15
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Intelligence
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consists of discovering, identifying, and understanding the problems occurring in the organization
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Intelligence Question
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What is the problem?
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Design
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involves identifying and exploring various solutions to the problem
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Design Question
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What are the possible solutions?
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Choice
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consists of choosing among solution alternatives
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Choice Question
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What is the best solution?
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Implementation
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involves making the chosen alternative work and continuing to monitor how well the solution is working
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Implementation Question
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Is the solution working?
Can we make it work better?
23
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High velocity decision-making
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The intelligence, design, choice, and implementation parts of the decision-making process are captured by computer algorithms that define steps to be followed to produce a decision, humans eliminated
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Quality of decisions making ABBREV
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ACFSCD
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Quality of decisions making
- Accuracy
- Comprehensiveness
- Fairness
- Speed (efficiency)
- Coherence
- Due Process
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Accuracy
Decision reflects reality
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Comprehensiveness
Decision reflects a full consideration of the facts and circumstances
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Fairness
decision faithfully reflects the concerns and interests of affected parties
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Speed (efficiency)
decision making is efficient with respect to time and other resources, including the time and resources of affected parties, such as customers
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Coherence
decision reflects a rational process that can be explained to others and made understandable
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Due Process
decision is the result of a known process and can be appealed to a higher authority
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Six elements in business intelligence environment ABBREV
DBBMDU
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Six elements in business intelligence environment
1. Data from the business environment
2. Business intelligence infrastructure
3. Business analytics toolset
4. Managerial users and methods
5. Deliver platform
6. User interface
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Data From the business environment
Deal with both structured and unstructured data that needs to be integrated and organized to be analyzed and used by human decision makers
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Business intelligence infrastructure
Captures all the relevant data that may be stored in transactional databases or combined and integrated into an enterprise data warehouse or series of interrelated data mart
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Business analytics toolset
A set of software tools used to analyze data and produce reports, respond to questions by managers, and track the progress of the business using key indicators of performance
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Managerial users and methods
Mangers impose order on the analysis of data using a variety of managerial methods that define strategic business goals and specify how progress will be measured
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Delivery platform
MID, DSS, ESS
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MID, DSS, ESS is the result of
business intelligence and analytics are delivered to managers and employees in a variety of ways
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MID, DSS, ESS deliver
information and knowledge to different people and levels in the firm
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User Interface
Analytics software suites emphasize visual techniques such as dashboards and scoreboards
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6 analytic functionalities that BI system deliver ABBREV
PPDADF
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6 analytic functionalities that BI system deliver
```
Production reports
Parameterized reports
Dashboards/scorecards
Ad-hoc query/search/report creation
Drill-down
Forecasts, scenarios, models
```
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Production reports
Predefined reports based on industry-specific requirements
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Parameterized reports
Users enter several parameters as in a pivot table to filter data and isolate impacts of parameters
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Dashboards/scorecards
Visual tools for presenting performance data defined by users
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Ad-hoc query/search/report creation
Allow users to create their own reports based on queries and searches
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Drill-down
The ability to move from a high level summary to a more detailed view
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Forecasts, scenarios, models
Include capabilities for linear forecasting, “what if” scenario analysis, and statistical analysis
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Predictive analysis
use statistical analysis and other techniques to extract information from data and use it to predict future trends and behavior patterns
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Predictive analysis extracts
information from data and uses it to predict future trends and behavior patterns
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Predictive Analysis accuracy
65%-90%
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Data visualization and visual analytics
help users see patterns and relationships in large amounts of data that would be difficult to discern if the data were presented as traditional lists of text or numbers
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Data in data visualization and visual analytics are presented in
rich graphs, charts, dashboards, maps
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Geographic Information Systems (GIS)
special category of tools for helping decision makers visualize problems requiring knowledge about the geographic distribution of people or other sources
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Example of GIS
GIS to help government calculate response times to emergencies
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Business Intelligence Users
Casual users
| Power users
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Casual users
consumers of BI output
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What % of employees are Casual Users?
80%
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Power Users
the producers of reports, new analysis, models, and forecasts
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What % of employees are Power Users?
20%
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How do Senior executives use BI?
monitor firm activities using visual interfaces like dashboards and score cards
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How do Middle managers and analysts use BI?
data and software, entering queries and slicing and dicing the data along different dimensions
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How do Operational employees use BI?
looking at mostly pre-packaged reports
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Decision-support system DSS
BI delivery platform for “super-users” who want to create own reports, use more sophisticated analytics and models
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Types of Decision-support system ABBREV
WSBPI
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Types of Decision-support system
- What-if analysis
- Sensitivity analysis
- Backward sensitivity analysis
- Pivot Tables
- Intensive modeling techniques
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What-if analysis
working forward from known or assumed conditions, allows the user to vary certain values to test results to predict outcomes if changes occur
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Sensitivity analysis
ask what-if questions repeatedly to predict a range of outcomes when one or more variables are changed multiple times
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Backward sensitivity analysis
helps decision makers with goal seeking
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Pivot tables
identify and understand patterns in business information that may be useful for semi structured decision making
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Decision Support for Senior Management ABBREV
EBKBD
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Decision Support for Senior Management
- Executive Support systems (ESS)
- Balanced scorecard method
- Key Performance indicators (KPIs)
- Business Performance management (BPM)
- Drill-down capabilities
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Executive Support Systems (ESS)
helps senior executives focus on the really important performance information that affects the overall profitability and success of the firm
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Balanced scorecard method
a framework for operationalizing a firm’s strategic plan by focusing on measurable outcomes on four dimension of firm performance
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Key Performance indicators (KPIs)
the measures proposed by senior management for understanding how well the firm is performing along any given dimension
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Business Performance management (BPM)
attempts to systematically translate a firm’s strategies into operational targets
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Drill-down capabilities
managers need more detailed views of data
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ESS combines
internal data with external and provides access to news services, financial market databases, economic information, etc.
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Group decision-support system (GDSS)
an interactive computer-based system for facilitating the solution of unstructured problems by a set of decision makers working together as a group in the same location or in different locations
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GDSS are used in
conference rooms with special hardware and software for collecting, ranking, storing ideas, and decision
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GDSS promotes
a collaborative atmosphere by guaranteeing contributors’ anonymity
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GDSS supports
increased meeting sizes with increased productivity
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GDSS software follows
structured methods for organizing and evaluating ideas
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Artificial intelligence (AI)
consists of computer-based systems (both hardware and software) that attempt to emulate human behavior and thought patterns
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Intelligent Systems Include ABBREV
ECFNGI
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Intelligent Systems Include
- Expert Systems
- Case-based reasoning
- Fuzzy logic
- Neutral networks
- Genetic algorithms
- Intelligent agents
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Expert systems
captures human expertise in a limited domain of knowledge as a set of rules in a software system that can be used by others in the organization
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Expert systems model
human knowledge as a set of rules that are collectively called the knowledge base
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How many Knowledge base rules?
200-10,000
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Case-based reasoning (CBR)
knowledge and past experiences of human specialists are represented as cases and stored in a database for later retrieval when the user encounters a new case with similar parameters
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Case-based reasoning system searches for
stored cases with problem characteristics similar to new one, finds closest fit, and applies solutions of old case to new case
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Successful and Unsuccessful CBR applications are
tagged and linked in database
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Case-based reasoning (CBR) is used in
medical diagnostic systems, customer support
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Fuzzy logic
a rule-based technology that represents such imprecision by creating rules that use approximate or subjective values
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Fuzzy logic describes
a particular phenomenon or process linguistically and then represents that description in a small number of flexible rules
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Fuzzy logic provides
solutions to problems requiring expertise that is difficult to represent in the form of IF-Then rules
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Neural Networks
used for solving complex, poorly understood problems for which large amounts of data have been collected
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Neural Networks use
hardware and software that parallel the processing patterns of a biological brain
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Neural networks learn
patterns from large quantities of data by searching for relationships, building models, and correcting over and over again the model’s own mistakes
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How do humans "train" neural networks?
by feeding it data for which the inputs produce a known set of outputs or conclusions
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Neural Networks used for
solving complex, poorly understood problems for which large amounts of data have been collected
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Genetic algorithms
useful for finding the optimal solution for a specific problem by examining a very large number of alternative solutions for that problem
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Genetic algorithms are based on
techniques inspired by evolutionary biology: inheritance, mutation, selection, etc.
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Genetic algorithms work by
representing a solution as a string of 0s and 1s, then searching randomly generated strings of binary digits to identify best possible solution
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Genetic algorithms are used to
solve complex problems that are very dynamic and complex, involving hundreds or thousands of variables or formulas
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Intelligent agents
software programs that work in the background without direct human intervention to carry out specific, repetitive, and predictable tasks for an individual user, business process, or software application.
108
Knowledge management
refers to the set of business processes developed in an organization to create, store, transfer, and apply knowledge
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Knowledge management increases
the ability of organization to learn from environment and to incorporate knowledge into business processes and decision making
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Knowledge management is knowing
how to do things effectively and efficiently in ways that other organizations cannot duplicate is major source of profit and competitive advantage
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Three kinds of Knowledge ABBREV
SST
112
Three kinds of Knowledge
```
Structured
Semistructured
Tacit knowledge (unstructured)
```
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Structured
structured text documents
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Semistructured
e-mail, voice mail, digital pictures, etc
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Tacit Knowledge (Unstructured)
knowledge residing in heads of employees, rarely written down
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Enterprise-wide knowledge management systems
general-purpose, firmwide systems that collect, store, distribute, and apply digital content and knowledge
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Enterprise content management systems
have capabilities for knowledge capture, storage, retrieval, distribution, and preservation to help firms improve their business processes and decisions
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Digital asset management systems
helps classify, store, and distribute digital objects like photographs, graphic images, video, audio
118
Enterprise Content management systems have capabilities for
collecting and organizing semi structured knowledge such as e-mail
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Knowledge network systems (expertise location and management systems)
provide an online directory of corporate experts in well-defined knowledge domains and use communication technologies to make it easy for employees to find the appropriate expert in company
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Digital asset management systems
helps classify, store, and distribute digital objects like photographs, graphic images, video, audio
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Social bookmarking
allows user to save their bookmarks to Web pages on public Web site and tag these bookmarks with keyboards
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Learning management systems (LMS)
provides tools for the management, delivery, tracking, and assessment of various types of employee learning and training
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Knowledge work systems (KWS)
specialized systems for engineers, scientists, and other knowledge workers that are designed to promote the creation of knowledge and to ensure that new knowledge and technical expertise are property integrated into the business
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Requirements of Knowledge work systems ABBREV
SCAU
119
Examples of knowledge work systems
- Computer-aided design (CAD) systems
- Virtual reality (VR) systems
- Virtual reality modeling language (VRML)
- Augmented reality (AR) systems
- Investment workstations
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Computer-aided design (CAD) systems
systems capable of generating realistic-looking three dimensional graphic designs that can be rotated and viewed from all sides
119
Virtual reality modeling language (VRML)
a set of specifications for interactive, three-dimensional modeling on the World Wide Web that organizes multiple media types, including animation, images, and audio, to put users ina simulated real-world environment
119
Augmented reality (AR) systems
a related technology for enhancing visualization that provides a live direct or indirect view of a physical real-world environment whose elements are augmented by virtual computer-generated imagery
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Investment workstations
Integrate a wide range of data both internal and external sources, including contact management data, real-time and historical market data, and research reports.
119
Folksonomies
the user-created taxonomies created for shared bookmarks and social tagging
119
Requirements of Knowledge work systems
- Specialized tools
- Computing power to handle sophisticated graphics or complex calculations
- Access to external databases
- User-friendly interfaces
119
Examples of knowledge work systems ABBREV
CVVAI
119
Virtual reality (VR) systems
use interactive graphics software to create computer-generated simulations that are so close to reality that users almost believe they are participating in a real-world situation.
