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Information Systems - MGCR 331 002 > Chapter 12 > Flashcards

Flashcards in Chapter 12 Deck (29)
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1
Q

12.1 What are a manager’s three basic roles? Hint: IID

A

All managers perform three basic roles:

  1. Interpersonal roles: Figurehead, leader, liaison
  2. Informational roles: Monitor, disseminator, spokesperson, analyzer
  3. Decisional roles: Entrepreneur, disturbance handler, resource allocator, negotiator
2
Q

12.1 What is a decision?

A

A decision refers to a choice among two or more alternatives that individuals and groups make. Decision making is a systematic process.

Economist Herbert Simon (1977) described decision making as composed of three major phases: intelligence, design, and choice.

3
Q

12.1 Describe the three phases of the decision-making process? Hint: IDC

A

The decision-making process starts with the intelligence phase, in which managers examine a situation and then identify and define the problem or opportunity.

In the design phase, decision makers construct a model for addressing the situation.

The choice phase involves selecting a solution or course of action that seems best suited to resolve the problem. Computer-based decision support assists managers in the decision-making process.

4
Q

12.1 Why do managers need IT support?

A

The turbulent business environment and borderless world has created more business opportunities, but has also generated more data, and in turn more decisions to be made.

The number of alternatives is constantly increasing.

Most decisions must be made under time pressure.

It is often necessary to rapidly access remote information, consult with experts, or reference points as such.

The increased complexity of decisions require sophisticated analysis.

5
Q

12.1 What are the two major dimensions in the framework for computerized decision analysis?

A

Various types of decisions can be placed along two major dimensions: problem structure and the nature of the decision.

6
Q

12.1 What are the three categories of problem structures (framework for computerized decision analysis)?

A

Decision-making processes fall along a continuum ranging from highly structured to highly unstructured.

  1. Structured decisions
  2. Unstructured decisions
  3. Semistructured decisions
7
Q

12.1 What are structured decisions?

A

Structured decisions deal with routine and repetitive problems for which standard solutions exist, such as inventory control. The first three phases of the decision process—intelligence, design, and choice—are laid out in a particular sequence. These types of decisions are candidates for decision automation.

8
Q

12.1 What are unstructured decisions?

A

Unstructured decisions are intended to deal with “fuzzy,” complex problems for which there are no cut-and-dried solutions. An unstructured decision is one in which there is no standardized procedure. Human intuition and judgment often play an important role.

9
Q

12.1 What are semistructured decisions?

A

Semistructured decisions are decisions in which only some of the decision-process phases are structured. Semistructured decisions require a combination of standard solution procedures and individual judgment.

10
Q

12.1 What are the three categories of managerial decision-making (nature of decisions)? Hint: OMS

A
  1. Operational control: Executing specific tasks efficiently and effectively
  2. Management control: Acquiring and using resources efficiently in accomplishing organizational goals
  3. Strategic planning: The long-range goals and policies for growth and resource allocation
11
Q

12.2 What is business analytics?

A

Business analytics (BA) is the process of developing actionable decisions or recommendations for actions based on insights generated from historical data.

12
Q

12.2 What are the three specific analytics targets (in BA)?

A
  1. The development of one or a few related analytics applications:
    This target is often a point solution for a departmental need, such as campaign management in marketing.
  2. The development of infrastructure to support enterprise-wide analytics:
    This target may require other investments such as an enterprise data warehouse.
  3. Support for organizational transformation:
    With this target, a company uses business analytics to fundamentally transform the ways it competes in the marketplace.
    Business analytics supports a new business model, and it enables the business strategy.
13
Q

12.2 What are the steps in the business analytics process?

A
  1. Identifying business problem - “pain points”. Organizations turn to BA and its underlying technologies to help solve business problems.
  2. Data management
  3. Descriptive analytics, predictive analytics, prescriptive analytics
  4. Presentation tools - Many organizations have employees who “translate” the results of these analyses into business terms for the decision makers. These employees often use presentation tools in the form of dashboards to communicate the message visually.
  5. Asking the right question - Decision makers must be ready to “ask the next question.” Everyone involved in the BA process must use their creativity and intuition.
14
Q

12.2 What is data management in the BA process? Hint: ETL

A

Organizations are now able to combine and analyze structured and unstructured data from many sources in the form of Big Data.

At this point, organizations integrate and “clean” these data into data marts and data warehouses through a process called extract, transform, and load (ETL). The data in the data warehouse are now available to be analyzed by data scientists, analysts, and decision makers.

15
Q

12.2 What are the main business analytics tools?

A
  • Excel (most popular BA tool)
  • Multidimensional analysis (also called OLAP)
  • Data mining
  • Decision-support systems
  • Statistical procedures: descriptive statistics; affinity analysis; linear, multiple and logistic regression; and others
16
Q

12.3 What is data reduction?

A

Data reduction is the conversion of raw data into a smaller amount of more useful information. Descriptive, predictive, and prescriptive analytics are essentially steps in data reduction.

17
Q

12.3 What is descriptive analytics?

A

Descriptive analytics is the first step in data reduction. Descriptive analytics summarizes what has happened in the past and enables decision makers to learn from past behaviors.

18
Q

12.3 What are the BA tools in descriptive analytics?

A
  • Online analytical processing (OLAP) (i.e., multidimensional analysis)
  • Data mining
  • Decision-support systems (DSSs)
  • Decision-support systems
    • Sensitivity analysis
    • What-If analysis
    • Goal-Seeking analysis
19
Q

12.3 What is online analytical processing (OLAP) in descriptive analytics?

A

Some BA applications include online analytical processing (OLAP), also referred to as multidimensional analysis capabilities.

OLAP involves “slicing and dicing” the data that are stored in a dimensional format, “drilling down” in the data to greater detail, and “rolling up” the data to greater summarization (less detail).

  • OLAP performs multidimensional data analysis
  • OLAP is a capability
  • OLAP is a certain class of database applications
20
Q

12.3 What is data mining in descriptive analytics? What are data mining’s two basic operations?

A

Data mining refers to the process of searching for valuable business information in a large database, data warehouse, or data mart. Data mining can perform two basic operations: (1) identifying previously unknown patterns and (2) predicting trends and behaviors. (The first operation is a descriptive analytics application, and the second is a predictive analytics application.)

In descriptive analytics, data mining can identify previously hidden patterns in an organization’s data.

21
Q

12.3 What is affinity analysis (a data mining application)?

A

Affinity analysis is a data mining application that discovers co-occurrence relationships among activities performed by specific individuals or groups. (Ex.: If you buy A (coffee), you might want to buy B (cream) too)

22
Q

12.3 What are decision-support systems (DSSs) in descriptive analytics?

A

Decision-support systems (DSSs) combine models and data to analyze semistructured problems and some unstructured problems that involve extensive user involvement.

Models are simplified representations, or abstractions, of reality. Decision-support systems enable business managers and analysts to access data interactively, to manipulate these data, and to conduct appropriate analyses.

They have the related capabilities of sensitivity analysis, what–if analysis, and goal-seeking analysis.

23
Q

12.3 What is sensitivity analysis in descriptive analytics?

A

Sensitivity analysis examines how sensitive an output is to any change in an input while keeping other inputs constant.

24
Q

12.3 What is what-if analysis in descriptive analytics?

A

A model builder must make predictions and assumptions on the assessment of uncertain futures. The results depend on the accuracy of these assumptions.

What-if analysis attempts to predict the impact of changes in the assumptions—that is, the input data—on the proposed solution.

25
Q

12.3 What is goal-seeking analysis in descriptive analytics?

A

Goal-seeking analysis represents a “backward” solution approach. Goal seeking attempts to calculate the value of the inputs necessary to achieve a desired level of output.

26
Q

12.4 What is predictive analytics?

A

Predictive analytics examines recent and historical data to detect patterns and predict future outcomes and trends. Predictive analytics provides estimates about the likelihood of a future outcome.

The purpose of predictive analytics is not to tell decision makers what will happen in the future. Predictive analytics can only forecast what might happen in the future, based on probabilities.

27
Q

12.4 What are some BA tools in predictive analytics?

A

The tools include data mining, and statistical procedures include linear regression, multiple regression, and logistic regression.

→ Data Mining

Recall that data mining can perform two basic operations: (1) identifying previously unknown patterns and (2) predicting trends and behaviors. The first operation is a descriptive analytics application, and the second is a predictive analytics application.

In predictive analytics, data mining can predict trends and behaviors.

28
Q

12.5 What is prescriptive analytics?

A

Prescriptive analytics goes beyond descriptive and predictive models by recommending one or more courses of action and by identifying the likely outcome of each decision.

Predictive analytics does not predict one possible future; rather, it suggests multiple future outcomes based on the decision maker’s actions.

Basically, prescriptive analytics requires predictive analytics with two additional components: actionable data and a feedback system that tracks the outcome produced by the action taken.

29
Q

12.5 What are the BA tools in prescriptive analytics? Hint: OSD

A

Statistical procedures include:
• optimization
• simulation
• decision trees