CHAPTER 9 ENABLING THE ORGANIZATION ( DECISION MAKING )

CHAPTER 9

9.1 Define the systems organizations use to make decisions and gain competitive advantages.

                A Decision Support System creates a competitive advantage if three criteria are met. First,

once the DSS is implemented it must become a major or significant strength or capability

of the organization. Second, the DSS must be unique and proprietary to the organization.

Third, the advantage provided by the DSS must be sustainable for at least 3 years. Even

with rapid technology change a 3 year payback is realistic. Managers who are searching for

strategic investments in information technology need to keep these three criteria in mind. A

competitive advantage means an organization does something important much better than

its competitors.

9.2 Describe the three quantitative models typically used by decision support systems.

Sensitivity analysis is a special type of what-if analysis. The decision maker will change only one variable of the problem to view change on the remaining variables. For example, change in the expenses again and again or increase/decrease the tax rate.

The decision maker will set a target figure for the required variables and try to evaluate the remaining variables using a goal-seeking analysis, such as an amount figure is set for the profit variable and make changes in the other variables to achieve it.

The decision maker to achieve the maximum feasible value for the target variable uses optimization analysis. Optimization analysis is a special type of goal-seeking analysis. Goal- seeking analysis is made without considering any constraints where as optimization analysts is made with considering all constraints, such as budget, schedule and resources.

9.3 Describe the relationship between digital dashboards and executive information systems.

Executive Information Systems includes consolidation which involves the aggregation of information and features simple rollups to complex groupings of interrelated information. Drill-down that enables users to get details, and details of details, of information viewing monthly, weekly, daily, or even hourly information represents drill down capability. Slide-and-dice which is the ability to look at information from different perspectives. Digital dashboards integrate information from multiple components and tailor the information to individual preferences. Digital dashboards commonly use indicators to help executives quickly identify the status of the key information or critical success factors.

9.4 List and describe four types of artificial intelligence systems.

1. Intelligent System - Intelligent systems are a new wave of embedded and real-time systems that are highly connected, with massive processing power and performing complex applications. Their pervasiveness is reshaping the real world and how we interact with our digital life.

2. Expert System - a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, represented primarily as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of AI software.

3. Neural Networks - An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurones) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurones. This is true of ANNs as well.

4. Knowledge - Knowledge is the information about a domain that can be used to solve problems in that domain. To solve many problems requires much knowledge, and this knowledge must be represented in the computer. As part of designing a program to solve problems, we must define how the knowledge will be represented. A representation scheme is the form of the knowledge that is used in an agent. A representation of some piece of knowledge is the internal representation of the knowledge. A representation scheme specifies the form of the knowledge. A knowledge base is the representation of all of the knowledge that is stored by an agent.