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.
