E-Business and Decision Making [2] Quiz

Answer: A model

We need models to aid us in making decisions. Models can calculate risks, understand uncertainty, change variables, and manipulate time.

Answer: Artificial Intelligence

Artificial intelligence systems can learn or understand from experiences, make sense of ambiguous or contradictory information, and even use reasoning to solve problems and make decisions effectively.

Answer: A business process

Business processes transform a set of inputs into a set of outputs (goods or services) for another person or process by using people and tools. Without processes, organizations would not be able to complete activities.

Answer: Decision Support System

In a Decision Support System(DSS), data is first queried and collected from the knowledge database. Results from the query are then checked and analyzed against decision models. Once checked against the decision models, the results are then generated for review to find a "best" solution for the situation.

Answer: What-if analysis

A what-if analysis determines the impact of change on an assumption or an input. For example, if the economic condition improves, how will it affect our sales?

Answer: Goal-seeking analysis

In goal-seeking analysis, you set a target value (a goal) for a variable and then repeatedly change other variables until the target value is achieved.

Answer: Executive information system

An Executive Information System (EIS) differs from a DSS because an EIS typically contains data from external sources as well as data from internal sources.
Most EISs offering the following capabilities:
Consolidation - involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information.
Drill-down - enables users to get details, and details of details, of information.
Slice-and-dice - looks at information from different perspectives.

Answer: Digital dashboard

Digital dashboards commonly use indicators to help executives quickly identify the status of key information or critical success factors. Whether basic of comprehensive, they deliver results quickly.

Answer: Intelligent Agent

Intelligent agents use their knowledge base to make decisions and accomplish tasks in a way that fulfills the intentions of the user.

Answer: Expert Systems

Expert systems are computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems. They reflect expertise from many humans and can therefore perform better analysis than any single skilled person.

Answer: Genetic Algorithm

A genetic algorithm is essentially an optimizing system: it finds the combination of inputs that gives the best outputs. They are best suited to decision-making environments in which thousands, or perhaps millions, of solutions are possible.

Answer: Business process modeling

Business process modeling (or mapping) is the activity of creating a detailed flow chart or process map of a work process showing its inputs, tasks, and activities, in a structured sequence. A business process model is a graphic description of a process, showing the sequence of process tasks, which is developed for a specific purpose and from a selected viewpoint.

Answer: As-Is process model

Analyzing As-Is business process models leads to success in business process reengineering since these diagrams are very powerful in visualizing the activities, processes, and the data flow of an organization.

Answer: Finance

Neural networks are most useful for decisions that involve patterns or image recognition. Typically used in the finance industry to discover credit card fraud by analyzing individual spending behavior. The finance industry uses neural networks to review loan applications and create patterns or profiles of applications that fall into two categories: approved or denied.

Answer: Business process improvement

Here are the steps to demonstrate how business process improvement basically works:
1. Organizations begin by documenting what they currently do.
2. Then, they establish a way to measure the performance.
3. They identify improvement opportunities based on the collected information.
4. Finally, implement process improvements and measure the performance of the new improved process.
5. The loop repeats over and over again as it is continuously improved.