Chapter 2
Describe artificial intelligence and identify its five main types.
Artificial Intelligence or AI is used to facilitate unstructured strategic decision making. AI replicates the way humans behave and think in an effort to create a system that mocks the intelligence of humans. There are five main types of AI. The first of these types is expert systems. Expert systems imitate the reasoning behind the decision making of experts through computerized advisory programs. These systems are generally used when an organization is unable to afford, retain, or find an expert. Expert systems can aid in serious tasks such as the diagnosis of a medical condition. The Second type of AI is neural networks. Neural networks try to simulate the way the human brain works. They are able to analyze b\big quantities of data in order to find and establish characteristics and patterns when the logic and/or rules behind a situation are unknown. Credit cards use Neural networks in order to spot fraud. The third type of AI systems are Genetic Algorithms. Genetic Algorithms play off the concept of survival of the fittest in an effort to continually create better solutions to a problem. It finds the inputs that create the best outputs. Some businesses use genetic algorithms to decide what combination of firms it would be most profitable for them to invest in. Intelligent agents are another type of artificial intelligence. Intelligent Agents solve specific tasks that are requested by a given user. An example of this is a shopping bot. The last type of AI is virtual reality. Virtual reality can create a simulation of both an actual and imaginary environment/world. Example of virtual realities include Google Glass, and Virtual Workplace.
Differentiate among automation, streamlining, and reengineering.
Automation, streamlining, and reengineering all are used to increase the efficiency of businesses. Automation increases efficiencies by computerizing tasks that originally had to be done manually. Streamlining increases business processes efficiencies by getting rid of unnecessary tasks, and simplifying others. Lastly Business processes reengineering focuses on analyzing and then redesigning the workflow inside and between organizations in an effort to increase efficiency
Explain the value of business process modeling, and compare As-Is and To-Be models.
Business modeling organizes an organization through the creation of flowcharts that shows the inputs, tasks, and activities within a given work process. These models are structured sequences created for a certain task from a specific point of view. As-Is process models show the state that a company is currently in, whereas, To-Be models show the result of improving and changing the original As-Is model.
Explain the value of business processes for a company, and differentiate between customer-facing and business-facing process.
Improving business processes makes companies more efficient and effective. Therefore improving the overall value chain of an organization. In addition, when a manager understands the processes within a given business they are then able to imagine how the company works as a whole. Customer-facing processes (front office processes) are goods or services received by a customer outside of the company. Examples include, billing customers, filling orders, sending out marketing information, and speaking directly with customers. Business-facing processes (back office processes) include daily planning, allocating resources, and discussing performance. Back office processes basically include anything that is not seen to an external individual.
Define critical success factors (CSFs) and key performance indicators (KPIs), and explain how managers use them to measure the success of MIS projects.
Key performance indicators (KPIs) and critical success factors (CSFs) are the two main metrics that evaluate results in order to see if a project is successfully measuring up to its goals and purpose. CSFs are the essential initiatives companies perform in order to reach their goals, execute their objectives, and apply their strategies. CSFs help to create a competitive advantage, lessen product prices, inflate the satisfaction of customers, and hire and keep the most certified business professionals for each job. The quantifiable metrics are KPIs. KPIs gauge advancements, toward the necessary success factors. Key performance indicators quantify the turnover rate in employment, the amount of calls that are answered by a receptionist within the minute, the number of products that are sent back, and the amount that the average buyer spends. These two metrics measure the performance of MIS (management information system) through looking at things such as the speed of transactions, and the overall availability on a given system.
Explain the importance of decision making for managers at each of the three primary organization levels along with the associated decision characteristics.
Operational level support systems include structured decisions, which occur when already occurring processes contain possible solutions. Structured decisions affect businesses in the short term because they happen often generally in a reoccurring pattern. At the operational level employees develop, and sustain activities that are day-to-day operations. Evaluation by employees of a businesses ability to identify and adapt to changes occurs at the managerial support system level. The managerial level contains semi-structured decisions. Lastly at the strategic level managers create business strategies, and develop goals as part of the entire company's strategic plan. At the strategic level all decisions are unstructured.
Classify the different operational support systems, managerial support systems, and strategic support systems, and explain how managers can use these systems to make decisions and gain competitive advantages.
Operational support systems utilize transactional information that includes all information within one process of business or unit of work. Its overall purpose is to assist in daily operational decisions. Examples of transactional information include, the buying of stock by customers, and withdrawing money through an ATM. Online Transaction Processing or OLTP happens when technology is utilized to take information in order to process the information by specific business rules, keep the information for later usage, and keep information up to date. A transaction processing system or TPS is the simple business system that serves analysts at the operational level in order to make decisions with structure. An example of a TPS is a payroll system. Managerial support systems contain analytical information. This analytical information is used to aid in the making of semi-structured decisions through the encompassment of organizational information. Examples include future growth projections, and trends. Online analytical processing or OLAP is the altering of data in order to support strategic resolutions through the creation of business intelligence. Decision support systems or DSSSs reflect information through the usage of OLAP, therefore assisting in the evaluation of picking the best course of action. DSSSs allow top-level managers to look at and change big quantities of detailed information from many sources, both internal and external. It contains what-if, sensitivity, goal seeking, and optimization analyses. Therefore DSSSs aids in helping companies gain a competitive advantage. Strategic support systems require business intelligence and knowledge to work through the complexity linked with business strategies. An Executive information system (EIS) is a specialized part of DSS that assists top-level managers and executives, and rare unstructured decisions that require a high level of knowledge and evaluation. The granularity of a model depicts the amount of detail in the decision. The higher the granularity is the greater level of detail a set of data contains. An EIS uses data from external sources, whereas, DSSSs usually rely solely on internal information. Visualization is also utilized in strategic support systems in order to create displays of patterns and relationships found in large quantities of data.
