Understanding Systems and Decision Making in Organizations

1. Compiled by : S. Agarwal St. Xavier’s College, Kolkata. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

2. What is a SYSTEM ? A system is defined as a set of concepts or parts that must work together to perform a particular function. An organization is a system or a collection of systems. Every job in an organization is used by a system to produce a product or service. The product or service is the means by which a organization supports itself. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

3. There are four inputs necessary in every system to produce a product or service: Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

4. Functional Divisions of an Organization and IS : • Finance • Marketing & sales • Human resources • Operation (manufacturing or services) • Information systems (IS) Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

5. Information System : A system, whether automated or manual, that comprises people, machines, and/or methods organized to collect, process, transmit, and disseminate data that represent user information. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

6. At the center of organizational units lies the information system. Each unit relies on the information system in the generation of information. People in different functional areas of the organization will need different types of information. Often it is not even appropriate for people in one area to have information given to workers in another area. For example, most companies do not allow people outside of the human resources and payroll departments to have information about various employees' salaries. Therefore, one of the functions of a CIS, besides making information available to employees who need it, is to keep information away from employees who should not have it. Sometimes this second function is harder to manage than the first. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

7. Simon’s Decision-Making Model • Renowned mathematician, Herbert Simon, born in 1916, is responsible for many of the algorithms used in today's computer models. Dr. Simon spent his career developing mathematical formulas to mimic human thinking. His work has added much to the study of artificial intelligence. Herbert Simondescribes the decision-making process as having three phases. • Intelligence : In this phase we collect facts (the data). • Design : In this phase, we design the methods for studying the data, such as models, decisions trees – tools that let us analyze the various alternatives • 3.  Choice : When we have reduced the alternatives down to a manageable number, we make our decision Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

8. Decisions are easy to make when we can clearly see that one option is better than the others. Unfortunately, most decisions we make are not this cut and dried. As the number possible options increases, the decision-making process becomes more difficult. When we are talking about decisions in terms of strategic issues, i.e., product decisions, marketing decisions, cost/benefit decisions, etc. the number of alternatives can be enormous. In the world of business, you will be faced with three general types of problems -- structured, unstructured and semi-structured. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

9. Structured or programmable - The solution has a known set of steps. The data and solution to all three phases of Simon’s decision-making model are known or can be determined. an example of a structured problem would be figuring out a payment amount, based upon a known principal, interest rate and time period. We know there is a mathematical model to solve this problem. Solving this type of problem using this model will always give us the same result. Structured problems are easy for us to resolve. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

10. Unstructured : The steps are not known. There may be too much or to little information to allow us to arrive at the best conclusion. The data and solution to all three phases of Simon’s decision-making model are unknown or not quantifiable. In an unstructured problem there is no known set of steps to follow. There may not be enough information about the situation, or there may be so much information that a model cannot be formulated to reach a decision. There is so much information to disseminate it would be impossible to pinpoint. Stock behavior, world economies etc. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

11. Semi-structured - We cannot say with absolute certainty the best decision, but we are able to narrow it down to the most likely decision. Usually one or two of the phases of Simon’s decision-making model are known and one or two are not known. Semi-structured problems are somewhere in between. We cannot say with absolute certainty that it will be sunny in Boone tomorrow, but based upon forecasts we can be relatively sure. In the case of certain diseases, it can be difficult to say with absolute certainty what a diagnoses should be, but based upon data and various alternatives, we can narrow it down to the most likely diagnoses. Managers are constantly faced with Semi-structured problems. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

12. Why Automate? • Basically, we create information systems to provide the following: • Reduce costs • Increase speed • Increase accuracy • Increase customer service • Improve decision making • If the systems can not provide some or all of the above, then we should not consider automation. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

13. Computer Based Information Systems Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

14. Computer-Based Information Systems (CBIS). Some people call CBISs management information system or management information services, but both meanings are very general and include all types of systems shown in the figure. CBIS refers to a class of software that provides managers with tools for organizing and evaluating their department. Within companies and large organizations, the department responsible for computer systems is sometimes called the MIS department. Other names for MIS include IS (Information Services) and IT (Information Technology). Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

15. Transaction (Data) Processing The objective of the transaction (data) processing (TP/DP) system is the collection and maintenance of data. This is where most of the data in an organization is collected and stored for use by members of the organization. It is interesting that most of the workers in the TP/DP system are lower level workers. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

16. The tasks that must be accomplished in the TP/DP system include: • Data (transaction) gathering : The first task is to gather the data or transactions. This task mostly deals with collecting new data as close to the source as possible. • Data manipulation : This task includes editing, correction, classifying, coding, sorting, calculating, summarizing, and maintenance of data. Data editing ensures the accuracy of the data. Data correction only require correcting of the data in error. • Data storage : This task stores the data for future use. • Reporting : Reports must be created for edits and operational control. Typical reports include transaction logs, input and error lists, and summaries. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

17. The TP/DP system has several characteristics. • A TP/DP system must perform all of the tasks listed above. If any task is not performed, they data and system will not be complete. • The processing of the tasks must adhere to standardized procedures. These procedures may be different for each organization, but they must be in place. • The TP/DP system handles detailed data. Sometimes this data is in the form of thousands or millions of transactions per day. • The TP/DP system has a primarily historical focus. • Data collected in the TP/DP system provides little problem-solving information for the TP/DP system. The data may be used by the other systems for problem solving, but not in the TP/DP system. • Data gathering activities occur throughout the organization, but primarily at the lowest level. For example, sales clerks record most retail transactions, tellers record most bank transactions, and meter readers collect most utility transactions. • The TP/DP system has an immediate/short range focus. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

18. Management Information System The management information system (MIS) provides useful and timely information to support management’s (mostly middle management) information needs and routine decision-making. The MIS is sometimes called the management reporting system (MRS). It is aimed at providing more summarized information relevant to specific information and decision-making needs of middle management. The MIS is more medium range in focus. The MIS uses mostly organizational data, but may include some environmental (data collected and maintained outside the organization) data. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

19. The MIS provides detailed, summary, and exception reports. Report triggers (events that cause a report to be produced) include periodic (also known as scheduled reports), exception, and on demand. A periodic trigger occurs when some time period is reached (such as the end of the month, or every Monday). An exception trigger causes a report to be produced when the exception is encountered (such as a missed payment, or a sale). Marketing, manufacturing, and financial systems are typical MISs. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

20. Expert Systems Expert systems are systems that emulate the thought process of an expert. There are many types of expert systems. However, before looking at expert systems, we need to visit the roots of expert systems – Artificial Intelligence. Artificial intelligence (AI) applications are where the computer appears to "reason" or display the ability to duplicate human reasoning. AI has not developed much, but has taken a back seat to DSS and Expert Systems. Expert systems is a subset of artificial intelligence. Expert systems function in the same manner as a human expert; that is they emulate the thought process of an expert. The objective of an expert system is to come to a conclusion; to make a decision. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

21. AI includes: Vision Systems : These systems simulate the function of the human eye. Natural Languages : Natural languages allow us to communicate with computers in "normal English." Voice input is a good example of the use of natural languages systems. Robotics : Robotics is the science of using robots to perform tasks. Robotics now includes robots with vision and sight. Expert Systems : the fourth area and the one used in business systems. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

22. The parts of an expert system include: • User Interface (Explanation Subsystem) – The user interface enables the user to use the expert system. Using the user interface, the user enters instructions and information and receives explanations and solutions. • Knowledge base – The knowledge base contains the facts and rules used by the expert system. The size and quality of the knowledge base determines complexity & performance • Inference Engine – This part of the expert system performs the reasoning by using the information provided and the knowledge base. • Forward reasoning – The rules are examined in a specific order. Backward reasoning – The rules are examined in any order. Backward reasoning is more complicated and usually more expensive to create. • Development Engine (Knowledge Acquisition Subsystem) – this is the software that creates the expert system.Currently, Lisp and Prolog are the two languages used. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

23. Characteristics of an expert system (ES) include: • The ES must demonstrate the expertise of the expert. • It represents knowledge symbolically. • It should be able to handle complex rules and problems. • It should be able to estimate the accuracy of the conclusions. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

24. Advantages of expert systems are numerous. • They allow for better (more accurate) solutions over a non-expert system. • They allow a company to maintain control over the knowledge. If an expert retires, dies, or leaves the company, the expert knowledge is retained through the expert system. • They sometimes allow for faster solutions. • Finally, they provide a consistency. The expert system will provide the same solution, given the same inputs, every time. An expert can “forget” a rule or apply the data provided in an inconsistent manner, thereby obtaining different “answers.” Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

25. Disadvantages of expert systems : First, expert systems are extremely costly, some costing many millions of dollars. Second, it is extremely difficult to emulate an expert's thinking process. Many times an expert will follow the logic pattern instinctively. If the expert cannot articulate the thought process, the efforts can failure. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

26. Other terms and concepts relating to expert systems include: Expert System Shells - A ready-made inference engine tailored to a specific problem domain. Many companies buy a expert shell and add additional facts and rules to the knowledge base. Knowledge Engineer – An IS person that works with the expert to isolate and define rules. Knowledge engineers are IS persons that specialize in programming the thought process of experts. Neural Networks – Systems that attempt to emulate the biological structure of the brain. Fuzzy logic/data – The science ofinexact/ambiguous reasoning. Many expert systems use types of fuzzy logic to define the facts and rules. Virtual Reality (cyberspace) – Systems thatuse multi-sensory human/computer interfaces. Virtual reality (VR) works in 3-D space. Virtual reality was covered earlier in Chapter 5 of the text. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

27. The following table shows some well-known expert systems. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

28. Decision Support Systems • A decision support system (DSS) is a system for use by a manager or a group of managers that provides decision-making information to help solve semi-structured problems. • Characteristics of a DSS include: • It may use multiple data sources • It may include user databases. These would be databases created and maintained by the user and not part of the corporate data. • It is usually model-oriented. • It generally supports tactical-level decision making • It provides information to HELP the decision maker make a specific decision. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

29. It is important to emphasize that decision support systems provide help in decision-making. They are usually very focused, that is, they are aimed at the decision to be made. They can be fairly expensive depending on scope. Because they are usually very costly, they are used for recurring decisions. The information provided/used in a decision support system depends on the decision. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

30. Decision support systems provide the organization with many benefits. • These include: • A DSS can evaluate more alternatives. • It allows the user to better understand the problem. • It can analyze new scenarios. • It usually saves time and costs • It usually allows for better decisions. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

31. The risks associated with decision support systems include: Quality assurance (testing, backup, documentation) - Has a valid, quality decision support system been created? Erroneous outcomes - Does the system provide valid outcomes or results? Without a good quality assurance program, the system may not be accurate. Unknown alternatives - A DSS evaluates the alternatives that are programmed. If the user is not aware of alternatives, they will not evaluate them. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

32. Companies use DSSs to perform something called Sensitivity Analysis, or “What If” analysis. Sensitivity Analysis (What if)-- The sensitivity of an outcome is high if the outcome is affected significantly by a slight change in some parameter. The user enters parameters at varying degrees to see the various outcomes. How much will sales of Coke Classic increase if advertising dollars in TV media are increased by 10%, or 5%, or 3%. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

33. How does a company decide if it needs a DSS? • Basically, the following questions should be answered: • Do we need a DSS to aide in analysis? • Are the data in computerized databases? • How often do we need to solve these problems? • Who will use the system? • Information systems are tremendous investments for companies, both in terms of dollars and in terms of change for the organization. • So, before investing in a DSS, the questions asked above should be considered. • A Decision Support System simply gives managers more information to aid in the decision making process. The manager, or human component, must make the ultimate decision based upon the best information possible. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

34. Executive Information Systems Executive Information Systems (EISs) support executives (VP & above) in their decision roles. They rely heavily on the ability to retrieve data and present information for an executive. Another way to look at an EIS is that it is basically a DSS to provide summary and decision making information to an executive. Executive support is required for an EIS to be a success. Since they are costly, they are more often found in large companies. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

35. Characteristics of a EIS include: • Highly summarized – Most executives are looking for summary data upon which to make decisions. They very seldom want detailed data. Top-level executives making decisions for large organizations do not have time to wade through pages of detail, but must be able to see enormous amounts of information in such a way that is quickly meaningful and useful. • Drill down - Although an executive usually needs summarized data, sometimes more detailed data is needed. Drill down means that the transactions that created a total can be accessed, when needed. • Easy on-line access to internal and external data – Most EISs provide access to external data, as well as internal data. For example, an executive may require access to current stock prices. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

36. Characteristics of a EIS continued…… • Problem solving ability – Many EISs contain “what if” analysis capabilities. This allows the executive to analyze scenarios. • Easy to use and easy to learn - • Designed with executives CSFs in mind – The screens are usually customized to the executives needs. • On demand industry- and organization-wide indicators –The executive should be able to find, at a moment’s notice, the company’s financial strengths and weaknesses. • Use state-of-the-art graphics, data storage, communications, and data retrieval. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

37. Computer-Supported Co-operative Work • Computer-supported cooperative work (Groupware) is a class of software that helps groups of colleagues (workgroups), attached to a local-area network, organize their activities. • Typically, groupware supports the following operations: • Scheduling meetings and allocating resources • E-mail • Password protection for documents • Telephone utilities • Electronic newsletters • File distribution • Video conferencing • Application sharing. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

38. Groupware is sometimes called workgroup productivity software. Much research has been done by organizational behaviorists with regard to group or team oriented work processes. Researchers have found that individuals that work within a team environment are more productive, efficient and effective than when working alone. Thus, groupware facilitates this process. Groupware also supports the concept of anonymity. Individuals are often reluctant to share creative ideas in a group setting. Groupware allows the sharing of such ideas without necessarily revealing identities. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

39. System Analyst A systems analyst is an information system professional who helps plan, develop, and implement computer-based information systems. In short, they help organizations determine their information system needs. Systems analysts are problem-solving professionals who work with users & management to determine an organization’s information system needs. They define the requirements needed to modify an existing system, or to develop a new one. Their job involves communication, including listening skills. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

40. Systems Analysis and Design Systems analysisand design is the process of attempting to determine and fill the information systems needs of an organization by a formal process. This process is known as the Systems Development Life Cycle (SDLC). Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

41. The systems analysis and design process is a very costly, time-consuming, and difficult to manage process. • Many systems analysis and design projects fail. Some points to avoid problems and failures include: • User involvement is crucial. • A problem-solving approach works best. • Good project management skills are needed. • Documentation is required. • Use checkpoints to make sure the project is on track. • Design systems for growth and change. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

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43. The Systems Development Life Cycle is the entire life cycle of an information system - from inception to replacement. Although the number of phases differ from time to rime, normally it as a five phase process: • Identify problems and opportunities, • Analyze and documenting existing systems, • Design & develop the system, • Implement the system, and • Support and maintain the system. • At the end of each phase, a "deliverable" is produced, which is a tangible product that both ends that phase and is used as input for the next phase. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

44. SDLC models take a variety of approaches to development. Some of these life cycle models include: The Waterfall Model: A classic SDLC model, with a linear and sequential method that has goals for each development phase. The waterfall model simplifies task scheduling, because there are no iterative or overlapping steps. One drawback of the waterfall model is that it does not allow for much revision. The waterfall model builds correction pathways into the model that enable a return to a previous phase. It’s currently the most widely used way to implement the systems development life cycle. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

45. Rapid Application Development (RAD): This model is based on the concept that better products can be developed more quickly by using workshops or focus groups to gather system requirements. Joint application development (JAD): This model involves the client or end user in the design and development of an application, through a series of collaborative workshops called JAD sessions. Prototyping Model: In this model, a prototype (an early approximation of a final system or product) is built, tested, and then reworked as necessary until an acceptable prototype is finally achieved from which the complete system or product can now be developed. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

46. Synchronize-and-Stabilize: This model involves teams working in parallel on individual application modules, frequently synchronizing their code with that of other teams and stabilizing code frequently throughout the development process. Spiral Model: This model of development combines the features of the prototyping model and the waterfall model. The spiral model is favored for large, expensive, and complicated projects Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

47. FACTORS THAT AFFECT THE SYSTEM DEVELOPMENT : • User Requests • Top Management Directives • Existing System • Information Technology Department • The Economy • Technology • Government • Software and Hardware Vendors • Competitors • Customer • Suppliers Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

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49. System Study • System study is the first stage of system development life cycle. This gives a clear picture of what actually the physical system is? • In practice, the system study is done in two phases. • In the first phase, the preliminary survey of the system is done which helps in identifying the scope of the system. • The second phase of the system study is more detailed and in-depth study in which the identification of user’s requirement and the limitations and problems of the present system are studied. • After completing the system study, a system proposal is prepared by the System Analyst and placed before the user. The proposed system contains the findings of the present system and recommendations to overcome the limitations and problems of the present system in the light of the user’s requirements. Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.

50. Steps in System Study : • Understand the problems • Project Scope and constraints • Fact-Finding • Determine Feasibility • Estimate time and cost to continue development • Present Results and recommendations to Management Compiled by : S. Agarwal, St. Xavier’s College, Kolkata.