ISORG BIBLE The objective of this guide is to facilitate the study of my friend’s level of understanding of the subject matter and at the same time provide an insight of how I view the subject and my personal understanding of the subject, in relation to the style of the examination questions. *disclaimer* All content in this bible is either copied directly from study guide, Jack koh’s ISORG bible, internet knowledge. It is just a summary and all information are based on Jeffrey’s personal opinion/interpretation. Use is at your own risk. Overview of this ISORG BIBLE
I’ll start of the ISORG bible with what I deemed important terms that will be used in the course of this subject. I’ll first give definitions from the subject guide as this will definitely be accepted by the examiners. Next I’ll give further definitions I found from websites/ Jack Koh’s notes to provide further insight and better understanding. I’ll then give explanations and also examples if possible of the term used. Most of the example will probably be from Jack Koh’s study package or even his ISORG bible unless I actually have the time to source out more.
BUT beware, if I do add further examples that I found out online, those are examples that I myself believe is appropriate, they may or may not even be correct so use those at your own risk. After all the definitions and explanations, I’ll try and include a brief summary of Jack Koh’s bible showing paragraphs that I find useful. I’ll italics and ‘quote’ the paragraphs or phrases that I sourced from his bible. At the end, I have also suggested a few articles that I feel are MUST reads for better ideas of how to answer questions. Finally, I just hope this ISORG bible is actually of even any use to anyone.
Information systems Information systems are sets of interrelated components that collect or retrieve, process, store and distribute information to support decision-making, co-ordination, control, analysis and visualization. (UOL-SG) Information systems are implemented within an organization for the purpose of improving the effectiveness and efficiency of that organization. Capabilities of the information system and characteristics of the organization, its work systems, its people, and its development and implementation methodologies together determine the extent to which that purpose is achieved. (Wikipedia. rg) The study of information systems is normally premised on the assumption that information systems are socio-technical systems. Socio-technical aspects encompass both technical and social variables. There are three perspectives or lenses with which to look at the role played by systems and networks in organizations namely data model (technical), decision-making model (cognitive) and transaction-cost model (behavioural). Examples of information system includes * Date warehouses (Page 5) * Enterprise resource planning * Transaction processing system * Management information system * Decision support system Executive information system Information and communications technology Information and communications technology (ICT), just like it’s’ name, refers to the different technology used in information processing/transferring and also technologies that aid in communication. Examples of ICT includes internet, extranet, cloud computing, wireless communication, TCP/IP, GPS, online video conferences, ipad, iphone, servers, databases, hardware and software infrastructure. (Jeffrey) *I gave up on this chapter especially regarding the hardware and software and so is unable to come up with a detailed write out about this. *
Data Model The data model is a model that describes in an abstract way how data are represented and interrelated in an information system, a database management system or even a business organization. In particular, this model focuses on data flows which can actually help the analyst design a new system or even the entire organization. (UOL-SG) A data model is a design-model that provides a specific technical framework to guide the analysis and design of a new information system solution for a specific organizational problem. Data model views the organizational problem as a bundle of data and network of processes.
The data model centres on the organization’s data, data-flow paths, processes and files. Data model summarizes the business view of the data to be stored in the database and how they are accessed in the new computerised information system. (ISORG bible) ‘Data modelling is the process of defining what data is used in an information system or organization and how that data is organized. With Data model, the design of an information system is concerned mainly to optimize the data flow in the organization, and lead to new ways to produce, store, process and exchange data faster, more reliable and secure than previous practices. Information system Database management system (DBMS) A database management system (DBMS) is the interface between the application programs and the database. Whenever the application program calls for a single data file (e. g. employee gross pay), the DBMS finds the item in the database under the heading ‘payroll’ and presents it to the application program so as to relieve the end user from the burden of understanding where and how the data are stored.
Database management systems require that the organization acknowledges the strategic role of information by treating it as a corporate resource. Decision makers need concise, reliable information about current operations, trends and changes. Data, however are often fragmented in separate systems. Data warehouse addresses this problem by integrating key operational data from around the company in a form that is consistent, reliable and easily available for reporting. Example of SIM class attendance
A simple example lies in the marking of SIM class attendances where the new computerised system will remove the two clerks checking attendances at the entrance to the 80 SIM lecture theatres, classrooms and labs at the start of every lecture. Recording papers, subsequent collating processes, human involvements will be a thing of the past. The new computerised system will definitely be more accurate in the data capture, subsequent processing and collation of reporting information. Design and implementing of information system ‘Key reasons for using the data model is it’s technical bias, data and process centric.
Tabula rasa and raison d’etre, disregards norms and existing rules – this being so, the systems and analyst need not actually talk to the people to identify the specifications of the new system but actually need only to “talk” to the documents, examine and consuming the documents by himself. The out of data model is to provide a new computerised solution to manage the current processes and data in new ways. However, any computerization outcome could results in drastic workplace change in procedures, job responsibilities and workflow. ’ Advantages
Appropriate for organizational problems such as inventory recording and control system, invoicing system, enterprise resource planning system (ERP) because the data model approach merely take interest only on files, documents and business processes that are generated internally. Hence, the absence of factors (such as opportunism, uncertainty and bounded rationality) makes the data model approach the right design choice. Data model leads to fast development through the system. The data model provides for a fast product uptime, involves much lesser resources, particularly human factors (as compared to the other two design models).
It is easier to manage, plan and budget. Designing the implementing functional requirements and specifications are especially facilitated if a prior business process re0engineering exercise has just been completed and the data model is there to implement the computerized version. Beside lower cost, the data model is the less complex of the three design-models. It’s technically and mathematically driven model hence the cognitive and behavioural aspects are not important considerations unlike the situation of the other 2 models. Since the systems analyst, with the data model approach, has the mandate to look into any files or documents in the organization to design and develop the new information system and actually be able to do so without any assistance from the people working in the respective user departments. It would appear that uncooperative and reluctant people in the organization would not pose a real threat to the successful design or development of the new information system since the data model approach does not really require much human interactions during the development stages.
Disadvantages/Limitations As the Data model is centric on the technical aspects, this can become its limitation too. Sometimes, this can become costly during the implementation stage of the new information system. ‘The Data model – abstraction design approach often drastically change the old ways the firm works. Jobs are redesign, combine or sometimes, even removed. New rules and guidelines are set regardless of how well some of the old rules work. This often are met with high resistance during implementation (i. e. cutover phase) and end up being rejected by the end-users.
Indeed, Data model abstraction technique can lead to a large percentage of redesign failures and rejections. ’ Problems that bear cognitive and behavioural characteristics are likely to fail if using the data model approach. ‘One example lies in the inventory recording system of Rollei Camera factory. Prior to computerisation, the workflow in updating the inventory stock cards is very flexible. Store keeper mass update the stock cards two or three times a day. They will arrange all issues (i. e. inventory taken out of the store) in one stack and all there receipts (i. e. new inventory received) in another.
The store keeper then update the stock cards with one stack (issues) follow by the other file (receipts). The new balance is derived by adding the opening stock to the difference between the total issues and total receipts. This is alright in the manual approach. With the newly implemented computerised system, stock cards must be updated interactively as and when an issue or receipt takes place. During the analysis, the behaviours of the store keepers were disregarded. So when the new information system went full swing, the inventory was reporting negative and misrepresented stock balances.
Instead of adding values to the related processes in production planning and purchasing, the information system was causing nightmare and serious injury to the whole firm’s information structure. Decision-making Model The decision-making model is a specific way of analysing the organization whereby the analyst attempts to ascertain the way information systems can support individual and collective decision-making processes on the basis of their structural features. (UOL-SG) The decision-making model attempts to ascertain how information systems can be designed to support individual and collective decision-making.
The model examines how the organization can be conceptualized as a decision-making system that scans the environment with the purpose of evaluating alternative solutions to a specific problem and in attempting to derive the rational choice. (ISORG bible) The cognitive perspective has come up with two decision-making models: rational decision-making, which supports value-maximising decisions on the basis of a comprehensive analysis of all possible alternative actions, and bounded rationality, which acknowledges that human beings can only choose among a subset of all possible courses of action. Rational model of decision-making
This model of decision-making is based on the idea that individuals or organization engage in value-maximising decision-making processes. It’s based on that actor of decision-making is able to rank all net pay-off of the different alternative actions to the desired goal. This set of assumptions is normally labelled as ‘unbounded rationality’. Bounded rationality and satisficing Rather than optimising, which presumes searching for all the alternative courses of actions, the actor can satisfice; that is, choose a satisfying course of action which is based on a sub-set of all the alternative courses of action.
This behavioural model is based on the assumption that people have bounded rationality because they stick with tried-and-tested rules and procedures since they are not able to take into account all the possible courses of action. Information system Several models attempt to describe the decision-making processes of individuals and organizations. The most influential models are based on the idea that decisions can be split into programmed or structured decisions and non-programmed or unstructured ones. Programmed or structured decision Programmed or structured decisions are highly repetitive and routine decisions.
Examples include Transaction processing system (TPS) and Office automation system (OAS). Structured decisions belong to operations decision makers that face operational problems at recurring frequently. Non-programmed or unstructured decision Non-programmed or unstructured decisions are based on intuition, judgement and improvisation. Examples include Executive support system (ESS) and knowledge work system (KWS). Unstructured decisions belong to strategic decision makers such as top executives responsible for the strategic directions of the firm.
Semi-structured decision A special category of decisions is labelled semi-structured because it shares traits common to both structured and unstructured decisions. In such cases, only part of the problem has a clear-cut answer according to a well-accepted procedure. Examples include Management information system (MIS) and Decision support system (DSS). Semi-structured decisions belong to tactical decision makers such as mid-level managers responsible for controlling and monitoring the progress of execution of the firm’s plans.
Structured Decisions Structured Decisions Operations Decision Makers Operations Decision Makers Semi-structured Decisions Semi-structured Decisions Unstructured Decisions Unstructured Decisions Tactical Decision Makers Tactical Decision Makers Strategic Decision Makers Strategic Decision Makers Type of decision| Operational| Knowledge| Management| Strategic| Structured| TPS| | | | | | OAS| MIS| | Semi-structured| | | | | | | | DSS| | Unstructured| | KWS| | ESS|