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  1. 1. MAJOR CHALLENGES OF INFORMATION SYSTEMSInformation System has brought revolution in the business world for getting its maximumbenefits. So, building, operating and maintaining information system is a challenging activitynow a days. 1. Globalization Challenge :- It deals with the identification of business and system requirements to survive in globalized economy. 2. Information Architecture Challenge :- It deals with what should be the architectural design of the information system to achieve the overall goal of the organization. 3. Strategic Business Challenge :- It deals with how to derive maximum benefits of information technology to make an organization competitive and effective. 4. Responsibility & Control Challenge :- It deals with whether information systems are ethical and socially responsible and can the system be controlled or not controlled by the people? 5. Information System Investment Challenge :- It deals with what is the business value of the information system? Generally it is very difficult to find out the value of information systems to the organization because the benefits from information system are intangible. 6. Product & Service Challenge :- Traditional products that are tangible such as automobile can be difficult to be deliver in the global market. However, electronic products like software, music, books and electronic services can be delivered to customers electronically over the networks, through Internet or other electronic means. 7. State, Regional & National Laws :- Every state, region and country has a set of laws that must be obeyed by organizations operating in the country. These laws deals with issues like trade secrets, patents, copyrights and privacy. Keeping track of all these laws and incorporating them into the procedures and computer systems of multi-national and transnational organizations is a difficult and time consuming challenge for managers, which require expert legal advice.
  2. 2. MANAGEMENT INFORMATION SYSTEM (MIS)MIS deals with information that is systematically and routinely collected in accordance with awell-defined set of rules. The information provided by an MIS helps the managers to makeplanning and control decisions. Managers often use historical data on an organization’s activitiesfrom database to make planning and control decisions. This data base is an essential componentof an MIS.According to Cannith, “ MIS is an approach that visualize the business organisation as a singleentity composed of various inter-related and interdependent sub-systems looking together toprovide timely and accurate information for management decision making, which leads to theoptimization of overall enterprise goals”.According to David J. Olson, “A Management Information System is an integrated usermachine system for providing information to support the operations, management, analysis anddecision-making functions in an organisation”.Thus, effective management information systems must be developed to provide modernmanagers with the specific marketing, financial, production and personnel information productsthey required to support their decision making responsibilities.OBJECTIVES OF MIS a) To store and manage data efficiently from all the functional areas of the business. b) To provide information quickly as and when required & process the collected data and derive information out of them. c) To provide information for planning, organizing and controlling purposes. d) To smooth up the flow of data through various levels of organization. e) To speed up the execution of the results with the reliable data available.
  3. 3. CHARACTERISTICS OF MISMIS is a comprehensive coordinated set of Information Sub-systems, which are rationallyintegrated and transform data into information. The following are the characteristics of MIS : • It is a sub-system concept. The system is viewed as a single entity but it is broken down into sub-systems that can be implemented one at a time. • It provides a comprehensive view look of the inter-related sub-systems that operate with an organisations. • It is a rationally integrative system. All the sub-systems are integrated so that the activities of each are inter-related with those of others. • It provides relevant information to management. • It enhances productivity, provides higher levels of service to organizations & individuals. • It enhances manager’s ability to deal with unanticipated problems, facilitates the organization’s normal management processes. • It is management oriented as well as management directed.ADVANTAGES OF MISMIS is a process of collection and storing of the data useful for the organization. The followingpoints can summarize the importance of MIS :- 1. It facilitates Planning : MIS improves the quality of plans by providing relevant information for sound decision – making. Due to increase in the size and complexity of organizations, managers take help of information systems to know about the status of operations. 2. In minimizes Information overload : MIS change the larger amount of data in to summarized form and there by avoids the confusion which may arise when managers are flooded with detailed facts.
  4. 4. 3. MIS encourages De-centralization : Decentralization of authority is possibly when there is a system for monitoring operations at lower levels. MIS is successfully used for measuring performance and making necessary change in the organizational plans and procedures. 4. It brings Co-ordination : MIS facilities integration of specialized activities by keeping each department aware of the problem and requirements of other departments. It connects all decision centers in the organization. 5. It makes control easier : MIS serves as a link between managerial planning and control. It improves the ability of management to evaluate and improve performance. The used computers has increased the data processing and storage capabilities and reduced the cost. 6. MIS assembles, process , stores , Retrieves , evaluates and Disseminates the information. 7. It helps in minimizing risk in decision making. 8. It helps the executives to avail the information regarding the functional areas quickly. 9. It processes the data and derives information out of them & helps in preparing corporate report.DISADVANTAGES OF MISMIS enhances the overall throughput of the organization. But it has certain limitations :  The qualities of the outputs of MIS are basically governed by the qualities of inputs and processes.  It may not have requisite flexibility to quickly update itself with the changing needs of time, especially in a fast changing and complex environment.  MIS effectiveness decreases due to frequent changes in top management, organizational structure and operational team.  It can not replace managerial judgment in making decisions in different functional areas.
  5. 5. DECISION SUPPORT SYSTEMS (DSS)DSS is identified as a system intended to support managerial decision makers in semi-structured decisionsituations. A properly designed DSS is an interactive software-based system intended to help decisionmakers compile useful information from a combination of raw data, documents, personal knowledge, orbusiness models to identify and solve problems and make decisions. They assist management decisionmaking by combining data, sophisticated analytical models and tools, and user-friendly software into thatsupport semi-structured or unstructured decision making. For Example, advertising managers may use anelectronic spreadsheet program to do what-if analysis as they test the impact of alternative advertisingbudgets on the forecasted sales of new products.According to Scott-Norton (1971), “DSS is an interacting computer-based system that helps the decisionmaker in the use of data and models in the solution of unstructured problems”According to Sprague & Carlson (1982), “Decision Support System (DSS) are interactive, computer-based information systems that use decision models and specialized databases to assist the decisionmaking process of managerial end users.”Therefore, DSS are designed to be ad-hoc, quick-response systems that are initiated and controlled bybusiness decision makers. A DSS provide managers with analytical modeling, simulation, data retrievaland information presentation capabilities.FEATURES OF DSSDecision Support Systems (DSS) have many characteristics that allow them to be effective managementsupport tools. Not all DSSs work the sane. Some of characteristics of DSS are : 1) Provide Rapid Access to Information : Some DSSs provide fast and continuous access to information. Example – the gauges on the dashboard of a car are used to see how the vehicle is running. 2) Handles Large Amount of Data from Different Sources : DSS allow decision makers to access data that resides in different databases on different computer systems or networks. Other sources of data can be accessed via the Internet or corporate Intranet.
  6. 6. 3) Provide Report and Presentation Flexibility : Managers can get the information they want, presented in a format that suits their needs. 4) Offer both Textual and Graphical Orientation : DSSs can produce text, tables, line drawings, pie charts, trend lines, etc. By using their preferred orientation, managers can use a DSS to get a better understanding of a situation and to convey this understanding to others. 5) Support Drill-Down Analysis : A manager can get more details by drilling down through data. Example – a manager can get more detailed information for a project by viewing the overall project cost of drilling down and seeing the cost for each phase, activity and task. 6) Perform Complex Analysis & Comparisons : Marketing research surveys can be analyzed in a variety of ways using programs that are part of a DSS.CAPABILITIES OF DSS 1. DSS provide support decision makers mainly for semi structured and unstructured situations, by bringing together human judgment and computer. 2. DSS provide support to several interdependent and sequential decisions to individuals as well as to groups. 3. It support all phases of the decision-making process. 4. DSS attempt to improve the effectiveness of decision making. 5. A DSS usually utilizes models for analyzing decision-making situations. 6. Improve the effectiveness rather than the efficiency 7. Combine the use of models or analytical techniques with data access functions 8. DSS facilitates flexibility, adoptability and a quick response.SIMON’S MODEL OF DECISION MAKINGThe word ‘Decision’ is derived from Latin word which means ‘to come to a conclusion’. Decision-making is a process of selecting one optimum alternative from several alternatives. So, decision is an endor final product of the decision-making process. Herbert A. Simon has given a model to describe thedecision-making process. The model consists of 3 major phases :
  7. 7. I. Intelligence – In this phase, scanning of the environment and identification of the problem or opportunity is done. Scanning of the environment may be continuous or intermittent. This phase also involves problem finding and problem formulation. ‘Problem’ is defined as the difference between something expected and reality. In this phase, once the problem is identified, then the problem is simplified by determining its boundaries, breaking it down into smaller manageable sub-problems or focusing on the controllable elements. II. Design – In this phase, the decision-maker makes a checklist of alternative courses of action to solve the problem. These alternatives can be developed by various methods such as brainstorming, interviews, etc. III. Choice – At this stage, the decision-maker selects one alternative from the various alternatives developed in design phase. This alternative after thorough analysis is further implemented.TYPES OF DSSDecision Support Systems (DSS) are interactive computer-based systems that help decision makers usecommunications technologies, data, documents, knowledge and/or models to complete decision processtasks. A DSS may present information graphically and may include an expert system or artificialintelligence (AI).Data-Driven DSSIt is also known as data-oriented DSS. It emphasizes access to internal company data through thecompany’s TPS and MIS systems and retrieve from it useful information which managers can use asinformation for further decisions. It is used to query a database or data warehouse to seek specificanswers for specific purposes.Communication-driven DSSIt is a hybrid DSS that focuses both the use of communication and decision models. They use networkand communications technologies to facilitate decision-relevant collaboration and communication. Its
  8. 8. purpose are to help conduct a meeting, or for users to collaborate. It supports more than one personworking on a shared task.Document-driven DSSThese systems have also been called as text-oriented DSS. Document-driven DSSs are more common,targeted at a broad base of user groups. The purpose of such a DSS is to search web pages and finddocuments on a specific set of keywords or search terms. It manages, retrieves, and manipulatesunstructured information in a variety of electronic formats. It integrates a variety of storage andprocessing technologies to provide complete document retrieval and analysis.Knowledge-driven DSSKnowledge-driven DSS can suggest or recommend actions to managers. These DSS are person-computersystems that provide specialized problem-solving expertise stored as facts, rules, procedures, or in similarstructures. The "expertise" consists of knowledge about a particular domain and understanding ofproblems within that domain. These systems are also called suggestion DSS.It is essentially used to provide management advice or to choose products/services. The typicaldeployment technology used to set up such systems could be client/server systems, the web, or softwarerunning on stand-alone PCs.Model-driven DSSModel-driven DSSs are complex systems that help analyze decisions or choose between different options.They emphasizes access to and manipulation of a statistical, financial, optimization, or simulation model.Model-driven DSS use limited data and parameters provided by users to assist decision makers inanalyzing a situation; they are not necessarily data-intensive.Web-based DSSWeb-based decision support system is a computerized system that delivers decision support informationor decision support tools to a manager or business analyst using a "thin-client" Web browser likeNetscape Navigator or Internet Explorer. Ex - Homes.com provides a nation-wide listing of homes forsale, apartments for sale and mortgages available.
  9. 9. In a nutshell, data-driven DSS will use faster, real-time access to larger, better integrated databases.Model-driven DSS will be more complex, yet understandable, and systems built using simulations andtheir accompanying visual displays will be increasingly realistic. Communications-driven DSS willprovide more real-time video communications support. Document-driven DSS will access largerrepositories of unstructured data and the systems will present appropriate documents in more useableformats. Finally, knowledge-driven DSS will likely be more sophisticated and more comprehensive. Theadvice from knowledge-driven DSS will be better and the applications will cover broader domains.COMPONENTS OF DSSDSS include a database of data used for query and analysis, a software system with models, a userinterface and other analytical tools.  DSS Database : It is a huge data warehouse that contains a subset of corporate data that has been combined with external data. It is a collection of current or historical data from a number of applications or groups. The data in DSS databases are generally extracts or copies of production databases.
  10. 10.  DSS Software system : It contains the software tools that are used for data analysis. It contain various OLAP tools, data mining tools, a collection of mathematical and analytical models. A model is an abstract representation that depicts the relationship of a phenomenon. The most common models used in DSS are Statistical model, Optimization model, Forecasting model, Sensitivity analysis model. (a) Statistical Model – This model has library which contain statistical functions like mean, median, deviations and scatter plots. This model has the ability to project future outcomes by analyzing a series of data. Example – Finding impact of differences in age, income and other miscellaneous factors on product sales. (b) Optimization Model – It uses linear programming, transportation algorithms to determine optimal resources allocation to maximize or minimize specified variables such as cost and time. Example – To determine the proper mix of products within a given market to maximize profits. (c) Forecasting Model – They are generally used by organizations to predict the actions of their competitors. These models use historical data to project future conditions and the sales that might result from these conditions. (d) Sensitivity Model – It uses ‘What-If” analysis to determine the impact of changes in one or more factors on outcomes. Example – “What happens if” we raise the price by 5% or increase the advertising budget by $100,000?  User Interface : DSS user interface permits easy interaction between users of the system and the DSS software tools. Today, DSS are built with Web-based interfaces to take advantage of the Web’s ease of use, interactivity and capabilities of customization.  Users : They are managers who have to take short-term decisions for the organizational run.BENEFITS/ADVANTAGES OF DSS 1. DSS improves managerial effectiveness and provides extensive range of support to management. 2. Expedites problem solving (speed up the progress of problems solving in an organization) 3. Encourages exploration and discovery on the part of the decision maker. 4. Reveals new approaches to thinking about the problem space.
  11. 11. 5. Provides a detailed quantitative analysis in very short time. 6. Facilitates quicker analysis of variances to anticipate outcomes with the help of efficient and ad- hoc query facilities. 7. Facilitates the faster analysis of unstructured decision-making which improves the response in unexpected decision-making situation.DISADVANTAGES OF DSS 1. It cannot replace human decision-making such as creativity, intuition & imagination. 2. Languages and command interface are not sophisticated enough to allow for natural language processing. 3. Their general design prevents their generalize use to multiple decision-making process.GENERAL USES OF DSS IN ORGANIZATION 1. Ad hoc data retrieval With the use of computer and application software, DSSs help the decision-maker to reduce the workload of handling a large amount of data, while improving efficiency and accuracy. The basic functionality of DSSs is to provide the decision-maker with the ability to retrieve information selectively on an ad hoc basis. DSSs have the capability to retrieve data selectively, as well as to aggregate and summarize data. 2. Information presentation DSS often present computational results in a variety of formats. The formats include traditional ones like tables and graphics as well as new patterns like animation, audio, and video. By means of the visual aids, users can recognize the relationship of a collection of data and understand some complicated results more easily. 3. Multiple decision aids
  12. 12. DSSs provide interactive decision aids that combine data retrieval, stylized displays, and model- based processing to satisfy some particular decision needs. For example, a decision aid can help a decision-maker to choose from many alternative solutions that might come from different databases, which are to be drawn out under different control conditions.ANALYTICAL MODELLING ACTIVITIES OF DSSUsing a DSS involve 4 basic types of analytical modeling activities :- 1. What-If Analysis - An end user makes changes to variables, or relationships among variables, and observes the resulting changes in the values of other variable. Example : What if we cut advertising by 20% - What would happen to sales? What if we change a revenue amount or a tax rate formula –What would happen to Net profit after Taxes? 2. Sensitivity Analysis – It is special type of ‘What If’ analysis involving repeated changes to only one variable at a time. In this, value of only one variable is changed repeatedly, and the resulting changes on other variables are observed. Example : Cut advertising by Rs. 100 repeatedly, and see its relationship to sales. 3. Goal-Seeking Analysis - It reverses the direction of the analysis done in ‘What-If’ and ‘Sensitivity’ analysis. In this, target value (goal) is set up for a variable and then repeatedly change other variables until the target value is achieved. Example : Let the target value is Rs. 2 crore for net profit after taxes for a small business. Now, one can repeatedly change the value of revenue or expenses in a spreadsheet model until the goal of Rs. 2 crores is achieved. So, this form of analytical modeling helps to answer the question, “How can we achieve Rs. 2 crore in net profit after tax?” Thus, goal-seeking analysis is another important method of decision-support. 4. Optimization Analysis – It is a more complex extension of ‘Goal-Seeking’ analysis. In this, rather than setting target value for a variable, the goal is to find the optimum value for one or more target variables, given certain constraints. Then one or more other variables are changed repeatedly, subject to the specific constraints, until the best values for the target values are achieved. Example : What is the best amount of advertising to have, given our budget and choice of media? What is the highest possible level of profit that could be achieved by varying the values for selected revenue source and expense categories. For optimization analysis, the commonly used software is the solver tool of MS-Excel.
  13. 13. DIFFERENCE BETWEEN MIS & DSSManagement Information Systems Decision Support SystemsProvide information about the performance of Provide information and decision supportthe organization techniques to analyze specific problems or opportunitiesInformation is in Prespecified & fixed format Information format is in Ad-hoc, flexible and adaptable formatInformation is produced by extraction and Information is produced by analytical modelingmanipulation of business data of business dataEmphasis is on data storage Emphasis is on data manipulationFocus is on structured tasks and routine Focus is on semi / unstructured tasks, whichdecisions require managerial judgmentEmphasis is on efficiency Emphasis is on effectivenessPresentation is in form of reports Presentation is in form of graphics