MANAGEMENT INFORMATION SYSTEM FINANCIAL MANAGEMENT INFORMATION SYSTEM, DECISION SUPPORT SYSTEM

FINANCIAL MANAGEMENT INFORMATION SYSTEM

Financial management information system provides information not only for managers but also for a broader set of people who need to make better decisions on a daily basis. Finding opportunities and quickly identifying problems can mean the difference between a business’s success and failure.

Financial statements Uses and management of funds Financial statistics for control Operational databases Databases of valid transactions for each TPS Transaction processing systems Business transactions Internet or Extranet Financial MIS Business transactions Databases of external data Databases of internal data Financial DSS Financial ES Financial applications databases Customers, Suppliers

FUNCTIONS OF FINANCIAL MIS 1.Integrates financial and operational information from multiple sources, including the internet, into single MIS. 2.Provides easy access to data for both financial and non financial users, often through use of the corporate intranet to access corporate web pages of financial data and information. 3.Makes financial data available on a timely basis to shorten analysis turn around time. 4.Enables analysis of financial data along multiple dimensions – time, geography, product, plant, customer.

Inputs to the Financial Information System Strategic plan or corporate policies – Contains major financial objectives and often projects financial needs. Transaction processing system (TPS) – Important financial information collected from almost every TPS - payroll, inventory control, order processing, accounts payable, accounts receivable, general ledger. – External sources – Annual reports and financial statements of competitors and general news items.

Financial MIS Subsystems and Outputs Financial subsystems – Profit/loss and cost systems – Auditing – Internal auditing – External auditing – Uses and management of funds

DECISION SUPPORT SYSTEM

A Decision Support System (DSS) is an interactive computer-based system or subsystem intended to help decision makers use communications technologies, data, documents, knowledge and/or models to identify and solve problems, complete decision process tasks, and make decisions. Decision Support System is a general term for any computer application that enhances a person or group’s ability to make decisions. Also, Decision Support Systems refers to an academic field of research that involves designing and studying Decision Support Systems in their context of use.

Model-driven DSS: Types of Decision-Support Systems Primarily stand-alone systems Use a strong theory or model to perform “what-if” and similar analyses

Data-driven DSS: Integrated with large pools of data in major enterprise systems and Web sites Support decision making by enabling user to extract useful information Data mining: Can obtain types of information such as associations, sequences, classifications, clusters, and forecasts

SYSTEMS FOR DECISION SUPPORT Components of DSS DSS database: A collection of current or historical data from a number of applications or groups DSS software system: Contains the software tools for data analysis, with models, data mining, and other analytical tools DSS user interface: Graphical, flexible interaction between users of the system and the DSS software tools

SYSTEMS FOR DECISION SUPPORT Model: An abstract representation that illustrates the components or relationships of a phenomenon Statistical models Optimization models Forecasting models Sensitivity analysis (“what-if” models)

SYSTEMS FOR DECISION SUPPORT Overview of a Decision-Support System

Providing fine-grained information for decisions that enable the firm to coordinate both internal and external business processes much more precisely Helping with decisions in SYSTEMS FOR DECISION SUPPORT Business Value of DSS Supply chain management Customer relationship management

Pricing Decisions Asset Utilization Data Visualization: Presentation of data in graphical forms, to help users see patterns and relationships Geographic Information Systems (GIS): Special category of DSS that display geographically referenced data in digitized maps SYSTEMS FOR DECISION SUPPORT Business Value of DSS (Continued)

The key DSS characteristics and capabilities are as follows: 1.Support for decision makers in semi structured and unstructured problems. 2.Support managers at all levels. 3.Support individuals and groups. 4.Support for interdependent or sequential decisions. 5.Support intelligence, design, choice, and implementation. 6.Support variety of decision processes and styles. 7.DSS should be adaptable and flexible. 8.DSS should be interactive ease of use. 9.Effectiveness, but not efficiency. 10.Complete control by decision-makers. 11.Ease of development by end users. 12.Support modeling and analysis. 13.Data access. 14.Standalone, integration and Web-based

Supports – Problem solving phases – Different decision frequencies Frequency lowhigh Merge with another company? How many widgets should I order?

Highly structured problems – Straightforward problems, requiring known facts and relationships. Semi-structured or unstructured problems – Complex problems wherein relationships among data are not always clear, the data may be in a variety of formats, and are often difficult to manipulate or obtain

Operational-level managers involved with daily decisions Strategic-level managers involved with long-term decisions LowHigh Decision Frequency Strategic Tactical Operational

In many organizations they are integrated through a common database Separation of DSS transactions in the database from TPS and MIS transactions may be important for performance reasons

DatabaseModel base External database access Access to the internet, networks, and other computer systems Dialogue manager DBMSMMS External databases

(1) Time savings. For all categories of decision support systems, research has demonstrated and substantiated reduced decision cycle time, increased employee productivity and more timely information for decision making. The time savings that have been documented from using computerized decision support are often substantial. Researchers, however, have not always demonstrated that decision quality remained the same or actually improved. (2) Enhance effectiveness. A second category of advantage that has been widely discussed and examined is improved decision making effectiveness and better decisions. Decision quality and decision making effectiveness are however hard to document and measure. Most researches have examined soft measures like perceived decision quality rather than objective measures. Advocates of building data warehouses identify the possibility of more and better analysis that can improve decision making.

(3 ) Improve interpersonal communication. DSS can improve communication and collaboration among decision makers. In appropriate circumstances, communications- driven and group DSS have had this impact. Model-driven DSS provides a means for sharing facts and assumptions. Data-driven DSS make "one version of the truth" about company operations available to managers and hence can encourage fact- based decision making. Improved data accessibility is often a major motivation for building a data-driven DSS. This advantage has not been adequately demonstrated for most types of DSS. (4) Competitive advantage. Vendors frequently cite this advantage for business intelligence systems, performance management systems, and web-based DSS. Although it is possible to gain a competitive advantage from computerized decision support, this is not a likely outcome. Vendors routinely sell the same product to competitors and even help with the installation. Organizations are most likely to gain this advantage from novel, high risk, enterprise-wide, inward facing decision support systems. Measuring this is and will continue to be difficult.

(1) Monetary cost. The decision support system requires investing in information system to collect data from many sources and analyze them to support the decision making. Some analysis for Decision Support System needs the advance of data analysis, statistics, econometrics and information system, so it is the high cost to hire the specialists to set up the system. (2) Overemphasize decision making. Clearly the focus of those of us interested in computerized decision support is on decisions and decision making. Implementing Decision Support System may reinforce the rational perspective and overemphasize decision processes and decision making. It is important to educate managers about the broader context of decision making and the social, political and emotional factors that impact organizational success. It is especially important to continue examining when and under what circumstances Decision Support System should be built and used. We must continue asking if the decision situation is appropriate for using any type of Decision Support System and if a specific Decision Support System is or remains appropriate to use for making or informing a specific decision. (3) Assumption of relevance. According to Wino grad and Flores (1986), "Once a computer system has been installed it is difficult to avoid the assumption that the things it can deal with are the most relevant things for the manager's concern." The danger is that once Decision Support System become common in organizations, that managers will use them inappropriately. There is limited evidence that this occurs. Again training is the only way to avoid this potential problem. (4) Transfer of power. Building Decision Support System, especially knowledge-driven Decision Support System, may be perceived as transferring decision authority to a software program. This is more a concern with decision automation systems than with Decision Support System. We advocate building computerized decision support systems because we want to improve decision making while keeping a human decision maker in the "decision loop". In general, we value the "need for human discretion and innovation" in the decision making process. (1) Monetary cost. The decision support system requires investing in information system to collect data from many sources and analyze them to support the decision making. Some analysis for Decision Support System needs the advance of data analysis, statistics, econometrics and information system, so it is the high cost to hire the specialists to set up the system. (2) Overemphasize decision making. Clearly the focus of those of us interested in computerized decision support is on decisions and decision making. Implementing Decision Support System may reinforce the rational perspective and overemphasize decision processes and decision making. It is important to educate managers about the broader context of decision making and the social, political and emotional factors that impact organizational success. It is especially important to continue examining when and under what circumstances Decision Support System should be built and used. We must continue asking if the decision situation is appropriate for using any type of Decision Support System and if a specific Decision Support System is or remains appropriate to use for making or informing a specific decision..

(3 ) Assumption of relevance. According to Wino grad and Flores (1986), "Once a computer system has been installed it is difficult to avoid the assumption that the things it can deal with are the most relevant things for the manager's concern." The danger is that once Decision Support System become common in organizations, that managers will use them inappropriately. There is limited evidence that this occurs. Again training is the only way to avoid this potential problem. (4) Transfer of power. Building Decision Support System, especially knowledge-driven Decision Support System, may be perceived as transferring decision authority to a software program. This is more a concern with decision automation systems than with Decision Support System. We advocate building computerized decision support systems because we want to improve decision making while keeping a human decision maker in the "decision loop". In general, we value the "need for human discretion and innovation" in the decision making process

Group Decision-Support System (GDSS) is an interactive computer-based system used to facilitate the solution of unstructured problems by a set of decision makers working together as a group. GROUP DECISION-SUPPORT SYSTEMS What Is a GDSS?

Hardware (conference facility, audiovisual equipment, etc.) Software tools (Electronic questionnaires, brainstorming tools, voting tools, etc.) People (Participants, trained facilitator, support staff) Three Main Components of GDSS: Three Main Components of GDSS: GROUP DECISION-SUPPORT SYSTEMS

Group System Tools GROUP DECISION-SUPPORT SYSTEMS Source: From Nunamaker et al., “Electronic Meeting Systems to Support Group Work,” Communication of the ACM, July Reprinted with permission.

Traditional decision-making meetings support an optimal size of three to five attendees. GDSS allows a greater number of attendees. Enable collaborative atmosphere by guaranteeing contributor’s anonymity. Enable nonattendees to locate organized information after the meeting. Business Value of GDSS GROUP DECISION-SUPPORT SYSTEMS

Traditional decision-making meetings support an optimal size of three to five attendees. GDSS allows a greater number of attendees. Enable collaborative atmosphere by guaranteeing contributor’s anonymity. Enable nonattendees to locate organized information after the meeting. Business Value of GDSS GROUP DECISION-SUPPORT SYSTEMS

Can increase the number of ideas generated and the quality of decisions while producing the desired results in fewer meetings Can lead to more participative and democratic decision making GROUP DECISION-SUPPORT SYSTEMS Business Value of GDSS (Continued)