Managerial Support Systems PDF

CHAPTER 6: MANAGERIAL SUPPORT SYSTEMS Managerial support systems are designed to provide support to a specific manager or a small group of managers, and they include applications to support managerial decision-making such as group support systems, executive information systems, and expert...

CHAPTER 6: MANAGERIAL SUPPORT SYSTEMS Managerial support systems are designed to provide support to a specific manager or a small group of managers, and they include applications to support managerial decision-making such as group support systems, executive information systems, and expert systems. Enterprise systems have been designed to support the organization, not you or even a group of managers. On the other hand, managerial support systems are intended to directly support you and other managers as you make strategic and tactical decisions for your organizations. DECISION SUPPORT SYSTEM A decision support system (DSS) is a computer-based system, almost always interactive, designed to assist a manager (or another decision maker) in making decisions. Incorporates both data and models to help a decision-maker solve a problem, especially a problem that is not well structured. The data are often extracted from a transaction processing system or a data warehouse. DSS requires three primary components: Model management to apply the appropriate model. Data management to select and handle the appropriate data. Dialog management interface to the DSS. Specific DSSs are the actual applications that assist in the decision-making process. DSS generator is a software package that provides a set of capabilities to build a specific DSS quickly and easily. DATA MINING Data mining, also known as knowledge discovery in data (KDD), is the process of uncovering patterns and other valuable information from large data sets. Employs a variety of technologies to search for information from the vast quantities of data stored in an organization’s data warehouse. Commercial data mining software products: IBM SPSS Modeler Professional XLMiner for Windows Oracle Data Mining KnowledgeSEEKER, Salford Predictive Miner KnowledgeSTUDIO, SAS Enterprise Miner and Text Miner StrategyBUILDER) TIBCO Spotfire Miner Decision techniques or approaches used in data mining: 1. Decision trees A decision tree is a tree-shaped structure that is derived from the data to represent sets of decisions that result in various outcomes. When a new set of decisions is presented, such as information on a particular shopper, the decision tree then predicts the outcome. 2. Linear and logistic regression Association rules for finding patterns of co-occurring events. 3. Rule induction the extraction of if-then rules based on statistical significance. 4. Nearest neighbor the classification of a record based on those most similar to it in the database. 5. Genetic algorithms optimization techniques based on the concepts of genetic combination, mutation, and natural selection. Uses of Data Mining: Cross-selling Identify products and services that will most appeal to existing customer segments and develop cross-sell and up-sell offers tailored to each segment. Customer churn Predict which customers are likely to leave your company and go to a competitor and target those customers at highest risk.  Customer retention Identify customer characteristics associated with the highest lifetime value and develop strategies to retain these customers over the long term. Direct marketing Identify which prospects should be included in a mailing list to obtain the highest response rate. Fraud detection Identify which transactions are most likely to be fraudulent based on purchase patterns and trends; identify insurance claims that are most likely to be fraudulent based on similar past claims. Interactive marketing Predict what each individual accessing a website is most likely interested in seeing. Market basket analysis Understand what products or services are commonly purchased together (e.g., beer and diapers) and develop appropriate marketing strategies. Market segmentation Segment existing customers and prospects into appropriate groups for promotional and evaluation purposes and determine how to approach each segment for maximum results. Payment or default analysis Identify specific patterns to predict when and why customers default on payments. Trend analysis Investigate the difference between an average purchase this month versus last month and prior months. GROUP SUPPORT SYSTEMS Group Support System (GSS) is a specialized type of groupware and a collaboration tool that is specifically aimed at supporting meetings. In a typical in-person implementation of the original Group Systems GSS (see Figure 6.2), a computer-supported meeting room is set up containing a PC for each participant, all linked by a local area network (LAN). A large public screen facilitates common viewing of information when this is desired. Group Systems, which is installed on each machine in the network, provides computerized support for idea generation, organizing ideas, prioritizing (such as voting), and policy development (such as stakeholder identification). Each participant in a group session (e.g., a brainstorming session) has the opportunity to provide input anonymously and simultaneously via the PC keyboard.  Recent work in the GSS area has moved beyond the support of the traditional group session. The new focus is to support the work team in all its endeavors, whether the team is operating in a “same time, same place” traditional meeting or in a “different time, different place” mode— that is, as a virtual team. GEOGRAPHIC INFORMATION SYSTEMS Geographic Information Systems is a geographic technology that captures, stores, manipulates, displays, and analyzes data spatially referenced to the Earth. Components of GIS: Hardware - Hardware is the computer on which a GIS operates. Software - GIS software provides the functions and tools needed to store, analyze, and display geographic information. Data - The most important component of a GIS which can be collected in-house or purchased from a commercial data provider. People - GIS technology is of limited value without the people who manage the system and develop plans for applying it to real world problems. Methods - A successful GIS operates according to a well-designed plan and business rules, which are the models and operating practices unique to each organization. Fields as diverse as natural resources management, public administration, NASA, the military, and urban planning have been using GIS for more than four decades.  In the 1990s, geographic technologies came to the attention of business users as the power of desktop computing merged with widespread access to geographic data. Today, geographic technologies are moving into key business functions enabled by technologies such as: Radio Frequency Identification (RFID) tags Global Positioning System (GPS) capabilities Database Management Systems (DBMSs) spatial analysis features Business Adopts Geographic Technologies Firms such as Arby’s and McDonald’s – whose ability to succeed depends on being in a better location than competitors- used GIS for site location to become among the first to recognize the business benefits of geographic technologies. Culver’s uses Esri’s GIS software to help franchisees choose the best possible locations for their restaurants. It is hard to find an industry or government agency that does not have spatial needs. Health care, transportation, telecommunications, homeland security, law enforcement, natural resources, utilities, real estate, banking, and media all need to locate people or assets, or both, in space and to predict their behavior. What’s Behind Geographic Technologies Two approaches to representing spatial data are widely used: the raster approach and the vector approach. Both types of data are commonly managed in a data model that stores related data in layers known as coverages or themes. Raster-based GIS divides space into small, equal-sized cells arranged in a grid. In a GIS, these cells (rasters) can take on a range of values and are aware of their location relative to other cells. Vector-based GISs are widely used in public administration and utilities and, arguably, are the most common approach used in business. Vector systems associate features in the landscape with either a point, a line, or a polygon. Points are often used to represent small features such as ATMs, customer addresses, power poles, or items in motion. Lines are for linear features such as roads and rivers. Polygons represent areas and surfaces, including lakes, land parcels, and regions. The relationships between the vector elements are called their topology. The most common data model for both vector and raster data is the coverage model in which different layers or themes represent similar types of geographic features in the same area and are stacked on top of one another.  Most GIS technologies today effectively combine both types of data, often using raster data sets for realism and vector data for roads, administrative boundaries, and locations. By employing both types of data, geographic analysis can answer questions such as the following: What is adjacent to this feature? Which site is the nearest one, or how many are within a certain distance? What is contained within this area, or how many are contained within this area? Which features does this element cross, or how many paths are available? What could be seen from this location? Issues for Information Systems Organizations Managing geographic technology options, now that they are available on familiar platforms, may be less challenging to a typical IS organization than managing spatial data. Because the value for a business in going spatial comes from bringing internal and external data together, IS personnel can expect to get an education in cost and quality issues for geographic data. Ongoing developments in geographic technologies include the following: three-dimensional and dynamic modelling to simulate movement through time and space. geography in your hand—the continued proliferation of spatial technologies. linking spatial capability with wireless capability for deployment and redeployment of the right assets— both human and nonhuman—to the right place, in real time. forecasting models that include geography as a variable to predict. use of spatial technologies in a variety of new settings. EXECUTIVE INFORMATION SYSTEMS/BUSINESS INTELLIGENCE SYSTEMS An executive information system is a type of management support system that facilitates and supports senior executive information and decision-making needs. It provides easy access to internal and external information relevant to organizational goals. Dating only to the late 1980s in most cases, EISs represent the first real attempt to deliver relevant summary information to management in online form. Originally, EISs were developed for just the two or three top executive levels in the firm, but that caused many problems of data disparity between the layers of management. As a result, today the user base in most companies has been broadened to encompass all levels  of management in the firm. Largely because of this broadening of the user base, today the EIS label has often been replaced with the broader term performance management (PM) software. Many successful EISs incorporate qualitative data such as competitive information, assessments, and insights. This emphasis on competitive information has become so important in the last few years that many organizations now call their EISs business intelligence (BI) systems or competitive intelligence systems. Infor is an example of a software platform for developing a performance management/business intelligence system. Infor PM Core Components: Strategic Management Forecasting Planning Financial Consolidation Budgeting Reporting and Analysis Modules of Reporting and Analysis: Infor PM Application Studio - Provides business intelligence by accessing, filtering, analyzing, and distributing information throughout the organization. Infor PM OLAP - Permits querying against a multidimensional database. Infor PM OfficePlus - A Microsoft Excel add-in designed for analysts who need financial reporting and analysis capabilities. Infor PM permits a customization of a large number of easy-to-use and easy-to-interpret displays to present key information to managers; the software package allows business users to view information in whatever way makes sense to them. Other EIS/PM products include: Executive Dashboard from Qualitech Solutions Oracle Enterprise Performance Management System SAP BusinessObjects Strategy Management, SAS/EIS SymphonyRPM from Symphony Metreo.  Business intelligence platforms, which overlap considerably with EIS/PM products but sometimes have a broader focus and sometimes a narrower focus include: IBM Cognos Business Intelligence MicroStrategy Intelligence Server Oracle Business Intelligence Suite SAP Business Objects BI Solutions (including Advanced Visualization, Dashboard Builder, and Voyager) SAS Business Intelligence KNOWLEDGE MANAGEMENT SYSTEMS Systems that enable individuals and organization to enhance learning, improve performance, and produce long-term sustainable competitive advantage. System for managing organizational knowledge. Provide organizations the ability to leverage and extract value from their intellectual or knowledge assets. Connection strategies: 1. Connections from people to people 2. Connections from people to knowledge 3. Connections from people to tools Knowledge Management (KM): Is a set of management practices that is practical and action-oriented. Concerned with behavior changes to reflect new knowledge. Relies on recognizing the knowledge held by individuals and the firm. Why has KM received so much of attention, and why are so many projects labeled KM projects? 1. Value will exceed its cost. 2. Firm valuation 3. Source of competitive advantage 4. Tangible benefits accrue from implementing KM and KMS initiatives. Operational improvements - Focus on internal activities. Market improvements - Focus on external activities.  Goal of a KMS: 1. Tap into the knowledge of the individual and the firm. 2. To disseminate it throughout the firm Difference of KMS to the other system: It considers the content contained within the system. The system acquire knowledge needed to perform the task. 3 characteristics of KMS: 1. Formal management and control 2. Focus of the KM processes 3. Reusability of knowledge is considered. COP (Communities of practice) KMS: have very little formal management control. members are responsible for validating and structuring their knowledge for use within the KMS. KM Team: extensive formal management and control oversee the process of validating the knowledge prior of dissemination. 80-20 rule Note: There is a spectrum of KMSs that are designed to meet the specific needs of a given firm Two recent KMS initiatives within a Pharmaceutical Firm 1. Corporate KMS KM team was formed to develop an organization-wide KMS serving multiple communities of practice Coordinators are volunteers and receive no extra compensation, but they do tend to become highly visible members of their communities. Portal software - used to support the COPS. Provides approximately 150 tools. 3 most commonly used tools are the discussion forum, tips, and calendar.  Discussion forum - a tool that enables question and answer discussions among member of the community. Tips tool - enables any member to write a short entry that documents some best practices advice. Calendar - includes face to face meetings, seminars and workshop, and more formal presentations. 2. Field Sales KMS This KMS team’s mission was to design and build both the content and the structure of the KMS. A knowledge of taxonomy was developed. The system was designed to be the primary knowledge repository used by the field sales representatives and sales managers. Field sales representative - contribute sales tips and practical advice for use by other sales representatives. Four-step process for validating all content: process within 2 weeks: 1 tip= approximately 60 dollars. 1. Vetted by the KM team. 2. The tip was submitted to the legal group. 3. The tip was sent to the brand management team. 4. The tip was sent to the sales operation group. T-structure: Across the top of the T - general sales knowledge designed to be pertinent to all sales division Down the middle of the T - the division-specific knowledge What does it take for a KMS to be a success? 1. Both the supply and demand sides of KM must be considered simultaneously. 2. The importance of social capital in determining whether benefits can be realized. ARTIFICIAL INTELLINGENCE The study of how to make computers do things that are currently done better by people. Over 50 years old but only in the last 30 years have computers become powerful enough to make AI app commercially attractive.  AI research into six separate but related areas: Natural languages o Is aimed at producing systems that translate ordinary human instructions into a language that computers can understand and execute. Robotics o to create intelligent machines that can assist humans in a variety of ways. Perceptive system (vision and hearing) o Involves creating machines possessing a visual and or aural perceptual ability that affects their physical behavior. o This research is aimed at creating robots that can see or hear and react to what they see or hear. Genetic programming (evolutionary design) o Or evolutionary design o The problem is divided into multiple segments, and solutions to these segments are linked together in different ways to breed new ‘child’ solution. o Might produce superior to anything devised by human. o Most useful in the design of innovative products such as: energy efficient halogen light bulb and satellite Expert system o Concerned with building systems that incorporate the decision-making logic of human expert. Neutral networks o named after the study of how human nervous system works. o Uses statistical analysis to recognize patterns from the vast amounts of information by a process of adaptive learning. EXPERT SYSTEM A computer system wherein it imitates the decision-making ability of an expert. It is designed to solve complex problems by reasoning.  Architecture of an Expert System Knowledge Engineer - Works very closely with one or more experts in the area under study. Knowledge Base - Contains both the inference rule and the parameters, or facts. Inference Engine - Logical framework that automatically executes a line of reasoning when supplied with the inference rules and parameters involved in the decision. User Interface - Allows a non-expert user to question the expert system. Explanation Subsystem - Explain the reasoning that the system followed in arriving at a decision. Workspace - for the computer to use as the decision is being made. Knowledge Acquisition Subsystem - To assist the knowledge engineer in recording inference rules and parameters in the knowledge base. General Approaches on Obtaining Expert System 1. An organization can buy a fully developed system that has been created for a specific application. 2. An organization can develop an expert system itself using an artificial intelligence shell (also called an expert systems shell). 3. An organization can have internal or external knowledge engineers custom-build the expert system. Examples of Expert Systems MYCIN - To diagnose and prescribe treatment for meningitis and blood diseases. CATS-1 - To diagnose mechanical problems in diesel locomotives. ACE - To locate faults in telephone cables.  Dipmeter - To give advice when a drill bit gets stuck while drilling a well. Market Surveillance - To help detect insider trading on the exchange. FAST (Financial Analysis Support Techniques) - Gives a credit analyst access to the expertise of more experienced analysts, speeding up the training process and increasing productivity. IDP (Individual development plan) Goal Advisor - Assists a supervisor and an employee in setting short-range and long-range employee career goals and the developmental objectives to reach these goals. EXNUT - To help peanut farmers manage irrigated peanut production. ESS (Expert Scheduling System) - To generate viable manufacturing schedule. Asbestos Advisor - One of the online advisors that have been created for more than a dozen complex areas of Occupational Safety and Health Administration (OSHA) regulations. Case Worker Advisor - To support the Navajo Nation’s Tribal Temporary Assistance for Needy Families (TANF) welfare program. NEURAL NETWORKS Can recognize patterns too obscure for humans to detect, and they adapt as new information is received. Analyzes the data, works out all the correlations, and then selects a set of variables that are strongly correlated with particular known outcomes as the initial pattern. Learns more about cause-and-effect patterns from this additional data, and its predictive ability usually improves accordingly. Commercial neural network programs are available for a reasonable price. Uses of Neural Networks Categorization: Credit rating and risk assessment Machinery defect diagnosis Insurance risk evaluation Character recognition Fraud detection Medical diagnosis Insider trading detection Bacteria identification Direct mail profiling Prediction/Forecasting: Share price forecast Weather prediction Commodity price forecast Future drug performance Economic indicator predictions Production requirement Process control Other Uses of Neural Networks Used to predict the total contingency costs on construction projects. Used to predict the probability of bankruptcy to help banks make lending decisions. Used in investment and trading applications. Used in targeted marketing. Used to improve security. VIRTUAL REALITY Refers to the use of computer-based systems to create an environment that seems real to one or more senses (usually including sight) of the human user or users. The use of VR in a nonentertainment setting falls primarily into three categories: Training, Design, and Marketing. Training The U.S. Army uses VR to train tank crews. Medical students are learning through collaboration and trial-and-error on virtual cadavers, which is much less expensive than using actual bodies. Truck driVR, for use in training its drivers. Duracell also employs VR for training. The company needed to train its factory personnel on the new equipment in a safe and cost-effective manner.  Design Several automobile manufacturers use VR to assist in the design of new automobiles. General Motors created the Envisioning Center, a three-screened, theater-like room where designers can view 3-D images of car designs. Arizona State University has created the Decision Theater, an immersive 3-D visualization environment that has many similarities to GM’s Envisioning Center. An air conditioning/furnace manufacturer is using VR to permit engineers to walk through an existing or proposed product. Marketing A very popular use of VR-like technology is the use of “virtual tours” for the real estate industry, the travel and hospitality industry, and educational institution. If you are house hunting, you can get a 360-degree view of the great room and the kitchen in a home for sale. If planning a vacation, you can get a 360-degree view of the grounds and the lobby of a resort hotel. If selecting a college, you can get a 360-degree look at key buildings on campus. CirclePix 360-Degree Virtual Tour of Family Room