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Management Information Systems - PowerPoint PPT Presentation

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Management Information Systems. Agenda. Warriors - video (10 mins) Telecommunication trends The Internet, Intranet, Extranet. Basic Components of a Network Model. Let’s watch a video Some definitions Ping of Death – DoS attack – a packet sent by a hacker

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  • Warriors - video (10 mins)

  • Telecommunication trends

  • The Internet, Intranet, Extranet

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Basic Components of a Network Model

  • Let’s watch a video

  • Some definitions

    • Ping of Death – DoS attack – a packet sent by a hacker

    • Port – interface of a computer application through which data are sent and received

      • 80 – Internet, 25 – email

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Internet Networking Technologies

  • Internet networking technologies are being used as technology platform

    • Web browser suites

    • HTML Web page editors

    • Network management software

    • Firewalls

  • Being applied in Internet, intranet, and extranet applications

  • Reinforces previous move toward client/server networks based on open-systems architecture

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Open Systems

  • Open systems use common standards for hardware, software, applications, and networks

    • Internet networking technologies are a common standard for open systems

  • Connectivity

    • Open systems provide greater connectivity and network interoperability

    • Middleware may be needed to help diverse systems work together

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  • Middleware

    • A general term for any programming that mediates between two separate programs

    • Allows a particular database to access other databases without custom programming

  • Commonly known as the “glue” of an information system

    • It routes data and information between back-end data sources and end user applications

    • An essential component of any IT infrastructure

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Digital Network Technologies

  • Telecommunications are being revolutionized by switch from analog to digital

    • Analog: voice-oriented transmission

    • Digital: discrete pulse transmission

  • Benefits

    • Higher transmission speeds

    • Moves larger amounts of information

    • Greater economy and much lower error rates

    • Transmits multiple types of communications (data, voice, video) on the same circuits

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The Internet Revolution

  • The Internet has become a global information superhighway

    • Millions of smaller, private networks operating independent of, or in harmony with, each other

    • 10 servers in 1991 to over 46 million today

    • Sustained growth in excess of 1 million servers per month

    • No central computer system

    • No governing body

    • Based on common standards

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  • Next generation of the Internet

    • High-performance

    • Different infrastructure than the current Internet

    • Will not replace the current Internet

    • In use at over 200 universities, scientific institutions, communications corporations

    • May never become totally open

    • Users are connected via a backbone that supports throughput of 10 Gbps

    • Infinite bandwidth

    • Over 4 million users

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Internet Service Providers

  • ISP

    • A company that specializes in providing easy access to the Internet

    • For a monthly fee, provides software, user name, password, and Internet access

  • ISPs themselves are connected to one another through network access points

    • One ISP can easily connect to another to obtain addresses of websites or user nodes

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Intranets as Information Portals

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  • Network links that use Internet technologies to connect the intranet of a business to the intranets of another

  • Virtual Private Networks

    • Direct private network links, or private secure Internet links between companies

  • Firewalls and encryption

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Telecommunications Network Knowledge

  • Telecommunications is a highly technical, rapidly changing field

    • Most business professionals don’t need detailed technical knowledge

    • However, understanding basic components and their characteristics is necessary

    • Can help you make informed decisions about telecommunications alternatives

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Enterprise Systems

Enterprise Systems

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  • Cross-functional enterprise systems

    • Enterprise application integration

    • Transaction processing systems

    • Enterprise collaboration systems

  • Functional enterprise systems

    • Accounting, Finance, HR management, Marketing, Production, Operations management

  • Cross-functional systems

    • CRM and ERP

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Cross-Functional Enterprise Applications

  • In the past - functional mainframe legacy systems

  • The current trend is to employ integrated cross-functional systems

    • ERP, CRM, SCM (supply-chain mgt)

    • SAP, Oracle PeopleSoft

  • Cross-functional systems are

    • Integrated combinations of information subsystems that share information resources and support business processes across the functional units

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Cross-Functional Systems

  • Cross the boundaries of traditional business functions

    • Used to reengineer and improve vital business processes all across the enterprise

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Enterprise Application Architecture

  • Enterprise Resource Planning (ERP)

    • Concentrates on the efficiency of internal production, distribution, and financial processes

  • Customer Relationship Management (CRM)

    • Focuses on acquiring and retaining profitable customers via marketing, sales, and services

  • Partner Relationship Management (PRM)

    • Aims at acquiring and retaining partners who can enhance the selling and distribution of products and services

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Enterprise Application Architecture

  • Supply Chain Management (SCM)

    • Focuses on developing the most efficient and effective sourcing and procurement processes

  • Knowledge Management (KM)

    • Focuses on facilitating internal group collaboration and decision support

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Enterprise Application Integration

  • EAI software connects cross-functional systems

  • Serves as middleware to provide

    • Data conversion

    • Communication between systems

    • Access to system interfaces

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Transaction Processing Systems

  • Cross-functional information systems that process data resulting from the occurrence of business transactions

    • Transactions include sales, purchases, deposits, withdrawals, refunds, and payments

    • Online transaction processing (OLTP) is a real-time system that captures transactions immediately

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Enterprise Collaboration Systems (ECS)

  • EC systems are cross-functional information systems that enhance team and workgroup

    • Communication

    • Coordination

    • Collaboration

  • MS SharePoint

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Enterprise Collaboration Systems

  • Fortune 500 companies lose $12 billion annually due to an inability to locate information

  • Knowledge worker spends 2.5 hours per day searching for information

  • In most cases, other organization members already know this information

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Enterprise Collaboration Systems

  • Cross-functional e-business systems that enhance communication, coordination, & collaboration

    • Communicate – share information with each other

    • Coordinate – coordinate individual work efforts & use of resources with each other.

    • Collaborate – work together cooperatively on joint projects and assignments

  • Why do most KM projects fail?

    • Knowledge hoarding

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Functional Business Systems

  • A variety of types of information systems that support the business functions of

    • Accounting

    • Finance

    • Marketing

    • Operations management

    • Human resource management

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Customer Relationship Management

  • A customer-centric focus

    • Customer relationships have become a company’s most valued asset

    • Every company’s strategy should be to find and retain the most profitable customers possible

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What is CRM?

  • Managing the full range of the customer relationship involves

    • Providing customer-facing employees with a single, complete view of every customer at every touch point and across all channels

    • Providing the customer with a single, complete view of the company and its extended channels

  • CRM uses IT to create a cross-functional enterprise system that integrates and automates many of the customer-serving processes

    • Shaw Cable example

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Contact and Account Management

  • CRM helps sales, marketing, and service professionals capture and track relevant data about

    • Every past and planned contact with prospects and customers

    • Other business and life cycle events of customers

  • Data are captured through customer touchpoints

    • Telephone, fax, e-mail

    • Websites, retail stores, kiosks

    • Personal contact

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  • A CRM system provides sales reps with the tools and data resources they need to

    • Support and manage their sales activities

    • Optimize cross- and up-selling

  • CRM also provides the means to check on a customer’s account status and history before scheduling a sales call

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Marketing and Fulfillment

  • CRM systems help with direct marketing campaigns by automatic such tasks as

    • Qualifying leads for targeted marketing

    • Scheduling and tracking mailings

    • Capturing and managing responses

    • Analyzing the business value of the campaign

    • Fulfilling responses and requests

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Customer Service and Support

  • A CRM system gives service reps real-time access to the same database used by sales and marketing

    • Requests for service are created, assigned, and managed

    • Call center software routes calls to agents

    • Help desk software provides service data and suggestions for solving problems

  • Web-based self-service enables customers to access personalized support information

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Retention and Loyalty Programs

  • It costs 6 times more to sell to a new customer

  • An unhappy customer will tell 8-10 others

  • Boosting customer retention by 5 percent can boost profits by 85 percent

  • The odds of selling to an existing customer are 50 percent; a new one 15 percent

  • About 70 percent of customers will do business with the company again if a problem is quickly taken care of

  • Extremely important to e-commerce companies

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Retention and Loyalty Programs

  • Enhancing and optimizing customer retention and loyalty is a primary objective of CRM

    • Identify, reward, and market to the most loyal and profitable customers

    • Evaluate targeted marketing and relationship programs

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Benefits of CRM

  • Benefits of CRM

    • Identify and target the best customers

    • Real-time customization and personalization of products and services

    • Track when and how a customer contacts the company

    • Provide a consistent customer experience

    • Provide superior service and support across all customer contact points

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CRM Failures

  • Business benefits of CRM are not guaranteed

    • 50 percent of CRM projects did not produce promised results

    • 20 percent damaged customer relationships

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CRM Failures

  • Reasons for failure

    • Not solving business process problems first

    • Due to the lack of understanding & preparation

      • Technology is implemented and it is hoped that it will solve all current business problems

      • No business process change and cultural change

      • Key stakeholders should be involved from before making a decision to acquire a CRM system

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CRM Examples

  • Examples of CRM applications

    • MS Dynamics CRM - Video

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ERP: The Business Backbone

  • ERP is a cross-functional enterprise backbone that integrates and automates processes within

    • Manufacturing

    • Logistics

    • Distribution

    • Accounting

    • Finance

    • Human resources

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What is ERP?

  • Enterprise resource planning is a cross-functional enterprise system

    • An integrated suite of software modules

    • Supports basic internal business processes

    • Facilitates business, supplier, and customer information flows

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Enterprise Resource Planning (continued)

  • ERP gives a company an integrated real-time view of its core business processes

  • Tracks all business resources

    • Cash, raw materials, production capacity

  • Business commitments

    • Orders, employee payroll, etc

  • No matter what department is in charge of each area

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Benefits and Challenges of ERP

  • ERP Business Benefits

    • Quality and efficiency

    • Decreased costs

    • Decision support

    • Enterprise agility

  • ERP Costs

    • Risks and costs are considerable

    • Hardware and software are a small part of total costs

    • Failure can cripple or kill a business

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Causes of ERP Failures

  • Most common causes of ERP failure

    • Under-estimating the complexity of planning, development, training

    • Failure to involve affected employees in planning and development

    • Trying to do too much too fast

    • Insufficient training

    • Insufficient data conversion and testing

    • Over-reliance on ERP vendor or consultants

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ERP Demo

  • SAP Business One Video

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  • DSS in Business

  • AI and Intelligent Agent Technologies

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Decision Structure

  • Unstructured (strategic)

    • It is not possible to specify in advance most of the decision procedures to follow

  • Semi-structured (tactical)

    • Decision procedures can be pre-specified, but not enough to lead to the correct decision

  • Structured (operational)

    • The procedures to follow when decision is needed can be specified in advance

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DSS Model Base

  • Model Base

    • A software component that consists of models used in computational and analytical routines that mathematically express relations among variables

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Applications of Statistics and Modeling

  • Supply Chain: simulate and optimize supply chain flows, reduce inventory, reduce stock-outs

  • Pricing: identify the price that maximizes yield or profit

  • Product and Service Quality: detect quality problems early in order to minimize them

  • Research and Development: improve quality, efficacy, and safety of products and services

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Using Decision Support Systems

  • Using a decision support system involves an interactive analytical modeling process

    • Decision makers are not demanding pre-specified information

    • They are exploring possible alternatives

  • What-If Analysis

    • Observing how changes to selected variables affect other variables

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Using Decision Support Systems

  • Sensitivity Analysis

    • Observing how repeated changes to a single variable affect other variables

  • Goal-seeking Analysis

    • Making repeated changes to selected variables until a chosen variable reaches a target value

  • Optimization Analysis

    • Finding an optimum value for selected variables, given certain constraints

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Using Decision Support Systems (continued)

  • Sensitivity Analysis

    • The value of only one variable is changed repeatedly, and the resulting changes on other variables are observed

    • Typically used when there is uncertainty about the assumptions made in estimating the value of certain key variables

    • E.g., cut the advertising budget $1,000 at a time and see the effect on sales, profits, etc.

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Using Decision Support Systems (continued)

  • Goal-Seeking Analysis

    • Instead of observing how changes in a variable affect other variables, goal-seeking sets a target value (a goal) for a variable, then repeatedly changes other variables until the target value is achieved

    • Set the net profit to $1,000,000 and see what revenues are required for that

    • Note: in what-if and sensitivity analysis, users specify inputs, in goal seeking - output

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Using Decision Support Systems (continued)

  • Optimization Analysis

    • A more complex extension of goal-seeking

    • The goal is to find the optimum value for one or more target variables, given certain constraints

    • E.g., given various combinations of resources, what is the highest profit level we may achieve? What is the best ‘mix’ of these resources to maximize the net profit?

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Executive Information Systems

  • EIS

    • Combines many features of MIS and DSS

    • Provide top executives with immediate and easy access to information

    • Identify factors that are critical to accomplishing strategic objectives (critical success factors)

    • So popular that it has been expanded to managers, analysis, and other knowledge workers

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Features of an EIS

  • Information presented in forms tailored to the preferences of the executives using the system

    • Customizable graphical user interfaces

    • Exception reports

    • Trend analysis

    • Drill down capability

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AI and Intelligent Technologies

  • AI and Intelligent Technologies

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Artificial Intelligence (AI)

  • AI is a field of science and technology based on

    • Computer science

    • Biology

    • Psychology

    • Linguistics

    • Mathematics

    • Engineering

  • The goal is to develop computers than can simulate the ability to think

    • And see, hear, walk, talk, and feel as well

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Attributes of Intelligent Behavior

  • Some of the attributes of intelligent behavior

    • Think and reason

    • Use reason to solve problems

    • Learn or understand from experience

    • Acquire and apply knowledge

    • Exhibit creativity and imagination

    • Deal with complex or perplexing situations

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Attributes of Intelligent Behavior

  • Attributes of intelligent behavior (continued)

    • Respond quickly and successfully to new situations

    • Recognize the relative importance of elements in a situation

    • Handle ambiguous, incomplete, or erroneous information

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Cognitive Science

  • Focuses on how the human brain works and how humans think and learn

  • Applications in the cognitive science of AI

    • Expert systems

    • Knowledge-based systems

    • Adaptive learning systems

    • Fuzzy logic systems

    • Neural networks

    • Genetic algorithm software

    • Intelligent agents

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  • AI, engineering, and physiology are the basic disciplines of robotics

    • Produces robot machines with computer intelligence and humanlike physical capabilities

  • This area include applications designed to give robots the powers of

    • Sight or visual perception

    • Touch

    • Dexterity

    • Locomotion

    • Navigation

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Natural Interfaces

  • Major thrusts in the area of AI and the development of natural interfaces

    • Natural languages

    • Speech recognition

    • Virtual reality

  • Involves research and development in

    • Linguistics

    • Psychology

    • Computer science

    • Other disciplines

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Latest Commercial Applications of AI

  • Decision Support

    • Helps capture the why as well as the what of engineered design and decision making

  • Information Retrieval

    • Distills tidal waves of information into simple presentations

      • E.g., news agents

    • Natural language technology

    • Database mining

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Virtual Reality

  • Computer-simulated reality

  • Relies on multisensory input/output devices

    • Data gloves, walkers – monitor feet moves

  • Allows interaction with computer-simulated objects, entities, and environments in three dimensions

    • Used in virtual surgery, computer-aided design, flight simulation, military (combat training), entertainment, etc.

  • Very expensive in terms of hard- and software

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Latest Commercial Applications of AI

  • Robotics

    • Machine-vision inspections systems

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Intelligent Agents

  • A software entity that may possess some ‘intelligent’ characteristics

    • Sometimes called software agents or bots


  • Uses built-in and learned knowledge base about a person or process to make decisions and accomplish tasks

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Expert Systems

  • An Expert System (ES)

    • A knowledge-based information system

    • Contain knowledge about a specific, complex application area

    • Acts as an expert consultant to end users

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Components of an Expert System

  • Knowledge Base

    • Facts about a specific subject area

    • Heuristics that express the reasoning procedures of an expert (rules of thumb)

  • Software Resources

    • An inference engine processes the knowledge and recommends a course of action

    • User interface programs communicate with the end user

    • Explanation programs explain the reasoning process to the end user

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Developing Expert Systems

  • Begin with an expert system shell

    • Software system or development tool

  • Add the knowledge base

  • Built by a “knowledge engineer”

    • A professional who works with experts to capture their knowledge to build the expert system

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The Value of Expert Systems (continued)

  • Benefits

    • Can outperform a single human expert in many problem situations

    • Helps preserve and reproduce knowledge of experts

  • Limitations

    • Limited focus, inability to learn, maintenance problems, developmental costs

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Software Demos

  • Expert System

    • Alien Employee Visa Classification Wizard

    • Camcorder Selection Expert System

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Neural Networks

  • Computing systems modeled after the brain’s mesh-like network of interconnected processing elements (neurons)

    • Interconnected processors operate in parallel and interact with each other

    • Allows the network to learn from the data it processes

    • E.g., characteristics of real and fake customer online behavior in e-commerce

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Fuzzy Logic

  • Fuzzy logic

    • Resembles human reasoning

    • Allows for approximate values and inferences and incomplete or ambiguous data

    • Uses terms such as “very high” instead of precise measures

    • Used more often in Japan than in the U.S.

    • Used in fuzzy process controllers used in subway trains, elevators, and cars

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Genetic Algorithms

  • Uses Darwinian (survival of the fittest), randomizing, & other mathematical functions to simulate an evolutionary process that can yield increasingly better solutions

    • E.g., simulation of millions of years of evolution in a few minutes on a computer

  • Especially useful for situations in which thousands of solutions are possible & must be evaluated