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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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agenda
Agenda
  • Warriors - video (10 mins)
  • Telecommunication trends
  • The Internet, Intranet, Extranet
basic components of a network model
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
internet networking technologies
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
open systems
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
middleware
Middleware
  • 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
digital network technologies
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
the internet revolution
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
internet2
Internet2
  • 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
internet service providers
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
extranets
Extranets
  • 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
telecommunications network knowledge
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
enterprise systems
Enterprise Systems

Enterprise Systems

agenda19
Agenda
  • 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
cross functional enterprise applications
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
cross functional systems
Cross-Functional Systems
  • Cross the boundaries of traditional business functions
    • Used to reengineer and improve vital business processes all across the enterprise
enterprise application architecture23
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
enterprise application architecture24
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
enterprise application integration
Enterprise Application Integration
  • EAI software connects cross-functional systems
  • Serves as middleware to provide
    • Data conversion
    • Communication between systems
    • Access to system interfaces
transaction processing systems
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
enterprise collaboration systems ecs
Enterprise Collaboration Systems (ECS)
  • EC systems are cross-functional information systems that enhance team and workgroup
    • Communication
    • Coordination
    • Collaboration
  • MS SharePoint
enterprise collaboration systems
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
enterprise collaboration systems30
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
functional business systems
Functional Business Systems
  • A variety of types of information systems that support the business functions of
    • Accounting
    • Finance
    • Marketing
    • Operations management
    • Human resource management
customer relationship management
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
what is crm
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
contact and account management
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
sales
Sales
  • 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
marketing and fulfillment
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
customer service and support
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
retention and loyalty programs
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
retention and loyalty programs43
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
benefits of crm
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
crm failures
CRM Failures
  • Business benefits of CRM are not guaranteed
    • 50 percent of CRM projects did not produce promised results
    • 20 percent damaged customer relationships
crm failures46
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
crm examples
CRM Examples
  • Examples of CRM applications
    • MS Dynamics CRM - Video
erp the business backbone
ERP: The Business Backbone
  • ERP is a cross-functional enterprise backbone that integrates and automates processes within
    • Manufacturing
    • Logistics
    • Distribution
    • Accounting
    • Finance
    • Human resources
what is erp
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
enterprise resource planning continued
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
benefits and challenges of erp
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
causes of erp failures
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
erp demo
ERP Demo
  • SAP Business One Video
slide56
DSS
  • DSS in Business
  • AI and Intelligent Agent Technologies
decision structure
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
dss model base
DSS Model Base
  • Model Base
    • A software component that consists of models used in computational and analytical routines that mathematically express relations among variables
applications of statistics and modeling
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
using decision support systems
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
using decision support systems64
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
using decision support systems continued
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.
using decision support systems continued66
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
using decision support systems continued67
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?
executive information systems
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
features of an eis
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
ai and intelligent technologies
AI and Intelligent Technologies
  • AI and Intelligent Technologies
artificial intelligence ai
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
attributes of intelligent behavior
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
attributes of intelligent behavior73
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
cognitive science
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
robotics
Robotics
  • 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
natural interfaces
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
latest commercial applications of ai
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
virtual reality
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
latest commercial applications of ai80
Latest Commercial Applications of AI
  • Robotics
    • Machine-vision inspections systems
intelligent agents
Intelligent Agents
  • A software entity that may possess some ‘intelligent’ characteristics
    • Sometimes called software agents or bots
      • http://www.botspot.com
  • Uses built-in and learned knowledge base about a person or process to make decisions and accomplish tasks
expert systems
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
components of an expert system
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
developing expert systems
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
the value of expert systems continued
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
software demos
Software Demos
  • Expert System
    • Alien Employee Visa Classification Wizard
    • Camcorder Selection Expert System
neural networks
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
fuzzy logic
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
genetic algorithms
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
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