Management Information System

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Management Information System
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• Decision Support System

Judi Prajetno Sugiono jpsugiono_at_gmail.com (2008)
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Learning Objectives

• Identify the changes taking place in the form and
  use of decision support in e-business
  enterprises.
• Identify the role and reporting alternatives of
  management information systems.

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Learning Objectives (continued)

• Describe how online analytical processing can
  meet key information needs of managers.
• Explain the decision support system concept and
  how it differs from traditional management
  information systems.

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Learning Objectives (continued)

• Explain how the following information systems can
  support the information needs of executives,
  managers, and business professionals
• Executive information systems
• Enterprise information portals
• Enterprise knowledge portals

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Learning Objectives (continued)

• Identify how neural networks, fuzzy logic,
  genetic algorithms, virtual reality, and
  intelligent agents can be used in business.
• How can expert systems be used in business
  decision-making situations?

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Section I

• Decision Support in Business

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Business and Decision Support

• To succeed, companies need information systems
  that can support the diverse information and
  decision-making needs of their managers and
  business professionals.

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Business and Decision Support (continued)

• Information, Decisions, Management
• The type of information required by decision
  makers is directly related to the level of
  management and the amount of structure in the
  decision situations.

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Business and Decision Support (continued)
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Business and Decision Support (continued)

• Information Quality
• Timeliness
• Provided WHEN it is needed
• Up-to-date when it is provided
• Provided as often as needed
• Provided about past, present, and future time
  periods as necessary

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Business and Decision Support (continued)

• Information Quality (continued)
• Content
• Free from errors
• Should be related to the information needs of a
  specific recipient for a specific situation
• Provide all the information that is needed
• Only the information that is needed should be
  provided
• Can have a broad or narrow scope, or an internal
  or external focus
• Can reveal performance

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Business and Decision Support (continued)

• Information Quality (continued)
• Form
• Provided in a form that is easy to understand
• Can be provided in detail or summary form
• Can be arranged in a predetermined sequence
• Can be presented in narrative, numeric, graphic,
  or other forms
• Can be provided in hard copy, video, or other
  media.

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Business and Decision Support (continued)
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Business and Decision Support (continued)

• Decision Structure
• Structured decisions
• Involve situations where the procedures to be
  followed can be specified in advance
• Unstructured decisions
• Involve situations where it is not possible to
  specify most of the decision procedures in advance

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Business and Decision Support (continued)

• Decision structure (continued)
• Semistructured decisions
• Some decision procedures can be specified in
  advance, but not enough to lead to a definite
  recommended decision

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Business and Decision Support (continued)

• Amount of structure is typically tied to
  management level
• Operational more structured
• Tactical more semistructured
• Strategic more unstructured

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Decision Support Trends

• The growth of corporate intranets, extranets and
  the Web has accelerated the development and use
  of executive class information delivery
  decision support software tools to virtually
  every level of the organization.

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Management Information Systems

• The original type of information system
• Produces many of the products that support
  day-to-day decision-making
• These information products typically take the
  following forms
• Periodic scheduled reports
• Exception reports
• Demand reports and responses
• Push reports

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Management Information Systems (continued)

• Management reporting alternatives
• Periodic scheduled reports
• Prespecified format
• Provided on a scheduled basis
• Exception reports
• Produced only when exceptional conditions occur
• Reduces information overload

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Management Information Systems (continued)

• Management reporting alternatives (continued)
• Demand reports and responses
• Available when demanded.
• Ad hoc
• Push reports
• Information is sent to a networked PC over the
  corporate intranet.
• Not specifically requested by the recipient

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Online Analytical Processing

• Enables managers and analysts to interactively
  examine manipulate large amounts of detailed
  and consolidated data from many perspectives
• Analyze complex relationships to discover
  patterns, trends, and exception conditions
• Real-time

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Online Analytical Processing (continued)

• Involves..
• Consolidation
• The aggregation of data.
• From simple roll-ups to complex groupings of
  interrelated data
• Drill-Down
• Display detail data that comprise consolidated
  data

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Online Analytical Processing (continued)

• Slicing and Dicing
• The ability to look at the database from
  different viewpoints.
• When performed along a time axis, helps analyze
  trends and find patterns

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Decision Support Systems

• Computer-based information systems that provide
  interactive information support during the
  decision-making process
• DSSs use
• Analytical models
• Specialized databases
• The decision makers insights judgments
• An interactive, computer-based modeling process
  to support making semistructured and unstructured
  business decisions

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Decision Support Systems (continued)

• Designed to be ad hoc, quick-response systems
  that are initiated and controlled by the decision
  maker
• DSS Models and Software
• Rely on model bases as well as databases
• Might include models and analytical techniques
  used to express complex relationships

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Decision Support Systems (continued)

• DSS models and software (continued)
• Can combine model components to create integrated
  models in support of specific types of business
  decisions

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Decision Support Systems (continued)

• Geographic Information Data Visualization
  Systems
• Special categories of DSS that integrate computer
  graphics with other DSS features
• GIS
• A DSS that uses geographic databases to construct
  and display maps and other graphics displays

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Decision Support Systems (continued)

• Geographic information and data visualization
  systems (continued)
• Data visualization systems
• Represent complex data using interactive
  three-dimensional graphic forms
• Helps discover patterns, links, and anomalies

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Using Decision Support Systems

• An interactive modeling process
• Four types of analytical modeling
• What-if analysis
• Sensitivity analysis
• Goal-seeking analysis
• Optimization analysis

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Using Decision Support Systems (continued)

• What-If Analysis
• End user makes changes to variables, or
  relationships among variables, and observes the
  resulting changes in the values of other variables

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Using Decision Support Systems (continued)

• Sensitivity Analysis
• A special case of what-if 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

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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

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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

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Contoh PT. INDAH GELAS

• PT Indah Gelas adalah suatu perusahaan yang
  memproduksi kaca berkualitas tinggi untuk
  digunakan sebagai jendela dan pintu kaca.
  Perusahaan ini memiliki tiga buah 'pabrik, yaitu
  pabrik 1 yang membuat bingkai aluminium, pabrik 2
  yang membuat bingkai kayu, dan pabrik 3 yang
  digunakan untuk memproduksi kaca dan merakit
  produk keseluruhan. Saat ini perusahaan mendapat
  pesanan berupa dua macam produk baru yang
  potensial, yaitu pintu kaca setinggi 8 kaki
  dengan bingkai aluminium (produk 1), dan jendela
  berukuran 4 x 6 kaki dengan bingkai kayu (produk
  2).

Produk Pabrik Kapasitas yang digunakan per unit ukuran produksi Kapasitas yang digunakan per unit ukuran produksi Kapasitas maks
Produk Pabrik 1 2 Kapasitas maks
1 1 0 4
2 0 2 12
3 3 2 18
Keuntungan 3 5
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• Goal
• Max. Profit z3x15x2
• Criterion
• x1lt4
• 2X2lt12
• 3x15x2lt18
• x1gt0
• X2gt0

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Decision Making Under Risk
Plant State of Nature State of Nature
Plant Wet P(W)0.6 Dry P(D)0.4
Lettuce 100 25
Tomatoes 80 50
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Decision Tree
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Expected Value of Imperfect Information

• Consider an imperfect source of information with
  a prediction record as shown in the table.
• In the past 100 seasons of which 60 wet (W) and
  40 dry (D), the source predicted a total of 46
  wet seasons (w) of which 42 were wet (W) and 4
  were dry (D). Of the 54 prediction of dry (d), 36
  were dry (D) and 18 were wet (W).

Actual State Actual State
W D
Prediction w 42 4 46
Prediction d 18 36 54
60 40
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Example Investment
Investment Alternatives Prospectus Prospectus
Investment Alternatives Good P(C)0.6 Bad P(L)0.4
A 50 -10
B 15 60
C 100 10

• Additional Information
• P(OC)0.8 P(OL)0.1 Ooptimistic
• P(PC)0.2 P(PL)0.9 Ppessimistic

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Using Decision Support Systems (continued)

• Data Mining for Decision Support
• Software analyzes vast amounts of data
• Attempts to discover patterns, trends,
  correlations
• May perform regression, decision tree, neural
  network, cluster detection, or market basket
  analysis

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Executive Information Systems

• EISs combine many of the features of MIS and DSS
• Originally intended to provide top executives
  with immediate, easy access to information about
  the firms critical success factors
• Alternative names
• Enterprise information systems
• Executive support systems

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Executive Information Systems (continued)

• Features of an EIS
• Information presented in forms tailored to the
  preferences of the users
• Most stress use of graphical user interface and
  graphics displays
• May also include exception reporting and trend
  analysis

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Enterprise Portals and Decision Support

• A Web-based interface and integration of intranet
  and other technologies that gives all intranet
  users and selected extranet users access to a
  variety of internal external business
  applications and services

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Enterprise Portals and Decision Support
(continued)

• Business benefits
• More specific and selective information
• Easy access to key corporate intranet website
  resources
• Industry and business news
• Access to company data for stakeholders
• Less time spent on unproductive surfing

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Knowledge Management Systems

• IT that helps gather, organize, and share
  business knowledge within an organization
• Hypermedia databases that store and disseminate
  business knowledge. May also be called knowledge
  bases
• Best practices, policies, business solutions
• Entered through the enterprise knowledge portal

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Section II

• Artificial Intelligence Technologies in Business

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Business and AI

• Designed to leverage the capabilities of humans
  rather than replace them,AI technology enables
  an extraordinary array of applications that forge
  new connections among people, computers,
  knowledge, and the physical world.

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Artificial Intelligence

• A field of science and technology based on
  disciplines such as computer science, biology,
  psychology, linguistics, mathematics,
  engineering
• Goal is to develop computers that can think, see,
  hear, walk, talk, and feel
• Major thrust development of computer functions
  normally associated with human intelligence
  reasoning, learning, problem solving

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Artificial Intelligence (continued)

• Domains of AI
• Three major areas
• Cognitive science
• Robotics
• Natural interfaces

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Artificial Intelligence (continued)

• Cognitive science
• Focuses on researching how the human brain works
  how humans think and learn
• Applications
• Expert systems
• Adaptive learning systems
• Fuzzy logic systems
• Neural networks
• Intelligent agents

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Artificial Intelligence (continued)

• Robotics
• Produces robot machines with computer
  intelligence and computer controlled, humanlike
  physical capabilities
• Natural interfaces
• Natural language and speech recognition
• Talking to a computer and having it understand
• Virtual reality

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Neural Networks

• Computing systems modeled after the brains
  meshlike network of interconnected processing
  elements, called neurons
• Goal the neural network learns from data it
  processes

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Fuzzy Logic Systems

• A method of reasoning that resembles human
  reasoning
• Allows for approximate values and inferences
• Allows for incomplete or ambiguous data
• Allows fuzzy systems to process incomplete data
  and provide approximate, but acceptable,
  solutions to problems

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Genetic Algorithms

• Uses Darwinian, randomizing, other mathematical
  functions to simulate an evolutionary process
  that can yield increasingly better solutions
• Especially useful for situations in which
  thousands of solutions are possible must be
  evaluated

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Virtual Reality

• Computer-simulated reality
• Relies on multisensory input/output devices
• Allows interaction with computer-simulated
  objects, entities, and environments in three
  dimensions

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Intelligent Agents

• A software surrogate for an end user or a
  process that fulfills a stated need or activity
• Uses built-in and learned knowledge base about a
  person or process to make decisions and
  accomplish tasks

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Expert Systems

• A knowledge-based information system that uses
  its knowledge about a specific, complex
  application area to act as an expert consultant
• Provides answers to questions in a very specific
  problem area
• Must be able to explain reasoning process and
  conclusions to the user

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Expert Systems (continued)

• Components
• Knowledge base
• Software resources

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Expert Systems (continued)

• Knowledge base
• Contains
• Facts about a specific subject area
• Heuristics that express the reasoning procedures
  of an expert on the subject

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Expert Systems (continued)

• Software Resources
• Contains an inference engine and other programs
  for refining knowledge and communicating
• Inference engine processes the knowledge, and
  makes associations and inferences
• User interface programs, including an explanation
  program, allows communication with user

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Developing Expert Systems

• Begin with an expert system shell
• Add the knowledge base
• Built by a knowledge engineer
• Works with experts to capture their knowledge
• Works with domain experts to build the expert
  system

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The Value of Expert Systems
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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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Discussion Questions

• Is the form and use of information and decision
  support in e-business changing and expanding?
• Has the growth of self-directed teams to manage
  work in organizations changed the need for
  strategic, tactical, and operational decision
  making in business?

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Discussion Questions (continued)

• What is the difference between the ability of a
  manager to retrieve information instantly on
  demand using an MIS and the capabilities provided
  by a DSS?
• In what ways does using an electronic spreadsheet
  package provide you with the capabilities of a
  decision support system?

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Discussion Questions (continued)

• Are enterprise information portals making
  executive information systems unnecessary?
• Can computers think? Will they EVER be able to?

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Discussion Questions (continued)

• What are some of the most important applications
  of AI in business?
• What are some of the limitations or dangers you
  see in the use of AI technologies such as expert
  systems, virtual reality, and intelligent agents?
  What could be done to minimize such effects?

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Real World Case 1 AmeriKing Others

• AmeriKings old system
• Relied on an antiquated corporate information
  system.
• Involved mailing or faxing paper reports to
  managers.
• AmeriKings new system
• An intranet-based enterprise information portal
• Enables employees to use Web browsers to
  instantly access financial, marketing, human
  resource, and other reports.

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Real World Case 1 (continued)

• What is the business value to a company of an
  enterprise portal like AmeriKings?
• What are several ways AmeriKing could improve the
  business value of its portal?

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Real World Case 1 (continued)

• How might an enterprise portal help you as a
  business professional or manager in your work
  activities?
• Is it becoming necessary for all companies to
  provide an enterprise information portal to their
  employees?

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Real World Case 2 BAE Systems

• Problems
• Wasted time trying to find information to do the
  job.
• Duplication of effort
• Information overload
• Inadequate search capability
• Solution
• An intranet-based knowledge management system

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Real World Case 2 (continued)

• What problems was BAE having in knowledge
  sharing? Are such problems common to many
  companies?
• How does BAEs knowledge management system help
  solve such problems?

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Real World Case 2 (continued)

• What are some of the business benefits and
  potential limitations of BAEs knowledge
  management system?
• What is the difference between a corporate
  intranet and a knowledge management system? What
  is the difference in their business value?

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Real World Case 3 Cisco Systems, NetFlix,
Office Depot

• What are the business benefits and limitations of
  Ciscos Web-based system for its channel
  managers?
• Do you agree that NetFlixs real-time
  personalization system is critical to their
  success?

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Real World Case 3 (continued)

• Do you think salespeople will appreciate and
  benefit from the real-time alert system
  envisioned for Office Depot?

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Real World Case 4 Producers Assistance,
Kinkos, Champion Printing

• Using Spatial Information Systems to
• Find workers
• Find services
• Find customers

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Real World Case 4 (continued)

• What is the business value of spatial information
  systems?
• How else could spatial information systems be
  used in business?

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Real World Case 4 (continued)

• How helpful is Kinkos location finder service?
  What else can they do to improve this spatial
  information management application?

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Real World Case 5 Schneider National

• The business value of business intelligence (BI)
• We were drowning in data but starving for
  information.

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Real World Case 5 (continued)

• What problem was Schneider National having with
  their business data?
• How did business intelligence solve the problem?

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Real World Case 5 (continued)

• What are the benefits and limitations of business
  intelligence software as demonstrated by
  Schneider National?
• What is the business value of business
  intelligence as defined by Cognos?