DECISION SUPPORT SYSTEMS AND BUSINESS INTELLIGENCE

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Chapter 1
Skip subsections 1.1, 1.2, 1.8, 1.10

• DECISION SUPPORT SYSTEMS AND BUSINESS
  INTELLIGENCE

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I. DSS Definitions

• System
• Information System
• Decision System
• Support System

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Decisions, decisions, ...

• When do you know, you have to make a decision?
• How will you go about making the decision?
• Why is that intuition and trialerror approaches
  to managerial decisions may not be effective in
  todays business environment?
• What are some of the tools that can be helpful in
  making a decision?

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DSS Definitions

• No universally accepted definition in literature
• DSS couples the intellectual resources of
  individuals with the capabilities of the computer
  to improve the quality of decisions. Keen
• DSS are interactive computer-based systems that
  help decision makers utilize data and models to
  solve unstructured problems. Sprague Carlson
• An interactive, flexible, and adaptable
  computer-based information system, especially
  developed for supporting the solution of a
  non-structured management problem for improved
  decision making. It utilizes data, provides an
  easy-to-use interface, and allows for the
  decision makers own insights. - Turban

Thus, DSS is a multi-disciplinary topic
covering Database research, AI, human-computer
interaction, management science modeling,
software engineering and telecommunications!
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Benefits of DSS

• Overcoming cognitive limits in processing and
  storing information
• Utilize internal and external data
• Uses robust mathematical/AI models
• Helps understand the problem better
• Speedy computations
• Leads to consistent decisions
• Useful in crisis
• Improved communication and collaboration

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Business as a decision-making entity

• What are the types of managerial control
  activities?
• What are the types of decisions?

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Decision Characteristics

• Managerial control activities
• Strategic planning rare, long-term
• Management control periodic, course corrections
• Operational control highly repetitive, brings
  revenue, short-term
• Types of decisions
• Structured algorithmic, programmable
• Unstructured subjective, vague problem space
• Semistructured combination of above

• For
• Structured decisions, use MIS/TPS
• Semi-structured Unstructured decisions, use DSS

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Gorry Scott-Morton Framework of DSS
Which of the cells has the most computer systems
in use today? Why? Any more example decisions
for cells 1-9?
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Supporting Managerial Roles

• What are some of the roles managers play in
  their job?
• Question
• You are a Public Relations manager for your
  company.
• In what ways can a DSS help you?

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Supporting Managerial Roles The challenge for DSS

• Managerial roles (Mintzberg)
• Interpersonal
• Informational
• Decisional

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Question How can a computer-based DSS assist a
manager in each of these roles?
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Supporting Decision Styles Another challenge for
DSS

• Decision style
• The manner in which a decision maker thinks and
  reacts to problems. It includes perceptions,
  cognitive responses, and beliefs
• Analytic vs. Intuitive
• Autocratic vs, Democratic
• Consultative
• Cooperative vs. Non-cooperative

What characteristics a DSS should have to support
each of these styles?
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Components of DSS
Network
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Automated Decision Systems (ADS)

• Typically, a DSS requires user interaction.
• - However, if the Knowledge component is complete
  (eg. all managers decision rules / models are
  known), a DSS may be use AI to implement (not
  just recommend) solutions directly without user
  intervention
• - Useful in repetitive decisions
• (such as program trading, approving a loan online)

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DSS Classifications

• Model-driven DSS quantitative models
  (statistical, financial, optimization,
  simulation) used to generate a recommended
  solution to a problem
• Data-driven DSS support ad-hoc reporting and
  queries on internal external database
• Communication-driven multiple users, support
  shared tasks, either cooperative or hostile mode
• Knowledge-driven qualitative models uses stored
  rules (Expert Sys Mining)
• Document-driven search, retrieve, analyze,
  classify text documents (eg. Law firms use it to
  create a case)

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II. Business Intelligence

• Companies collect a large amount of data from
  their business operations.
• To keep track of that information, a business
  uses disparate software applications , such as
  Excel, Access, etc.
• Using multiple software makes it difficult to
  retrieve information in a timely manner and to
  perform analysis of the data.
• Business Intelligence (BI) represents the tools
  and systems that play a key role in integrating
  and analyzing all corporate data.
• Generally illustrates intelligence in the areas
  of customer profiling, market research, product
  profitability (by product, region, year), etc.

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BI ? Custom reports

• Dashboard reports
• Production reports

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Analytic Reports (slice dice)
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Sources of BI
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BI Architecture

• Consists of 3 system components
• Data warehouse
• Business analytics
• Performance management (BPM)

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A Framework for Business Intelligence (BI)
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Data warehouse

• A repository of cleaned and integrated historical
  /stable data for the entire business
• Extracted from independent databases (internal
  external)
• Transformed (ie. cleaned and reformatted)
• - A subset of a warehouse limited to a business
  function is called a Data Mart (eg. Sales).

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DW vs. Transaction DBs

• DWs are not designed for performing transaction
  entries, but only for planning and analysis
• DWs are not designed for retrieval of individual
  records emphasis is on summarized data
• DWs data pulled and integrated from disparate
  databases, unlike Transaction dbs which are
  individual applications
• Transaction dbs are concerned with now DW
  focuses on activity over a period
• A transaction db is volatile (eg. an order may be
  cancelled) In a DW, data is only added, never
  deleted (as it maintains a history)
• Transaction db is optimized for rapid retrieval
  not DWs

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Business analytics
These are tools that help analyze the data
towards finding solutions

• Reporting and queries (eg. 3-dimensional cubes)
• Advanced analytics (LP, financial, stat,
  simulation models)
• Data, text and Web mining and other sophisticated
  mathematical and statistical tools (searching for
  relationships)

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Business performance management (BPM)

• An advanced performance measurement and analysis
  approach that embraces planning and strategy
• BPM extends the monitoring, measuring, and
  comparing of sales, profit, cost, profitability,
  and other performance indicators
• BPM provides a top-down enforcement of
  corporate-wide strategy