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Supporting Business Decision-Making

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Title: Supporting Business Decision-Making


1
Supporting Business Decision-Making
  • Good Information is Essential for Fact-Based
    Decision-Making

2
The Importance of Knowledge
  • For centuries managers have used the knowledge
    available to them to make decisions
  • The amount of knowledge used to make decisions
    has increased exponentially
  • The Importance of Decision Making
  • Decisions today determine the landscape of
    tomorrow's world

3
Decision Making
  • The common thread that runs through all
    managerial functions
  • Decision a choice of one course of action from
    a number of alternatives leading to a certain
    desired objective

4
Classifying Decisions
  • Functional area
  • Finance decisions
  • Marketing decisions
  • Production decisions
  • Personnel decisions, etc.
  • Managerial Function
  • Planning decisions
  • Organizing decisions
  • Control decisions, etc.

5
Classifying Decisions
  • Management Level
  • Strategic decisions
  • Tactical decisions
  • Operational decisions
  • Structure of decision
  • Structured/Programmed decisions
  • Semi-structured decisions
  • Unstructured decisions

6
Decision Support System Definition
  • A decision Support System is an interactive
    computer-based system or subsystem that helps
    people use computer communications, data,
    documents, knowledge and models to identify and
    solve problems, complete decision process tasks,
    and make decision
  • DSS comprise a class of information system that
    draws on transaction processing systems and
    interacts with the other parts of the overall
    information system to support the decision-making
    activities of managers and other knowledge
    workers in organizations (Sprague and Carlson,
    1982, p. 9).
  • DSS are ancillary or auxiliary systems they are
    not intended to replace skilled decision-makers

Reference - Power (2008)
7
DSS Assumptions
  • Is good information and analysis essential for
    fact-based decision-making?
  • Build DSS when good information is likely to
    improve decision-making
  • Build DSS when managers need and want
    computerized decision support

Reference - Power (2008)
8
MIS and DSS Brief History
  • Late 1960s, MIS focused on providing structured,
    periodic reports
  • Late 1960s, first DSS built using interactive
    computer systems, Scott-Morton
  • 1975-1980 DSS using financial models with What
    if? analysis
  • 1975 Steve Alter MIT dissertation
  • 1979-1982 Theoretical foundations
  • Mid-1980s Executive Information Systems and GDSS
  • Early 1990s shift to client/server DSS, Business
    Intelligence, Bill Inmon and Ralph Kimball
  • 1995 Data warehousing, data mining and the
    world-wide web
  • 1998 Enterprise performance management and
    balanced scorecard
  • 2000 Application service providers (ASPs) and
    portals

Reference - Power (2008)
9
DSS History - Specifics
  • 1951 Lyons Tea Shops used LEO 1 digital computer
    to factor in weather forecasts to determine what
    fresh produce delivery vans would carry to
    Lyons UK shops
  • Later SAGE a control system for tracking aircraft
    used by NORAD from the 1950s to the early 1980s
    (real time control, communications)
  • Mid-1960s NLS first hypermedia groupware system
    was the forerunner to GDSS
  • 1965 more cost effective due to the IBM System
    360 and other more powerful mainframes and
    minicomputer systems
  • 1970s companies were implementing a variety of
    DSS
  • 1982 DSS considered a new class of IS
  • 1980s financial planning systems became popular
    What-if analysis
  • Mid-1980s DSS were supporting managers in
    operations, financial management, management
    control and strategic decision making (scope,
    purpose and targeted user base was expanding)
  • 1985 PG built a DSS that linked sales
    information and retail scanner data

Reference - Power (2008)
10
DSS Conceptual Perspective
  • DSS are both off-the-shelf, packaged application
    and custom designed systems.
  • Alter (1980)
  • Designed specifically to facilitate a decision
    process
  • Should support rather than automate decision
    making
  • Should be able to respond quickly to changing
    needs of decision makers
  • Business intelligence, knowledge management

Reference - Power (2008)
11
Characteristics of DSS
  • Body of knowledge
  • Record keeping
  • Provide structure for a particular decision
  • Decision maker interacts directly with DSS
  • Facilitation
  • Ancillary. Not intended to replace decision
    makers
  • Repeated used
  • Task-oriented
  • Identifiable
  • Decision impact. Improve accuracy, timeliness,
    quality and overall effectiveness of a specific
    decision or a set of related decision

Reference - Power (2008)
12
Characteristics of Decision Support Information
  • Right Information accurate, relevant and
    complete
  • Right Time current, timely information
  • Right Formation easy to understand and
    manipulate
  • Right Cost Cost/Benefit Trade-off

Reference - Power (2008)
13
Is a DSS an MIS?
  • MIS describe a broad, general category of
    information systems or a functional reporting
    system.
  • MIS is used to identify an academic major
  • Data-Driven DSS meet management reporting needs
  • Decision Support Systems is a broad category of
    interactive, analytical management information
    systems

Reference - Power (2008)
14
Transaction Processing
  • What is a transaction? A work task recorded by a
    data capture system. i.e., Purchase, order,
    payment
  • Record current information but does not maintain
    a database of historical information
  • Emphasize data integrity and consistency

Reference - Power (2008)
15
DSS vs. Transaction Processing Systems (TPS)
  • TPS is designed to expedite and automate
    transaction processing, record keeping, and
    business reporting
  • TPS is related to DSS because TPS provides data
    for reporting systems and data warehouses
  • DSS are designed to aid in decision-making tasks
    and/or decision implementation

Reference - Power (2008)
16
DSS Applications
  • Major airlines use DSS for many tasks including
    pricing and route selection
  • DSS aid in corporate planning and forecasting
  • Specialists use DSS that focus on financial and
    simulation models
  • Frito-Lay has a DSS that aids in pricing,
    advertising, and promotion
  • Monsanto, FedEx and most transportation companies
    use DSS for scheduling trucks, airplanes and ship
  • Wal-Mart has large data warehouses and data
    mining systems
  • There are many DSS on the Internet that help
    track and manage stock portfolios, choose stocks,
    plan trips, and suggest gifts

17
Alters Categories of DSS
  • Data-Driven
  • File Drawer Systems
  • Data Analysis Systems
  • Analysis Information Systems
  • Model-Driven
  • Accounting and Financial Models
  • Representational Models
  • Optimization Models
  • Knowledge-Driven
  • Suggestion Models

Reference - Power (2008)
18
Alters Categories of DSS
  • Data-Driven
  • File Drawer Systems
  • Data Analysis Systems
  • Analysis Information Systems

Reference - Power (2008)
19
Alters Categories of DSS
  • Model-Driven
  • Accounting and Financial Models
  • Representational Models
  • Optimization Models

Reference - Power (2008)
20
Alters Categories of DSS
  • Knowledge-Driven
  • Suggestion Models

Reference - Power (2008)
21
Framework
  • Primary framework dimension is the dominant
    component or driver of the decision support
    system (Power, 2002)
  • Secondary dimensions are
  • The intended or targeted users,
  • The specific purpose of the system
  • The primary deployment or enabling technology

Reference - Power (2008)
22
Identify the system component that provides
primary functionality ? dominant component
  • Communication technologies
  • Data and data management
  • Documents and document management
  • Knowledge base and processing
  • Models and model processing

Reference - Power (2008)
23
DSS Framework
  • Communications-driven DSS
  • Interactive computer-based systems intended to
    facilitate the solution of problems by
    decision-makers working as a group
  • Group DSS may be communications-driven or
    model-driven

Reference - Power (2008)
24
DSS Framework
  • Data-driven
  • Includes File Drawer/Management Reporting, Data
    Warehousing and Analysis Systems, Executive
    information Systems (EIS), and Geographic
    Information Systems external data
  • Emphasize access to and manipulation of large
    databases and especially a time-series of
    internal company data and sometimes external data
  • Document-driven DSS
  • Retrieve and manage unstructured documents and
    web pages

Reference - Power (2008)
25
DSS Framework
  • Knowledge-driven
  • Built using AI tools, data mining tools and
    management expert systems
  • Model-driven
  • Include systems that use accounting and financial
    models, representative models, and optimization
    models
  • Emphasize access to and manipulation of a model,
    Whit If? analysis

Reference - Power (2008)
26
DSS Framework
  • Intended Users, e.g. Inter-Organizational DSS
  • Designed for customers and suppliers
  • Data, model, document, knowledge, or
    communications-driven
  • Purpose, e.g. Function and Industry-Specific DSS
  • A DSS that is designed specifically for a narrow
    task
  • Specific rather than General purpose
  • Vertical Market/Industry-Specific

Reference - Power (2008)
27
Describing a Specific DSS
  • A web-based, model-driven DSS for truck routing
    used by a dispatcher
  • A handheld PC-based, knowledge-driven DSS for
    accident scene triage used by an EMT
  • A web-enabled, data-driven DSS for real-time
    performance monitoring used by a factory manager
  • A PC-based, model-driven DSS for planning supply
    chain activities used by logistics staff

Reference - Power (2008)
28
Enabling Technology
  • USE the Web to deliver and category of DSS
    Web-based DSS
  • Web-based, Communications-driven DSS
  • Web-based, Data-driven DSS
  • Web-based, Document-driven DSS
  • Web-based, Knowledge-driven DSS
  • Web-based, Model-driven DSS

Reference - Power (2008)
29
Building DSS - components
  • Database Component
  • Knowledge
  • Data
  • Documents
  • Model Component
  • Interface Engine
  • Models
  • External Data
  • Dow Jones
  • Reuters
  • Communications Component
  • DSS Architecture
  • Network
  • Web server
  • Client/Server
  • Mainframe
  • Internal Data
  • Personnel
  • Production
  • Finance
  • Marketing
  • User Interface Component
  • Dialog
  • Maps
  • Menus, Icons
  • Representations
  • Charts, graphs
  • Web Browser

Users
Reference - Power (2008)
30
Building DSS User Interface
  • User Interface
  • Most Important Component
  • Tools needed
  • DSS Generator
  • Query Reporting Tools
  • Front-End Development Packages

Reference - Power (2008)
31
Building DSS Database
  • Database
  • Collection of current and historical data from a
    number of sources
  • Large databases are called data warehouses or
    data marts
  • Size of data warehouses are discussed in terms of
    multiple Terabytes (TB)

Reference - Power (2008)
32
Building DSS Models
  • Mathematical and Analytical Tools
  • Used and manipulated by managers
  • Each Model-driven DSS has a specific purpose
  • Values of key variables and parameters are
    frequently changed What IF? analysis

Reference - Power (2008)
33
Building DSS Architecture
  • DSS Architecture and Networking
  • How hardware is organized
  • How software and data are distributed and
    organized
  • How components of the system are integrated and
    connected
  • Communications component

Reference - Power (2008)
34
Challenges of DSS
  • Rapid technology change
  • Managers as users and customers
  • Major issues
  • What to computerize?
  • What data? Source?
  • What processing and presentation?
  • Are current DSS results decision-impelling?
  • What technology for a new DSS?

Reference - Power (2008)
35
Gaining Competitive Advantage
  • DSS can create a Competitive Advantage if the
    following 3 criteria are met
  • Must be a major or significant strength or
    capability of the organization
  • DSS must be unique and proprietary to the
    organization
  • DSS must be sustainable for approximately 3 years

36
How can DSS provide a competitive advantage?
  • Internet technologies have opened doors for
    innovative Web-based DSS
  • Inter-organizational DSS can improve linkages
    with customers and suppliers
  • Increasing efficiency and eliminate staff and
    activities, cost advantage
  • New products and services, differentiation

37
How can DSS provide a competitive advantage?
  • Communications-Driven DSS can remove time and
    location barriers
  • Increase focus on specific customer segments
  • Better fact-based decision-making
  • Decrease decision cycle time

38
Strategic DSS Examples
  • Frito-Lay
  • L.L. Bean
  • Lockheed - Georgia
  • Mrs. Fields Cookies
  • Wal-Mart
  • A company needs to continually invest in a
    Strategic DSS to maintain any advantage.

Classic examples!!
Reference - Power (2008)
39
Frito-Lay
  • Route Sales people were all given a hand-held
    computer
  • Enables sales people to have decision-making role
  • Allows Frito-Lay to track products
  • The data is put into a Data-Driven DSS
  • Automated a cumbersome process and improved the
    quality of data

Reference - Power (2008)
40
L.L. Bean
  • Consultants hired to design a system that would
    provide better allocation of resources in
    telemarketing
  • Economic Optimization Model System (EOM)
  • This Model-Driven DSS examined variables such as
    the number of telephone lines to carry incoming
    traffic, number of agents, and the queue capacity
  • System generates specific resource amounts the
    company should deploy to be most economically
    advantageous

Reference - Power (2008)
41
Mrs. Fields Cookies
  • Developed MIS in early 1980s to provide
    uniformity in store management also supporting
    rapid expansion
  • Designed to serve two purposes
  • Control and better management decision-making
  • Enabled each store to be run as Debbie Field ran
    the original store

Reference - Power (2008)
42
Mrs. Fields Cookies
  • Knowledge-Driven DSS developed that automated
    routine activities and responded to exceptions by
    prompting the store manager for input
  • Tracked financial performance of each store,
    provided comprehensive scheduling of operations,
    including market support, hourly sales goals, and
    assisted with candidate interview selection

Reference - Power (2008)
43
Wal-Mart
  • Creates a competitive advantage that other
    retailers have tried to mimic but have not
    duplicated
  • Result of Retail Link and FAR
  • Less inventory in stores, more inventory of the
    right products at the right time and place, and
    improved revenues for both supplier and retailer
  • Collaborative Forecasting and Replenishment
    Initiative (CFAR)
  • Evaluating ways to apply wireless technology in
    stores. Testing emerging RFID smart-tag systems,
    to replace bar codes with a more efficient
    product-tracking mechanism.

Reference - Power (2008)
44
Advanced Scout
  • IBM has prototyped software to help National
    Basketball Association (NBA) coaches and league
    officials organize and interpret the data
    collected at every game. Using software called
    Advanced Scout to prepare for a game, a coach can
    quickly review countless stats shots attempted,
    shots blocked, assists made, personal fouls. But
    Advanced Scout can also detect patterns in these
    statistics that a coach may not have known about.
    Advanced Scout software provides an easy and
    meaningful way to process information. "It helps
    coaches easily mine through and analyze a lot of
    data and no computer training or data analysis
    background is required," says Dr. Inderpal
    Bhandari, computer scientist at IBM's T.J. Watson
    Research Center. Patterns found through analysis
    are linked to the video of the game. Coaches can
    look at just those clips that make up an
    interesting pattern.

45
FedEx Business Intelligence System
  • Federal Express, based in Memphis, Tenn., rolled
    out Business Intelligence capabilities to a
    global base of 700 end-users. FedEx created a
    central, integrated data warehouse hub, which
    provides Web-based, real-time access to financial
    and logistical information necessary for planning
    and decision-making. The solution, from Pinnacle
    Solutions Inc., was deployed on a group of Dell
    PowerEdge servers running Windows NT Server 4.0.
    Data is stored in an Oracle database, and
    analytical queries are run against a separate
    server running Hyperion Essbase, an online
    analytical processing (OLAP) engine. Most access
    is from browsers over the corporate intranet,
    along with some standard client/server
    deployments using Excel spreadsheets.

46
DSS Benefits
  • Improve personal efficiency
  • Expedite problem solving and improve decision
    quality
  • Facilitate interpersonal communication
  • Promote learning or training
  • Increase organizational control

Reference - Power (2008)
47
Other DSS Benefits
  • Extending decision-makers ability to process
    information and analyze it
  • Helping decision-makers deal with complex,
    large-scale problems
  • Decreasing the amount of time needed to make a
    decision, reducing the decision cycle
  • Improving the reliability and enforcing the
    structure of a decision process
  • Encouraging exploration and discovery by the
    decision-maker in less structured or more novel
    decision situations related to the domain or
    scope of the DSS
  • Creating a competitive or strategic advantage for
    an organization.

Some DSS development opportunities are better
than others.
Reference - Power (2008)
48
Risks
  • Gaining any advantage may require large financial
    investments
  • Competitors responses may result in a heated
    race to gain or regain market share
  • Technology risks include
  • Picking the wrong vendor, using new technology
    too early in technology life cycle, and using a
    technology that might soon become obsolete

Reference - Power (2008)
49
Risks
  • People cause the greatest risk
  • Inability to predict human behaviors and
    reactions
  • Basic human instinct to resist change
  • Power struggles
  • Personal motives
  • No matter how wonderful a proposed DSS, if
    people resist the change the system fails

Reference - Power (2008)
50
Questions for Further Thought
  • Do managers need the support provided by DSS?
  • Do managers want to use DSS?
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