Enhancing Management Decision-making For The Digital Firm

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Enhancing Management Decision-making For The
Digital Firm
Chapter
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Objectives

• How can information systems help individual
  managers make better decisions when the problems
  are non-routine and constantly changing?
• How can information systems help people working
  in a group make decisions more efficiently?

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Objectives

• Are there any special systems that can facilitate
  decision-making among senior managers? Exactly
  what can these systems do to help high-level
  management?
• What benefits can systems that support management
  decision-making provide for the organization as a
  whole?

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Management Challenges

• Building information systems that can actually
  fulfill executive information requirements
• Create meaningful reporting and management
  decision-making processes

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Decision-Support Systems (DSS)

• Computer system at the management level of an
  organization
• Combines data, analytical tools, and models
• Supports semi-structured and unstructured
  decision-making

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Systems and Technologies for Business Intelligence
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Decision-Making Levels

• Senior management
• Middle management and project teams
• Operational management and project teams
• Individual employees

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Types of Decisions

• Unstructured decisions
• Novel, non-routine decisions requiring judgment
  and insights
• Examples Approve capital budget decide
  corporate objectives

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• Structured decisions
• Routine decisions with definite procedures
• Examples Restock inventory determine special
  offers to customers
• Semistructured decisions
• Only part of decision has clear-cut answers
  provided by accepted procedures
• Examples Allocate resources to managers develop
  a marketing plan

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Information Requirements of Key Decision-Making
Groups in a Firm
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Systems for Decision Support

• There are four kinds of systems that support the
  different levels and types of decisions
• Management Information Systems (MIS)
• Decision-Support Systems (DSS)
• Executive Support Systems (ESS)
• Group Decision-Support Systems (GDSS)

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Decision Making in the Real World

• In the real world, investments in
  decision-support systems do not always work
  because of
• Information quality Accuracy, integrity,
  consistency, completeness, validity, timeliness,
  accessibility
• Management filters Biases and bad decisions of
  managers
• Organizational inertia Strong forces within
  organization that resist change

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Trends in Decision Support and Business
Intelligence

• Detailed enterprise-wide data
• Broadening decision rights and responsibilities
• Intranets and portals
• Personalization and customization of information
• Extranets and collaborative commerce
• Team support tools

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Stages in Decision Making
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Management Information Systems

• Primarily address structured problems
• Provides typically fixed, scheduled reports based
  on routine flows of data and assists in the
  general control of the business

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DSS

• Support semistructured and unstructured problems
• Greater emphasis on models, assumptions, ad-hoc
  queries, display graphics
• Emphasizes change, flexibility, and a rapid
  response

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Types of Decision-Support Systems

• Model-driven DSS
• Primarily stand-alone systems
• Use a strong theory or model to perform what-if
  and similar analyses

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Types of Decision-Support Systems

• Data-driven DSS
• Integrated with large pools of data in major
  enterprise systems and Web sites
• Support decision making by enabling user to
  extract useful information
• Data mining Can obtain types of information such
  as associations, sequences, classifications,
  clusters, and forecasts

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Overview of a Decision-Support System (DSS)
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Components of DSS

• DSS database A collection of current or
  historical data from a number of applications or
  groups
• DSS software system Contains the software tools
  for data analysis, with models, data mining, and
  other analytical tools
• DSS user interface Graphical, flexible
  interaction between users of the system and the
  DSS software tools

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Model

• An abstract representation that illustrates the
  components or relationships of a phenomenon
• Statistical models
• Optimization models
• Forecasting models
• Sensitivity analysis Models that ask what-if
  questions repeatedly to determine the impact of
  changes in one or more factors on the outcomes

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Sensitivity Analysis
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Decision-Support Systems (DSS)

• Associations Occurrences linked to a single
  event
• Sequences Events linked over time

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Decision-Support Systems (DSS)

• Classification Recognizing patterns that
  describe the group to which an item belongs
• Clustering Similar to classification when no
  groups have yet been defined. Discovers different
  groupings within data

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Business Value of DSS

• Providing fine-grained information for decisions
  that enable the firm to coordinate both internal
  and external business processes much more
  precisely
• Helping with decisions in
• Supply chain management
• Customer relationship management
• Pricing Decisions
• Asset Utilization
• Data Visualization Presentation of data in
  graphical forms, to help users see patterns and
  relationships
• Geographic Information Systems (GIS) Special
  category of DSS that display geographically
  referenced data in digitized maps

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Decision-Support Systems (DSS)
Cargo revenue optimization of Continental Airlines
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DSS for Pricing Decisions

• By analyzing several years of sales data for
  similar items, the software estimates a seasonal
  demand curve for each item and predicts how many
  units would sell each week at various prices.
• The software uses sales history to predict how
  sensitive customer demand will be to price changes

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DSS for Supply Chain Management

• Can help firms model inventory stocking levels,
  production schedules, or transportation plans
• Can provide firms with information on key
  performance indicators such as lead time, cycle
  time, inventory turns, or total supply chain
  costs

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DSS for Customer Relationship Management

• Uses data mining to guide decisions
• Consolidates customer information into massive
  data warehouses
• Uses various analytical tools to slice
  information into small segments

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DSS for Customer Analysis and Segmentation
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Predictive Analysis

• Use of datamining techniques, historical data,
  and assumptions about future conditions to
  predict outcomes of events

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Web-Based Customer Decision-Support Systems

• DSS based on the Web and the Internet can support
  decision making by providing online access to
  various databases and information pools along
  with software for data analysis
• Some of these DSS are targeted toward management,
  but many have been developed to attract
  customers.
• Customer decision making has become increasingly
  information intensive, with Internet search
  engines, intelligent agents, online catalogs, Web
  directories, e-mail, and other tools used to help
  make purchasing decisions.
• Customer decision-support systems (CDSS) support
  the decision-making process of an existing or
  potential customer.

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Group Decision-Support System (GDSS)

• An interactive computer-based system used to
  facilitate the solution of unstructured problems
  by a set of decision makers working together as a
  group.

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Components of GDSS

• Hardware
• conference facility,
• audiovisual equipment, etc.
• Software tools
• Electronic questionnaires,
• brainstorming tools,
• voting tools, etc.
• People
• Participants,
• trained facilitator,
• support staff

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Overview of a GDSS Meeting

• In a GDSS electronic meeting, each attendee has a
  workstation.
• The workstations are networked and are connected
  to
• the facilitators console, which serves as the
  facilitators workstation and
• control panel, and
• to the meetings file server.
• All data that the attendees forward from their
  workstations to the group are collected and saved
  on the file server.

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• The facilitator is able to project computer
  images onto the projection screen at the front of
  the room.
• Many electronic meeting rooms have seating
  arrangements in semicircles and are tiered in
  legislative style to accommodate a large number
  of attendees.
• The facilitator controls the use of tools during
  the meeting.

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Group System Tools
Group Interaction
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How GDSS can Enhance Group Decision-Making

• Traditional decision-making meetings support an
  optimal size of three to five attendees. GDSS
  allows a greater number of attendees.
• Enable collaborative atmosphere by guaranteeing
  contributors anonymity.
• Enable nonattendees to locate organized
  information after the meeting.

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How GDSS Can Enhance Group Decision Making

• Can increase the number of ideas generated and
  the quality of decisions while producing the
  desired results in fewer meetings
• Can lead to more participative and democratic
  decision making

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Organizational Memory

• Store learning from an organizations history
  that can be used for decision making and other
  purposes

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Executive Support Systems (ESS)

• ESS can bring together data from all parts of the
  firm and enable managers to select, access, and
  tailor them as needed.
• It tries to avoid the problem of data overload so
  common in paper reports.
• The ability to drill down is useful not only to
  senior executives but also to employees at lower
  levels of the firm who need to analyze data.
• Can integrate comprehensive firmwide information
  and external data in timely manner
• Inclusion of modeling and analysis tools usable
  with a minimum of training

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Executive Support Systems (ESS)

• Monitor organizational performance
• Track activities of competitors
• Spot problems
• Identify opportunities
• Forecast trends

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The Role of Executive Support Systems in the
Organization

• Brings together data from the entire organization
  
• Allows managers to select, access, and tailor
  data
• Enables executive and any subordinates to look at
  the same data in the same way

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Drill Down

• The ability to move from summary data to lower
  and lower levels of detail

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Developing ESS

• Ease of use
• Facility for environmental scanning
• External and internal sources of information to
  be used for environmental scanning

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Benefits of Executive Support Systems

• Analyzes, compares, and highlights trends
• Provides greater clarity and insight into data
• Speeds up decision-making

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Benefits of Executive Support Systems

• Improves management performance
• Increases managements span of control
• Better monitoring of activities

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ESS for Competitive Intelligence

• Identify changing market conditions
• Formulate responses
• Track implementation efforts
• Learn from feedback

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Balanced Scorecard

• Model for analyzing firm performance that
  supplements traditional financial measures with
  measurements from additional business
  perspectives, such as customers, internal
  business processes, and learning and growth

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Strategic performance management tools for
enterprise systems

• SAP Web-enabled mySAP.com, Management Cockpit
• PeopleSoft Web-enabled Enterprise Performance
  Management (EPM)

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Activity-Based Costing

• Model for identifying all the company activities
  that cause costs to occur while producing a
  specific product or service so that managers can
  see which products or services are profitable or
  losing money and make changes to maximize firm
  profitability

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Management Challenges

• Building systems that can actually fulfill
  Executive Information Requirements
• Changing management thinking to make better use
  of systems for decision support
• Organizational resistance

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Management Opportunities

• Decision-support systems provide opportunities
  for increasing precision, accuracy, and rapidity
  of decisions and thereby contributing directly to
  profitability

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Solution Guidelines

• Flexible Design and Development
• Users must work with IS specialists to identify a
  problem and a specific set of capabilities that
  will help them arrive at decisions about the
  problem.
• The system must be flexible, easy to use, and
  capable of supporting alternative decision
  options.
• Training and Management Support
• User training, involvement, and experience top
  management support and length of use are the
  most important factors in the success of
  management support systems.