Decision Support Systems and Executive Information Systems

1
Decision Support Systems and Executive
Information Systems

• Chapter 12
• Information Systems Management In Practice 5E
• McNurlin Sprague

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What are Decision Support Systems?

• Systems that support, not replace, managers in
  their decision-making activities
• Decision modeling, decision theory, and decision
  analysis, attempt to make models from which the
  best decision can be derived, by computation
• DSS is defined as Computer-based systems
• That help decision makers
• Confront ill-structured problems
• Through direct interaction
• With data and analysis models

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The Architecture for DSS Components

• DDM Paradigm is the interaction of
• Dialog (D) between the user and the system
• Data (D) that support the system
• Models (M) that provide the analysis capabilities

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The Architecture for DSS Components

• A good DSS should have a balance among the three
  capabilities
• Easy to use to support interaction with non-tech
  users
• Access to wide variety (4 types) of information
  sources
• Provide analysis and modeling in a variety of ways

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The Architecture for DSSThe Dialog Component

• The attributes of the dialog components can be
  called a dialog style
• Reference card
• Mouse to access pull-down menus

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The Architecture for DSSThe Data Component

• Data sources
• Data warehousing
• Data mining

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The Architecture for DSSThe Model Component

• Models provide the analysis capabilities for a
  DSS. Using a mathematical representation of the
  problem, algorithmic processes are employed to
  generate information to support decision making.

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Types of DSS Institutional

• Institutional DSS Intended for organizational
  support on a continuing basis,written using a DS
  language. Typically mainframe, now PC-based
• For Marketing Analysis (e.g., Ore-Ida) Support
  three main tasks in decision-making process
• Data retrieval - help manager answer What has
  happened?
• Market analysis - answer question Why did it
  happen?
• Modeling - helps manager answer What will happen
  if?

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Types of DSS Institutional

• Institutional DSS (cont.)
• For Sales Forecasting (e.g., Sara-Lee)
• Previously sales forecasts came from sales force
  - were too optimistic, inventories were
  excessive.
• Then time-series analysis of historical data was
  used, did not handle impact of sales promotions
  well.
• Now companies use multiple regression models in
  order to inject explanatory variables into
  analysis of historical data - and therefore into
  the forecasts

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Types of DSS Quick Hit DSS

• Quick hit DSS Means a system that is quite
  limited in scope, is developed and put into use
  quickly, and helps a manager come to a decision
  fast. Can be useful for
• Getting managers started in using DSS
• Providing DS for certain types of management
  decisions on an ad hoc or recurring basis
• Providing a basis for deciding whether or not to
  build a full DSS
• For supporting decision situations where the
  executives cannot wait for a full DSS to be built

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Types of DSS Quick Hit DSS

• Quick hit DSS (cont.) - types
• Reporting DSS Select, summarize, and list data
  from existing data files to meet manager's
  specific info needs
• Short Analysis program Analyze data as well as
  print or display the data. Generally use a small
  amount of data, which can be entered manually,
  e.g., impact of ESOP
• DSS generators Provide a way to develop
  quick,high - payoff DSS. Include languages,
  interfaces, and other facilities that aid in
  setting up specific DSS within a class of
  decision support applications

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Important Developments in DSS

• PC-based DSS has continued to grow. Spreadsheets
  encompass some of the functions previously
  performed by DSS generators.
• Group DSS to support interdependent group
  decisions
• Focused versions targeted at specific users
• DSS groups as support teams for variety of other
  types of user support
• User friendly capabilities
• DSS refers mostly to systems for analysis of
  complex situations, having absorbed most of the
  work of management science and operations
  research in business organizations

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Data Warehousing and Data Mining

• Data warehouse Houses data used to make
  decisions. This data is obtained periodically
  from transaction databases. The warehouse
  provides a snapshot of a situation at a specific
  time. Data warehouses differ from operational
  databases in that they do not house data used to
  process daily transactions. Operational
  databases have the latest data.

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Data Warehousing and Data Mining

• Key Concepts
• Metadata The part of the warehouse that defines
  the data. Metadata means data about data.
  Metadata explains the meaning of each data
  element, how each element relates to each other,
  etc.
• Quality data Is the cleaning process
• Data marts Is a subset of data pulled off the
  warehouse for a specific group of users

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Data Warehousing and Data Mining

• Give people new insights into data
• Uncover unknown similarities, correlations that
  exist within one customer group that
  differentiates them from other groups
• Is an advanced use of data warehouses, and it
  requires huge amounts of detailed data

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Executive Information Systems (EIS) Executive
Support Systems (ESS)

• ESS
• Company performance data sales, production,
  earnings, budgets, and forecasts
• Internal communications personal correspondence,
  reports, and meetings
• Environmental scanning for news on government
  regulations, competition, financial and economics
  developments, and scientific subjects

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EIS and ESS Cont.

• EIS is a DSS that provides access to (mostly)
  summary performance data,
• using sophisticated graphics to display and
  visualize that data,
• in a very easy to use fashion,
• and with a minimum of analysis for modeling
  beyond the capability to drill down in summary
  data to examine components.
• ESS adds communications and environmental
  scanning.

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Pitfalls in ESS Development

1. Lack of executive support - executives must
   provide the funding, but are the principal users
   and supply the needed continuity
2. Undefined system objectives - the technology, the
   convenience, and the power of EIS are impressive,
   but the underlying objectives and business values
   of an EIS must be carefully thought through

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Pitfalls in ESS Development (cont)

1. Poorly defined information requirements EIS
   typically need non - traditional information
   sources - judgments, opinion, external text-based
   documents - in addition to traditional financial
   and operating data.
2. Inadequate support staff support staff must have
   technical competence, understand the business,
   and ability to relate executives, and be a
   permanent team to manage evolution of systems

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Pitfalls in ESS Development (cont.)

1. Poorly planned evolution highly competent system
   professionals using the wrong development process
   will fail with EIS EIS are not developed,
   delivered, and then maintained. They should
   evolve over a period of time under the leadership
   of a team that includes the executive sponsor,
   the operating sponsor, executive users, the EIS
   support staff manager, and the IS technical staff

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What is a strong reason to install an EIS?

• Attack a critical business need EIS can be
  viewed as an aid to dealing with important needs
  that involve the future health of the
  organization
• A strong personal desire by the executive The
  executive sponsoring the project may want to get
  information faster than he/she is now getting it,
  or have a quicker access to a broader range of
  information, or have the ability to select and
  display only desired information and to probe for
  supporting detail, or to see information in
  graphical form

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A weak reason to install an EIS

• The thing to do An EIS is seen as something
  that modern management must have, in order to be
  current in management practices. The rationale
  given is that the EIS will increase executive
  performance and reduce time that is wasted by
  such things as telephone tag.

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The Main Role of EIS

1. A Status Access System Filter, extract, and
   compress a broad range of up-to-date internal and
   external information. It should call attention to
   variances from plan. It should also monitor and
   highlight the critical success factors of the
   individual executive user. EIS is a structured
   reporting system for executive management,
   providing the executive with the data and
   information of choice and desired form.

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The Main Role of EIS

1. Human Communications Support This viewpoint sees
   an EIS in terms of human communications support
   that it provides. Manager can call on network of
   help (peers, subordinates, clients, customers,
   suppliers, etc). Manager makes requests, gives
   instructions, asks questions to selected members
   of this network, and acts through communications.
   EIS supports these communications.

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DSS Trends

• Personal computer based DSS Newer packages
• For the institutional DSS that support sequential
  interdependent decision making Distributed DSS
• For interdependent decision support Group DSS
• Decision support system products are
  incorporating tools and techniques from
  artificial intelligence

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DSS Trends

• Continued efforts to leverage the usefulness of
  DSS EIS
• DSS development groups have become less like
  special project commando teams and more a part of
  the end user support team
• Cutting across all the preceding trends is the
  continued development of user friendly
  capabilities Dialog support, speech recognition

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Future of DSS

• Application of technologies to improve the
  performance of information workers in
  organizations, specially dealing with
  ill-structured problems.
• Challenges
• Integrated architecture a common interface at
  the desktop as common dialog interface to access
  all IS
• Connectivity an integrated part of IS
• Document in addition to data
• More intelligence