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MANAGEMENT
INFORMATION SYSTEM
FINANCIAL MANAGEMENT INFORMATION SYSTEM,
DECISION SUPPORT SYSTEM
FINANCIAL
MANAGEMENT
INFORMATION SYSTEM
Financial management information
system provides information not only for
managers but also for a broader set of
people who need to make better
decisions on a daily basis. Finding
opportunities and quickly identifying
problems can mean the difference
between a business’s success and failure.
Databases of
internal data
Databases of
external data
Financial
DSS
Business
transactions
Transaction
processing
systems
Databases
of valid
transactions
for each
TPS
Business
transactions
Internet or
Extranet
Business
transactions
Financial
MIS
Financial statements
Operational
databases
Uses and management
of funds
Financial statistics
for control
Customers,
Suppliers
Financial
applications
databases
Financial
ES
FUNCTIONS OF FINANCIAL MIS
1. Integrates financial and operational information from multiple sources,
including the internet , into single MIS.
2. Provides easy access to data for both financial and non financial users , often
through use of the corporate intranet to access corporate web pages of
financial data and information.
3. Makes financial data available on a timely basis to shorten analysis turn around
time.
4. Enables analysis of financial data along multiple dimensions – time, geography,
product, plant , customer.
Inputs to the Financial
Information System
• Strategic plan or corporate policies
– Contains major financial objectives and often projects
financial needs.
• Transaction processing system (TPS)
– Important financial information collected from almost
every TPS - payroll, inventory control, order processing,
accounts payable, accounts receivable, general ledger.
– External sources
– Annual reports and financial statements of competitors
and general news items.
Financial MIS Subsystems and
Outputs
• Financial subsystems
–
–
–
–
–
Profit/loss and cost systems
Auditing
Internal auditing
External auditing
Uses and management of funds
DECISION SUPPORT
SYSTEM
A Decision Support System (DSS) is an interactive
computer-based system or subsystem intended to
help decision makers use communications
technologies, data, documents, knowledge and/or
models to identify and solve problems, complete
decision process tasks, and make decisions.
Decision Support System is a general term for any
computer application that enhances a person or
group’s ability to make decisions.
Also, Decision Support Systems refers to an
academic field of research that involves designing
and studying Decision Support Systems in their
context of use.
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
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
SYSTEMS FOR DECISION SUPPORT
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
SYSTEMS FOR DECISION SUPPORT
Model: An abstract representation that illustrates the
components or relationships of a phenomenon
• Statistical models
• Optimization models
• Forecasting models
• Sensitivity analysis (“what-if” models)
SYSTEMS FOR DECISION SUPPORT
Overview of a Decision-Support System
SYSTEMS FOR DECISION SUPPORT
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
SYSTEMS FOR DECISION SUPPORT
Business Value of DSS (Continued)
• 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
•
The key DSS characteristics and capabilities are as follows:
1. Support for decision makers in semi structured and unstructured
problems.
2. Support managers at all levels.
3. Support individuals and groups.
4. Support for interdependent or sequential decisions.
5. Support intelligence, design, choice, and implementation.
6. Support variety of decision processes and styles.
7. DSS should be adaptable and flexible.
8. DSS should be interactive ease of use.
9. Effectiveness, but not efficiency.
10. Complete control by decision-makers.
11. Ease of development by end users.
12. Support modeling and analysis.
13. Data access.
14. Standalone, integration and Web-based
• Supports
– Problem solving phases
– Different decision frequencies
Merge with
another
company?
How many
widgets
should I order?
low
high
Frequency
• Highly structured problems
– Straightforward problems, requiring known
facts and relationships.
• Semi-structured or unstructured problems
– Complex problems wherein relationships
among data are not always clear, the data may
be in a variety of formats, and are often
difficult to manipulate or obtain
Strategic
Strategic-level managers
involved with long-term
decisions
Tactical
Operational-level
managers involved with
daily decisions
Operational
High
Low
Decision Frequency
• In many organizations they are integrated
through a common database
• Separation of DSS transactions in the
database from TPS and MIS transactions
may be important for performance reasons
Database
Model base
DBMS
MMS
Access to the
internet, networks,
and other computer
systems
Dialogue manager
External database
access
External
databases
(1) Time savings. For all categories of decision support systems, research has
demonstrated and substantiated reduced decision cycle time, increased
employee productivity and more timely information for decision making. The
time savings that have been documented from using computerized decision
support are often substantial. Researchers, however, have not always
demonstrated that decision quality remained the same or actually improved.
(2) Enhance effectiveness. A second category of advantage that has been
widely discussed and examined is improved decision making effectiveness and
better decisions. Decision quality and decision making effectiveness are
however hard to document and measure. Most researches have examined soft
measures like perceived decision quality rather than objective measures.
Advocates of building data warehouses identify the possibility of more and
better analysis that can improve decision making.
(3) Improve interpersonal communication. DSS can improve
communication and collaboration among decision makers. In appropriate
circumstances, communications- driven and group DSS have had this
impact. Model-driven DSS provides a means for sharing facts and
assumptions. Data-driven DSS make "one version of the truth" about
company operations available to managers and hence can encourage factbased decision making. Improved data accessibility is often a major
motivation for building a data-driven DSS. This advantage has not been
adequately demonstrated for most types of DSS.
(4) Competitive advantage. Vendors frequently cite this advantage for
business intelligence systems, performance management systems, and
web-based DSS. Although it is possible to gain a competitive advantage
from computerized decision support, this is not a likely outcome. Vendors
routinely sell the same product to competitors and even help with the
installation. Organizations are most likely to gain this advantage from
novel, high risk, enterprise-wide, inward facing decision support systems.
Measuring this is and will continue to be difficult.
(1) Monetary cost. The decision support system requires investing in information
system to collect data from many sources and analyze them to support the
decision making. Some analysis for Decision Support System needs the advance
of data analysis, statistics, econometrics and information system, so it is the high
cost to hire the specialists to set up the system.
(2) Overemphasize decision making. Clearly the focus of those of us interested in
computerized decision support is on decisions and decision making.
Implementing Decision Support System may reinforce the rational perspective
and overemphasize decision processes and decision making. It is important to
educate managers about the broader context of decision making and the social,
political and emotional factors that impact organizational success. It is especially
important to continue examining when and under what circumstances Decision
Support System should be built and used. We must continue asking if the
decision situation is appropriate for using any type of Decision Support System
and if a specific Decision Support System is or remains appropriate to use for
making or informing a specific decision.
.
(3) Assumption of relevance. According to Wino grad and Flores (1986), "Once a
computer system has been installed it is difficult to avoid the assumption that the
things it can deal with are the most relevant things for the manager's concern." The
danger is that once Decision Support System become common in organizations, that
managers will use them inappropriately. There is limited evidence that this occurs.
Again training is the only way to avoid this potential problem.
(4) Transfer of power. Building Decision Support System, especially knowledge-driven
Decision Support System, may be perceived as transferring decision authority to a
software program. This is more a concern with decision automation systems than
with Decision Support System. We advocate building computerized decision support
systems because we want to improve decision making while keeping a human
decision maker in the "decision loop". In general, we value the "need for human
discretion and innovation" in the decision making process
GROUP DECISION-SUPPORT SYSTEMS
What Is a GDSS?
• Group Decision-Support System (GDSS) is an interactive
computer-based system used to facilitate the solution of
unstructured problems by a set of decision makers working
together as a group.
GROUP DECISION-SUPPORT SYSTEMS
Three Main Components of GDSS:
• Hardware (conference facility, audiovisual equipment,
etc.)
• Software tools (Electronic questionnaires, brainstorming
tools, voting tools, etc.)
• People (Participants, trained facilitator, support staff)
GROUP DECISION-SUPPORT SYSTEMS
Group System Tools
Source: From Nunamaker et al.,
“Electronic Meeting Systems to
Support Group Work,”
Communication of the ACM, July
1991. Reprinted with permission.
GROUP DECISION-SUPPORT SYSTEMS
Business Value of GDSS
• 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
contributor’s anonymity.
• Enable nonattendees to locate organized information after
the meeting.
GROUP DECISION-SUPPORT SYSTEMS
Business Value of GDSS
• 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
contributor’s anonymity.
• Enable nonattendees to locate organized information after
the meeting.
GROUP DECISION-SUPPORT SYSTEMS
Business Value of GDSS (Continued)
• 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