Business Firm as System

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Business

Environment

and the AIS


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The Business Firm as a System


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System Characteristics of

Business FirmsObjectives

Environment

Constraints

Input-Process-Output

Feedback

ControlsSubsystems


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Major Subsystems


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1. Organizational Structure

It shows how the tasks are divided, groupedand coordinated. An organizational chart is a

diagram that depicts an organbizationalstructure.

Major Subsystems


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2. Information SystemThe information system can be depicted

as a group of related subsystems, such as the

production information system, theaccounting information system, and themarketing information system.

Major Subsystems


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3. Operational Sytem

The operational system of a firm is thecollection of primary physical processes.

Major Subsystems


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The Operational

System of aManufacturing Firm


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Facilities

Labor(humanservices)

Data

Funds

AcquiringMaterials

ProducingFinishedGoods

StoringFinishedGoods

ShippingFinishedGoods

Goodsto

Customer

SupportingOperations

AIS

Information

Funds

MaterialfromSupplier

Manufacturing Firm

Data and information flow

Physical flows

The Operational System of aManufacturing Firm


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Organizational

Structures


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Matrix Structure It blends functional and project oriented

structures.

Organizational Structures


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Decentralized StructureA considerable degree of authority is

delegated to middle-level and lower levelmanagers within the structures.



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Network Structure It represents an interconnected but non-

hierarchal structure that is both flexible andfluid.



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Operational System

An operational system is a term used in datawarehousing to refer to a system that is used toprocess the day-to-day transactions of an

organization. These systems are designed soprocessing of day-to-day transactions isperformed efficiently and the integrity of thetransactional data is preserved.


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Operational Systems vs. Data

Warehousing

The fundamental difference betweenoperational systems and data warehousing

systems is that operational systems aredesigned to support transactionprocessing whereas data warehousing systemsare designed to support online analytical

processing(orOLAP, for short).


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Based on this fundamental difference,datausage patterns associated with operationalsystems are significantly different than usage

patterns associated with data warehousingsystems. As a result, data warehousing systemsare designed and optimized usingmethodologies that drastically differ from that

of operational systems.


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Operational Systems Data Warehousing Systems

Operational systems are

generally designed to support

high-volume transaction

processing with minimal back-

end reporting.

Data warehousing systems are generally designed to

support high-volume analytical processing (i.e. OLAP)

and subsequent, often elaboratereport generation.


generallyprocess-

orientedorprocess-driven,

meaning that they are focused

on specific business processes

or tasks. Example tasks include

billing, registration, etc.

Data warehousing systems are generally subject-

oriented, organized around business areas that the

organization needs information about. Such subject

areas are usually populated with data from one or

more operational systems. As an example, revenue

may be a subject area of a data warehouse that

incorporates data from operational systems that

contain student tuition data, alumni gift data,

financial aid data, etc.

Comparison


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Operational Systems Data Warehousing Systems


generally concerned

with current data.

Data warehousing systems are generally concerned

with historical data.

Data within operational

systems are

generally updated

regularlyaccording to need.

Data within a data warehouse is generally non-volatile,

meaning that new data may be added regularly, but onceloaded, the data is rarely changed, thus preserving an

ever-growing history of information. In short, data within

a data warehouse is generally read-only.


generally optimized to

performfast inserts and

updates of relatively small

volumes of data.

Data warehousing systems are generally optimized to

performfast retrievals of relatively large volumes of data.

Comparison


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Operational

Systems

Data Warehousing Systems


generally application-

specific, resulting in a

multitude of partially or

non-integrated systems

andredundant data (e.g.

billing data is not integrated

with payroll data).

Data warehousing systems are generally integratedat a

layer above the application layer, avoiding data

redundancy problems.

Operational systems

generally require a non-trivial level of computing

skills amongst the end-user

community.

Data warehousing systems generally appeal to an end-user community with a wide range of computing skills,

from novice to expert users.

Comparison

Business Firm as System

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