COMPLEX SYSTEM IN DAILY
LIFE
1.
INFORMATION
SYSTEM
v Components
Morley
and Parker (2010) define information system as a discipline that is formed from
elements of business and computer science and is developing to form a separate
area of scientific study. It has been stated that “healthcare information
systems and healthcare processes are closely entwined with one another. Health
care processes require the use of data and information and they also produce or
create information” (Wager et al, 2009, p.65)
Three
basic components of system are explained by Bagad (2010) as input,
process/transformation and output. In information system inputs are data that
are going to be transformed. The process component of an information system
transforms input into an output. Output is considered to be the final product
of a system. In case of an information system, an output would be obtaining
necessary information in a desired format (Currie, 2009).
Explan ations of all of the components of information
system are offered by Stair et al (2008) in the following manner:
Components of information system
|
Definitions
|
Data
|
Input the system takes to produce information
|
Hardware
|
A computer and its peripheral equipment: input, output and storage
devices; hardware also includes data communication equipment
|
Software
|
Sets of instructions that tell the computer how to take data in, how
to process it, how to display information, and how to store data and
information
|
Telecommunications
|
Hardware and software that facilitates fast transmission and reception
of text, pictures, sound, and animation in the form of electronic data
|
People
|
Information systems professionals and users who analyse organisational
information needs, design and construct information systems, write
computer programs, operate the hardware, and maintain software
|
Procedures
|
Rules for achieving optimal and secure operations in data processing;
procedures include priorities in dispensing software applications and
security measures
|
v Classification
of Information System
In
any given organization information system can be classified based on the usage
of the information. Therefore, an information system in an organization can be
divided into operations support system and management support system.
·
Operations support system
In
an organization, data input is done by the end user which is processed to
generate information products i.e. reports, which are utilized by internal and
or external users. Such a system is called operation support system.
The
purpose of the operation support system is to facilitate business transaction,
control production, support internal as well as external communication and
update organization central database. The operation support system is further
divided into a transaction-processing system, processing control system and
enterprise collaboration system.
·
Transaction Processing
System (TPS)
In
manufacturing organization, there are several types of transaction across
department. Typical organizational departments are Sales, Account, Finance,
Plant, Engineering, Human Resource and Marketing. Across which following
transaction may occur sales order, sales return, cash receipts, credit sales;
credit slips, material accounting, inventory management, depreciation
accounting, etc. These transactions can be categorized into batch transaction
processing, single transaction processing and real time transaction processing.
·
Process Control System
In
a manufacturing organization, certain decisions are made by a computer system
without any manual intervention. In this type of system, critical information
is fed to the system on a real-time basis thereby enabling process control.
This kind of systems is referred as process control systems.
·
Enterprise Collaboration
System
In
recent times, there is more stress on team effort or collaboration across
different functional teams. A system which enables collaborative effort by
improving communication and sharing of data is referred to as an enterprise
collaboration system.
·
Management Support System
Managers
require precise information in a specific format to undertake an organizational
decision. A system which facilitates an efficient decision making process for
managers is called management support system. Management support systems are
essentially categorized as management information system, decision support
system, expert system and accounting information system.
2.
DECISION
SUPPORT SYSTEM
Decision
support systems vary greatly in application and complexity, but they all share
specific features. A typical Decision support systems has four components: data
management, model management, knowledge management and user interface
management.
1. Data
Management Component
The
data management component performs the function of storing and maintaining the
information that you want your Decision Support System to use. The data
management component, therefore, consists of both the Decision Support System
information and the Decision Support System database management system. The
information you use in your Decision Support System comes from one or more of
three sources:
·
Organizational
information; you may want to use virtually any information available in the
organization for your Decision Support System. What you use, of course, depends
on what you need and whether it is available. You can design your Decision
Support System to access this information directly from your company’s database
and data warehouse. However, specific information is often copied to the
Decision Support System database to save time in searching through the
organization’s database and data warehouses.
·
External information:
some decisions require input from external sources of information. Various
branches of federal government, Dow Jones, Compustat data, and the internet, to
mention just a few, can provide additional information for the use with a
Decision Support System.
·
Personal information: you
can incorporate your own insights and experience your personal information into
your Decision Support System. You can design your Decision Support System so
that you enter this personal information only as needed, or you can keep the
information in a personal database that is accessible by the Decision Support
System.
2. Model
Management Component
The
model management component consists of both the Decision Support System models
and the Decision Support System model management system. A model is a
representation of some event, fact, or situation. As it is not always
practical, or wise, to experiment with reality, people build models and use
them for experimentation. Models can take various forms.
Businesses
use models to represent variables and their relationships. For example, you
would use a statistical model called analysis of variance to determine whether
newspaper, TV, and billboard advertizing are equally effective in increasing
sales.
Decision
Support Systems help in various decision-making situations by utilizing models
that allow you to analyze information in many different ways. The models you
use in a Decision Support System depend on the decision you are making and,
consequently, the kind of analysis you require. For example, you would use
what-if analysis to see what effect the change of one or more variables will have
on other variables, or optimization to find the most profitable solution given
operating restrictions and limited resources. Spreadsheet software such as
excel can be used as a Decision Support System for what-if analysis.
The
model management system stores and maintains the Decision Support System’s
models. Its function of managing models is similar to that of a database
management system. The model management component can not select the best model
for you to use for a particular problem that requires your expertise but it can
help you create and manipulate models quickly and easily.
3. User
Interface Management Component
The
user interface management component allows you to communicate with the Decision
Support System. It consists of the user interface management system. This is
the component that allows you to combine your know-how with the storage and
processing capabilities of the computer.
The
user interface is the part of the system you see through it when enter information,
commands, and models. This is the only component of the system with which you
have direct contract. If you have a Decision Support System with a poorly
designed user interface, if it is too rigid or too cumbersome to use, you
simply won’t use it no matter what its capabilities. The best user interface
uses your terminology and methods and is flexible, consistent, simple, and
adaptable.
For
an example of the components of a Decision Support System, let’s consider the
Decision Support System that Land’s End has tens of millions of names in its
customer database. It sells a wide range of women’s, men’s, and children’s
clothing, as well various household wares. To match the right customer with the
catalog, land’s end has identified 20 different specialty target markets.
Customers in these target markets receive catalogs of merchandise that they are
likely to buy, saving Lands’ End the expense of sending catalogs of all
products to all 20 million customers. To predict customer demand, lands’ end
needs to continuously monitor buying trends. And to meet that demand, lands’
end must accurately forecast sales levels. To accomplish theses goals, it uses
a Decision Support System which performs three tasks:
·
Data management: The
Decision Support System stores customer and product information. In addition to
this organizational information, Lands’ End also needs external information,
such as demographic information and industry and style trend information.
·
Model management: The
Decision Support System has to have models to analyze the information. The
models create new information that decision makers need to plan product lines
and inventory levels. For example, Lands’ End uses a statistical model called
regression analysis to determine trends in customer buying patterns and
forecasting models to predict sales levels.
·
User interface
management: A user interface enables Lands’ End decision makers to access
information and to specify the models they want to use to create the
information they need.
4. Knowledge
Management Component
The
knowledge management component, like that in an expert system, provides
information about the relationship among data that is too complex for a
database to represent. It consists of rules that can constrain possible
solution as well as alternative solutions and methods for evaluating them.
For
example, when analyzing the impact of a price reduction, a Decision Support
System should signal if the forecasted volume of activity exceeds the volume
that the projected staff can service. Such signaling requires the Decision
Support System to incorporate some rules-of-thumb about an appropriate ratio of
staff to sales volume. Such rules-of-thumb, also known as heuristics, make up
the knowledge base.
3.
ENTERPRISE
RESOURCES PLANNING
Enterprise
resource planning (ERP) is a suite of integrated applications that a company
uses to connect its business activities across departments so that everyone is
working with the same data and processes. Companies can use it to streamline
and improve the efficiency of their operations, which saves time and money. In
the course of implementing ERP, companies can also standardize and automate
many business processes, which eliminates manual time and effort.
The
ERP tools that a company selects often depend upon the specific business
processes it wants to improve, and also upon whether it is selling products or
services. Businesses that sell products often have manufacturing, supply chain
and distribution functions that the ERP system must address. For organizations
that sell services, ERP capabilities such as project management for service
engagements and support for field services and sales operations are very
important.
Despite
the wide variability in company needs for ERP, there is a core set of ERP components
that most companies want:
v Finance
Companies
want to record, track and consolidate all of their sales and operational
information in a central accounting system. ERP financial software delivers
this capability with centralized general ledger, accounts receivable, accounts
payable and payroll systems.
v HR
ERP
offers a centralized HR system that enables organizations to track personnel
hours and employee performance evaluations across the organization, as well as
administer benefits and manage talent and staff development.
v Purchasing/procurement
ERP
purchasing software streamlines the procurement process from purchase-order
issuance and vendor management to payments and reporting. ERP purchasing
software also has the ability to automatically route approvals of purchase
orders and payments to the appropriate corporate decision makers.
v Business
intelligence
Organizations
increasingly want data analytics that enable them to assess and act on
information about the business. To facilitate this, ERP vendors provide
pre-designed reports that companies use to assess business sales and
operations, along with the ability to perform data mining and to develop custom
reporting.
v Customer
relationship management
The
ERP CRM application is a centralized repository of customer information that
customer-facing organizations across the company can use and access. It
includes information about company interactions with prospects, customers,
clients and partners, and can track all of these interactions across marketing,
sales, service and any other customer-facing department. ERP CRM includes sales
force reporting, tracking and automation, marketing, service and support.
Erp Software For
Product-Oriented Companies
While
the below components are still core to ERP, they cater more to companies with
specific needs, such as product-oriented companies.
v Supply
chain
An
ERP system that encompasses not only the company's internal operations, but the
operations of supply chain business partners and suppliers in the production of
goods from raw materials, inventory and supplies gives companies much-needed
visibility into their manufacturing processes.
SUGGESTION OF STRATEGY IN
MANAGING BIF DATA AND DATA ANALYTICS
Big
data management strategies and best practices are still evolving, but joining
the big data movement has become an imperative for companies across a wide
variety of industries. This guide delves into the experiences of early-adopter
companies that have already deployed big data applications and technologies. IT
professionals, C-level executives and industry analysts offer insights into
what strategies work on big data projects and how to best integrate big data
management initiatives with related processes such as data warehousing, data
governance and data analytics.
The
following stories explore the steps these companies took to set up big data
systems and to update their approaches as needed. Readers will find practical
information on implementing big data strategies, mixing Hadoop clusters and
conventional data warehousing tools, incorporating big data analytics into the
process and translating big data ideas into successful deployments.
BIG
DATA STRATEGY
Advertising
firm attracts clients with big data strategy. The search advertising company
adMarketplace processes billions of ad requests daily in near real time using a
pay-per-click platform. Due partly to the high level of data customization it
offers to advertisers, adMarketplace processes 100 gigabytes of data per hour.
The first article below explains how the company implemented a platform
combining a traditional data warehouse and a NoSQL database to power the big
data environment that feeds its search syndication system. Other stories in
this section offer more insights into managing and using big data and how it
fits into the data warehousing and data governance process.
REFERENCES
Bagad,
V.S. (2010) “Management Information Systems” John Wiley & Sons
Carter,
J.H. (2010) “Electronic health records: a guide for clinicians and
administrators” ACP Press
Currie,
W. (2009) “Integrating healthcare” in Integrating Healthcare with Information and
Communications Technology” Radcliffe Publishing. Editors, Currie, W &
Finnegan, D.
Hoyt,
R.E., Sutton, M. & Oshinashi, A. (2008) “Medical Informatics: Practical
Guide for the Healthcare Professional” Lulu
Morley,
D. & Parker, C. (2010) “Understanding Computers: Today and Tomorrow,
Comprehensive” Cengage Learning
Wager,
K.A., Lee, F.W & Glaser, J.P. (2009) “Health Care Information Systems: A
Practical Approach for Health Care Management”. Second editon, John Wiley &
Sons
http://dsssystem.blogspot.co.id/2010/01/components-of-decision-support-systems.html
http://searchmanufacturingerp.techtarget.com/feature/Before-implementing-ERP-understand-its-many-components
http://searchdatamanagement.techtarget.com/essentialguide/Big-data-applications-Real-world-strategies-for-managing-big-data
