Unit-4
Information System
"Information system is set of people, information technology, and business process in
order to achieve a business objective."
Information systems are a set of interconnected elements working together to collect, process,
store, and distribute information to help coordination, visualization in an organization,
analysis, and decision-making.
The Information system can be defined as a collection of software, hardware, and
telecommunications network that people develop and use to gather, create, and distribute
useful data, mainly in organizational settings.
In other words, an information system means a collection of interrelated components which
work together to gather, process, store, and break down the information to help decision
making.
Pyramid Diagram of Organizational levels and information
requirements
Understanding the various levels of an organization is essential to understand the information
required by the users who operate at their respective levels.
The following diagram illustrates the various levels of a typical organization.
Operational management level
The operational level is concerned with performing day to day business transactions of the
organization.
Examples of users at this level of management include cashiers at a point of sale, bank tellers,
nurses in a hospital, customer care staff, etc.
Users at this level use make structured decisions. This means that they have defined rules that
guides them while making decisions.
For example, if a store sells items on credit and they have a credit policy that has some set
limit on the borrowing. All the salesperson needs to decide whether to give credit to a
customer or not is based on the current credit information from the system.
Tactical Management Level
This organization level is dominated by middle-level managers, heads of departments,
supervisors, etc. The users at this level usually oversee the activities of the users at the
operational management level.
Tactical users make semi-structured decisions. The decisions are partly based on set
guidelines and judgmental calls. As an example, a tactical manager can check the credit limit
and payments history of a customer and decide to make an exception to raise the credit limit
for a particular customer. The decision is partly structured in the sense that the tactical
manager has to use existing information to identify a payments history that benefits the
organization and an allowed increase percentage.
Strategic Management Level
This is the most senior level in an organization. The users at this level make unstructured
decisions. Senior level managers are concerned with the long-term planning of the
organization. They use information from tactical managers and external data to guide them
when making unstructured decisions.
Types of Information System
The types of information systems are as follows:
Transaction Processing System (TPS):
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The term "transaction processing system" refers to an information system that
processes data are originating from business transactions.
The primary purpose of a transaction processing system is to offer transactions to
update records and produce reports required for storekeeping.
Online Transaction Processing and Batching Processing are the methods which we
used to complete the transaction.
Examples of transaction processing systems are Stock control systems, Payroll
systems, Bill systems.
Transaction processing system meaning refers to an information processing system that
processes all transactions taking place within the business. Such transactions include
modification, collection, and retrieval of transaction data. A TPS is highly consistent,
efficient, and dependable. It is the same system that online businesses utilize for e-commerce.
A TPS has the following four components. One must understand them to know how the
system works.
1. Inputs: Inputs are original requests for payments or products outside parties send to
an organization’s TPS. Typically, inputs include bills, coupons, custom orders, and
invoices.
2. Output: Outputs are the documents a TPS generates after it processes all inputs, for
example, the receipts stored by companies in their records. Such documents help
validate transactions and offer crucial reference details for tax and multiple official
purposes.
3. Storage: A TPS’s storage component is where organizations keep their output and
input data. Some businesses store the documents in a database. This component
ensures the security, accessibility, and organization of all documents for late use.
4. Processing System: The processing system goes through every input and establishes
a useful output, for example, a receipt. It helps outline the input data and defines what
the outputs must be. One must remember that the processing time varies depending on
the type of TPS an organization uses.
Features
The following are some crucial features of a TPS:
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Controlled Access: TPSs are powerful business tools. Hence, only authorized
employees can access it. In other words, it allows only certain employees to control
and process transactions.
Connection With the External Environment: TPS establishes a relationship with
the external environment by distributing information to suppliers and customers.
Fast Response: This feature is crucial for a TPS as organizations cannot afford to
keep their customers waiting long before completing a transaction.
Inflexibility: A TPS processes all transactions in the same way, irrespective of the
time of day, user, or customer, to maximize efficiency.
Reliability: A TPS must be reliable as customers do not tolerate errors; it must have
adequate security and safety measures.
Distribution Of Details to Other Systems: A TPS produces and distributes
information to different systems. For instance, sales processing systems provide
information to general ledger systems.
Types of transaction processing systems
There are two types of transaction processing systems:
Batch processing
Through batch processing, a TPS interprets sets, or batches, of data by grouping items based
on similarities. Batch processing can create a time delay because it reviews several sets of
data simultaneously, requiring more computing power.
Example: A customer pays for a subscription service at the end of the month, The TPS
system processes the transactions as a batch because they occur at the same time. In this case,
a delay in processing transactions is acceptable because the system only interprets batches
once per month.
Real-time processing
Real-time processing is a method to process transactions as they appear. This helps prevent
delays in processing and can provide a more accurate result.
Example: An e-commerce website might use a TPS to process credit card transactions in realtime to ensure payment before the company starts its fulfillment process. Processing
transactions in real-time also helps the company identify and address errors quickly, as well
as increase its overall response times.
Advantages
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A TPS helps organizations save funds by minimizing their need to improve their
system or utilize multiple systems to fulfill demand.
Companies can use a TPS to process transactions accurately and quickly.
A TPS automates a significant part of a company’s revenue management and internal
resources. Because of this, employees can review transactions faster. Moreover, this
gives them more time to focus on critical thinking tasks.
It allows businesses to carry out operations in multiple segments by working
remotely. This enables organizations to explore new markets that are full of
opportunities.
Disadvantages
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A TPS does not have a standard format.
Companies have to incur a high set-up cost initially for TPS.
Sometimes, hardware and software have compatibility issues.
A TPS may stop working or slow down due to many transactions.
Decision Support System (DSS)
A decision support system (DSS) is a computerized program used to support determinations,
judgments, and courses of action in an organization or a business. A DSS sifts through and
analyzes massive amounts of data, compiling comprehensive information that can be used to
solve problems and in decision-making.
Typical information used by a DSS includes target or projected revenue, sales figures or past
ones from different time periods, and other inventory- or operations-related data.
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A decision support system (DSS) is a computerized system that gathers and analyzes
data, synthesizing it to produce comprehensive information reports.
A decision support system differs from an ordinary operations application, whose
function is just to collect data.
Decision support systems allow for more informed decision-making, timely problemsolving, and improved efficiency in dealing with issues or operations, planning, and
even management.
Characteristics of a DSS
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Support for decision-makers in semi-structured and unstructured problems.
Support for managers at various managerial levels, ranging from top executive to line
managers.
Support for individuals and groups. Less structured problems often requires the
involvement of several individuals from different departments and organization level.
Support for interdependent or sequential decisions.
Support for intelligence, design, choice, and implementation.
Support for variety of decision processes and styles.
DSSs are adaptive over time.
Components of a Decision Support System
The three main components of a DSS framework are:
1. Model Management System
The model management system S=stores models that managers can use in their decisionmaking. The models are used in decision-making regarding the financial health of the
organization and forecasting demand for a good or service.
2. User Interface
The user interface includes tools that help the end-user of a DSS to navigate through the
system.
3. Knowledge Base
The knowledge base includes information from internal sources (information collected in a
transaction process system) and external sources (newspapers and online databases).
Types of Decision Support Systems
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Communication-driven: Allows companies to support tasks that require more than
one person to work on the task. It includes integrated tools such as Microsoft
SharePoint Workspace and Google Docs.
Model-driven: Allows access to and the management of financial, organizational, and
statistical models. Data is collected, and parameters are determined using the
information provided by users. The information is created into a decision-making
model to analyze situations. An example of a model-driven DSS is Dicodess – an
open-source model-driven DSS.
Knowledge-driven: Provides factual and specialized solutions to situations using
stored facts, procedures, rules, or interactive decision-making structures like
flowcharts.
Document-driven: Manages unstructured information in different electronic formats.
Data-driven: Helps companies to store and analyze internal and external data.
Advantages of a Decision Support System
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A decision support system increases the speed and efficiency of decision-making
activities. It is possible, as a DSS can collect and analyze real-time data.
It promotes training within the organization, as specific skills must be developed to
implement and run a DSS within an organization.
It automates monotonous managerial processes, which means more of the manager’s
time can be spent on decision-making.
It improves interpersonal communication within the organization.
Disadvantages of a Decision Support System
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The cost to develop and implement a DSS is a huge capital investment, which makes
it less accessible to smaller organizations.
A company can develop a dependence on a DSS, as it is integrated into daily decisionmaking processes to improve efficiency and speed. However, managers tend to rely
on the system too much, which takes away the subjectivity aspect of decision-making.
A DSS may lead to information overload because an information system tends to
consider all aspects of a problem. It creates a dilemma for end-users, as they are left
with multiple choices.
Implementation of a DSS can cause fear and backlash from lower-level employees.
Many of them are not comfortable with new technology and are afraid of losing their
jobs to technology.
Experts System
An expert system is the highest form of management computing office automation which
allows the communication and manipulation of documents.
Decision support systems aid in problem solving by allowing for manipulation of data and
models.
Expert systems go beyond traditional manipulation of this type as they allow experts to
‘teach’ computers about their fields so that the system may support more of the decisionmaking process for less expert decision makers.
In this sense, an expert system is software that contains a knowledge base of facts and
relationships and has the ability to make inferences based on that knowledge base. An expert
system is a computer-based information system in which knowledge is represented in data, in
which the processing of the knowledge is directed primarily by computer programs.
Expert systems represent one of the most advanced facts of information technology. That is,
they aid people in some of the most complex and least understood human information
handling tasks, i.e., decision making, problem solving, diagnosis and learning. They do this
by storing a large amount of factual information on a subject area, together with lines of
reasoning employed by human experts in that area.
Most of this material is supplied to the program at the time it is written, but it also has
facilities for adding to this base of information as it is applied in new situations. The subject
expertise is provided initially by interviews and observations of successful PR actioners of
the subject.
Expert system is software, which is used by the business executives to solve complex
organizational problems. These are the programs, which act both as intelligently and as an
expert in some area of knowledge. Modern business managers perform their duties under
dynamic environment. Due to the complexity in the way, the business is conducted.
There are number of variables which are involved in decision making. This has made the
overall decision-making process very complex to analyze the alternatives manually. The role
of operation research has been increasingly important in solving managerial problems. Expert
systems are the programs, which incorporate all these decision-making techniques.
Expert System Components
The key components of Expert System are as followings,
1. User Interface:
It contains a computerized system between the user and the machine for friendly
communication. This system provides an interface to the user in a graphical way.
2. Interference Engine:
It regains & determines the data process. It performs this task to deduce new facts
which are subsequently used to draw further conclusions. This component is
associated with an expert system as the brain of the expert system.
3. Knowledge Base:
This is the most important element of an expert system because it holds the expert's
knowledge of problem-solving. It is here that the expert's elicited knowledge is stored.
It contains the rules, facts, and object descriptions, etc. The knowledge base is always
stored in the data with the newest expert system products. The knowledgebase
information is all that is needed to understand & formulate the problem, and then
solve it.
4. Data Acquisition Subsystem:
The specialist has to learn the information reflected in the knowledge base.
Information acquisition software is used by a person who has problem experience to
build, incorporate or modify the base of knowledge. Potential knowledge sources
include human experts, research reports, textbooks, databases, and the experience of
the user himself.
Advantages of Expert System
Expert System (ES) gives clear responses for routine actions, procedures, and activities.
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Expert System (ES) retains significant levels of the knowledge base.
Expert System (ES) supports organizations to explain the rationale of their decisionmaking.
Disadvantages Expert System
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Expert System (ES) doesn't reply creatively as a human expert in unusual ways.
Expert System (ES) requires more technical aspects due to this difficult in use.
Highly costlier system.
Executive Information System
An Executive Information System (EIS) is a kind of decision support system (DSS) used
in organizations to help executives in decision making. It does so by providing easy access to
important data needed in an organization to achieve strategic goals. An EIS usually has
graphical displays on a user-friendly interface.
Executive information systems can be used for monitoring company performance in many
different types of organizations as well as for identifying opportunities and problems.
Early executive information systems were developed on mainframe computers as computerbased programs to provide the description, sales performance and/or market research data for
senior executives of a company. Executives, however, were not all literate or confident about
the computers. Also, EIS data endorsed only executive-level decisions that did not
necessarily support the entire company or enterprise.
HOW AN EIS SHOULD BE?
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EIS should be very easy to understand so that the users do not get confused while using it. A
user-friendly EIS can help management to save time and collect information rather easily.
EIS should be such that it helps in achieving organizational objective. EIS data should clearly
reflect objectives of the organization in various core fields of the organization.
EIS should be such that it encourages staff & management to work towards growth of the
organization.
EIS must be such that it meets the changing needs of the organization.
EIS should help to reduce the workload of the top management and staff.
Confidential Information should not become part of the EIS.
Executive Information System (EIS) Characteristics
The below mentioned figure describes about key characteristics of EIS,
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Detailed data – EIS provides absolute data from its existing database.
Integrate external and internal data – EIS integrates integrate external and internal
data. The external data collected from various sources.
Presenting information – EIS represents available data in graphical form which
helps to analyze it easily.
Trend analysis – EIS helps executives of the organizations to data prediction based
on trend data.
Easy to use – It is a very simplest system to use.
COMPONENTS OF EIS
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USER INTERFACE: User Interface allows the users to communicate with the EIS. User
interface must be easy to use and understand. Users should not be required to understand the
complex query languages and other mathematical or statistical formulas.
HARDWARE: Hardware refers to devices by which users give input, data processing and the
output is received. Users may give input via keyboard and mouse and CPU may be used for
processing and output may be received on monitor or from printer.
SOFTWARE: Software is required for various calculations, providing graphical view to the
management, storing data in the form of Information, etc. Software allows user to get
information in the form it is actually required.
TELECOMMUNICATION: In today’s world the most important thing is communication.
Users may require transferring information from one point to another point. The information
might be a little confidential in nature. The secrecy of the information should be well
maintained.
APPLICATIONS OF EIS
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MANUFACTURING: It determines whether a process is running correctly or not. It helps in
ensuring proper quality control of finished goods. It measures the actual process time and
compares with the standard time required for the process. It provides management with daily
production report, daily consumption report, safety stock report, economic order quantity, etc.
FINANCIAL: Every organization needs to ensure financial activities are running sound. EIS
may help to analyze whether payment has been realized from creditors within stipulated
period of time. It can help management in managing various other sources of finance.
ACCOUNTING: It helps in proper accounting and disbursement of accounting functions.
ADVANTAGES
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EIS is easy for use and saves time of the top-level management of the organization.
EIS provide access to timely information in a rapid manner.
EIS provides extensive online analysis tools.
EIS can easily be given a DSS support.
Knowledge Management System
Knowledge management (KM) is the process of identifying, organizing, storing, and
disseminating information within an organization. When knowledge is not easily accessible
within an organization, it can be incredibly costly to a business as valuable time is spent
seeking out relevant information versus completing outcome-focused tasks.
A knowledge management system (KMS) harnesses the collective knowledge of the
organization, leading to better operational efficiencies. These systems are supported by the
use of a knowledge base. They are usually critical to successful knowledge management,
providing a centralized place to store information and access it readily.
Companies with a knowledge management strategy achieve business outcomes more quickly
as increased organizational learning and collaboration among team members facilitates faster
decision-making across the business. It also streamlines more organizational processes, such
as training and on-boarding, leading to reports of higher employee satisfaction and retention.
Types of knowledge
The definition of knowledge management also includes three types of knowledge—tacit,
implicit, and explicit knowledge. These types of knowledge are largely distinguished by the
codification of the information.
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Tacit knowledge: This type of knowledge is typically acquired through experience,
and it is intuitively understood. As a result, it is challenging to articulate and codify,
making it difficult to transfer this information to other individuals. Examples of tacit
knowledge can include language, facial recognition, or leadership skills.
Implicit knowledge: While some literature equivocates implicit knowledge to tacit
knowledge, some academics break out this type separately, expressing that the
definition of tactic knowledge is more nuanced. While tacit knowledge is difficult to
codify, implicit knowledge does not necessarily have this problem. Instead, implicit
information has yet to be documented. It tends to exist within processes, and it can be
referred to as “know-how” knowledge.
Explicit knowledge: Explicit knowledge is captured within various document types
such as manuals, reports, and guides, allowing organizations to easily share
knowledge across teams. This type of knowledge is perhaps the most well-known and
examples of it include knowledge assets such as databases, white papers, and case
studies. This form of knowledge is important to retain intellectual capital within an
organization as well as facilitate successful knowledge transfer to new employees.
Knowledge management process
Effective knowledge management system typically goes through three main steps:
1. Knowledge Creation: During this step, organizations identify and document any
existing or new knowledge that they want to circulate across the company.
2. Knowledge Storage: During this stage, an information technology system is typically
used to host organizational knowledge for distribution. Information may need to be
formatted in a particular way to meet the requirements of that repository.
3. Knowledge Sharing: In this final stage, processes to share knowledge are
communicated broadly across the organization. The rate in which information spreads
will vary depending on organizational culture. Companies that encourage and reward
this behavior will certainly have a competitive advantage over other ones in their
industry.
Knowledge management tools
There are a number of tools that organizations utilize to reap the benefits of knowledge
management. Examples of knowledge management systems can include:
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Document management systems act as a centralized storage system for digital
documents, such as PDFs, images, and word processing files. These systems enhance
employee workflows by enabling easy retrieval of documents, such as lessons
learned.
Content management systems (CMS) are applications which manage web content
where end users can edit and publish content. These are commonly confused with
document management systems, but CMSs can support other media types, such as
audio and video.
Intranets are private networks that exist solely within an organization, which enable
the sharing of enablement, tools, and processes within internal stakeholders. While
they can be time-consuming and costly to maintain, they provide a number of
groupware services, such as internal directories and search, which facilitate
collaboration.
Wikis can be a popular knowledge management tool given its ease of use. They make
it easy to upload and edit information, but this ease can lead to concerns about
misinformation as workers may update them with incorrect or outdated information.
Data warehouses aggregate data from different sources into a single, central,
consistent data store to support data analysis, data mining, artificial intelligence (AI),
and machine learning. Data is extracted from these repositories so that companies can
derive insights, empowering employees to make data-driven decisions.
Benefits of knowledge management
Companies experience a number of benefits when they embrace knowledge management
strategies. Some key advantages include:
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Identification of skill gaps: When teams create relevant documentation around
implicit or tacit knowledge or consolidate explicit knowledge, it can highlight gaps in
core competencies across teams. This provides valuable information to management
to form new organizational structures or hire additional resources.
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Make better informed decisions: Knowledge management systems arm individuals
and departments with knowledge. By improving accessibility to current and historical
enterprise knowledge, your teams can upskill and make more information-driven
decisions that support business goals.
Maintains enterprise knowledge: If your most knowledgeable employees left
tomorrow, what would your business do? Practicing internal knowledge management
enables businesses to create an organizational memory. Knowledge held by your
long-term employees and other experts, then make it accessible to your wider team.
Operational efficiencies: Knowledge management systems create a go-to place that
enable knowledge workers to find relevant information more quickly. This, in turn,
reduces the amount of time on research, leading to faster decision-making and costsavings through operational efficiencies. Increase productivity not only saves time,
but also reduces costs.
Increased collaboration and communication: Knowledge management systems and
organizational cultures work together to build trust among team members. These
information systems provide more transparency among workers, creating more
understanding and alignment around common goals. Engaged leadership and open
communication create an environment for teams to embrace innovation and feedback.
Data Security: Knowledge management systems enable organizations to customize
permission control, viewership control and the level of document-security to ensure
that information is shared only in the correct channels or with selected individuals.
Give your employees the autonomy access knowledge safely and with confidence.
Recent Developments in the Field of Information Technology
New trends arise within this industry every year, and it becomes essential for professionals to
be familiar with these different trends and all that they entail. No matter what profession one
is working in, being familiar with these can improve your professional standing and help you
understand the potential upgrades for the industry you are already working in.
1. Cloud Computing
One of the biggest trends that have emerged during the past year is cloud computing. More
and more industries realize that it is essential for a company to have a designated place for all
of its digital information and resources. Having a well-protected place that can take care of
everything and keep the information safe has almost become a necessity. Cloud computing is
the go-to solution for brands who want to improve their work and make it more efficient
digitally.
2. Mobile Apps
Mobile applications have only grown in popularity over the past few years, and this year,
they are surfacing in bigger and better ways. Brands and industries worldwide are trying to
improve their work by using mobile apps and implementing new resources that can make
working on the go more efficient.
3. Big Data Analytics
Big data analytics is a trend that has grown over the past few years. This is implemented in
almost every industry using large-scale production processes, manufacturing, and supply. Big
data analytics allows brands to process their information better and better understand the
areas they need to develop.
4. Automation
Automation is one trend that has primarily hit the manufacturing and production units and is
estimated to only grow more in the coming years. Automation has also enabled processes to
work faster and would allow companies to reach their goals much more efficiently.
5. Artificial Intelligence
While automation grows, artificial intelligence is now seeing the light of day. The past year
saw the introduction of several new mediums of artificial intelligence. This year, industries
are looking at ways in which they can grow these resources and implement the work they do.
Artificial intelligence is now starting to see implementation on a larger scale which is only set
to grow more over the coming years.
6. Smart Technology
Intelligent machines that use artificial intelligence or automation are on the rise, even in
small-scale units and smaller implementations. Homes are becoming more innovative due to
the intelligent technology used and opted for in homes. Simple tools such as Alexa have
become essential to homes and are only estimated to increase over the next year.
7. Virtual Reality
The gaming industry has always been one that has experienced growth alongside the field of
information technology, and virtual reality has taken this one step further, giving customers
the epitome of digital experience. Virtual reality gaming has already started to become
popular due to new technology, which improves how the industry can grow.
8. Augmented Reality
Augmented reality is another approach to ‘artificial experiences’ that individuals are now
given access to. This has improved how the field has been able to develop. Augmented reality
is seeing a lot more applicability outside the gaming industry as well and is something that is
seeing more implementation as compared to virtual reality.
9. Blockchain Data
Cryptocurrency might have been at an all-time high in 2017 and 2018, but the fact remains
that this is yet to see significant development. Blockchain technology is only starting to grow
in popularity and is being implemented by industries worldwide for all it offers.
10. CyberSecurity
With the growth of digital mediums and technology, the potential threats that people can face
are only rising. Because of this, cybersecurity has had to grow extensively over the past few
years to stay in touch with the growth experienced. Industries all over the world also realize
the importance of investing in cybersecurity, which is why the field is experiencing growth at
such a rapid pace.
11. Growth of IoT Networks
The Internet Of Things is a concept that all digital devices are connected by a single medium
through which one can control everything within their home. More and more brands realize
that this is indeed the way of the future and is within technological reach. More brands are
beginning to incorporate this concept, and the statistics showcasing this are prevalent enough
to attest to positive growth.
12. Predictive Analytics Implementations
Predictive Analytics is analyzing large volumes of data to conclude the possible outcomes
that a situation might have. Market analysts see this as a unique tool for brands to note
whether they should move in a particular direction. This has proven to be a very efficient
analysis method and saves the industry an incredible amount of money.
13. Cloud Migration
Cloud migration has proven incredibly beneficial for businesses that want to move in a digital
direction and maintain better digital data records. Cloud migration has grown over the past
few years, and these statistics show positive results. More than 74% of CFOs state that cloud
migration was one of the most beneficial things for the growth of their businesses.
14. Rise Of Data Officers
With the growing importance of information technology and data analytics, data officers have
become even more critical in institutions and industries worldwide. The number of positions
open within this is plenty and is growing as more and more businesses require someone
proficient in this.
15. Quantum Computing Applications
Quantum Computing is a process of conducting complex equations and functions to perform
several complex tasks or process large volumes of information with absolute ease. This has
proven incredibly beneficial for various industries and is seeing massive growth.
16. Smart Technology
Homes are now becoming more intelligent thanks to the numerous integrated devices that
work to make our lives easier. Things like Alexa and other supplementary resources have
proven incredibly beneficial, making homes significantly more efficient and safer.
17. Open-Source Solutions
Open-Source programs give users access to some of the main files and frameworks in a
particular program, enabling them to modify it easily. As more and more users become
technologically proficient, allowing them to work with applications themselves is incredibly
beneficial.
18. Edge Computing
Edge computing is one phenomenon that has grown over the past few years and is currently
seeing a wide scale of implementation. In edge computing, large volumes of data are
processed near the network’s edge rather than where the data is mainly generated. This is
meant to make this processing more efficient and optimized. More development mediums are
choosing to go in for this form of computing over traditional types because of its efficiency.
This also attests to the rising number of computing and program generation methods.
19. Rise Of Chatbots
While most tech advancements help us move toward the greater good, some aren’t as
beneficial as we might think. Chatbots aren’t always bad because, in some situations, they
have improved the customer service that we have access to. Chatbots are a program to
respond to specific queries in specific ways and are designed to help customers with some of
the more basic functions they would need. These are, of course, still not in a position wherein
they are a complete substitute for absolute live customer service, which has helped them stay
in development.
Impact of IT on Organization
What is information technology?
IT refers to the study and application of computing and telecommunications systems for
information storage, analysis, transmission, delivery, retrieval, and manipulation. Information
technology (IT) refers to the people, software, Internet, and hardware that work together to
conduct an organization’s most fundamental, automated functions.
Commonly referred to as “IT techs” or “IT technicians,” IT professionals research and
collaborate with businesses to help them determine the types of technology they require and
the benefits of IT, then assist those firms in implementing, maintaining, and servicing those
solutions. Explore- marketing information technology.
Why is information technology important?
Information Technology entails creating, upkeep, and using computer systems, software, and
networks to process and disperse information. It encompasses the individuals who work in
the field of computing as well as the hardware, software, networks, and the Internet. Now,
let’s learn why information technology is important. Along with this, you can explore – the
importance of information in gaining insights.
Impact of information systems on organizations
Information systems have a greater impact on an organization. It may be affected in several
ways. Let’s see1. Economic impact
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From an economic point of view, there are three types of changes we can see.
The relative cost of capital and the cost of information are changed by IT.
It is viewed as a factor of production that can be substituted for traditional
capital and labor
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It also affects the cost and quality of the information.
2. Organization and behavioral impacts
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It flattens organizations.
Now, most of the decision making done by lower levels. There is no need for many
managers. Only fewer managers can do this. Having technological development, large
organizations are reducing their employees and number of business levels. The managers are
received accurate information on time. They are going faster than previously at making their
decision. Management costs are declining day by day. The percentage of revenues and
hierarchy becomes more efficient.
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Post-industrial organizations are based on history and sociology. In the post-industrial
period, managers are chosen by competencies, skills, knowledge, and experience.
Professional workers are much more decentralized, and self-managing in their
decision-making. Task force network is done by workers. They meet face to face to
do specific work. After completing one work, they move to the next work. Explore –
the role of IT.
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Understanding organizational resistance to change
Sometimes, Organizations are affected by organizational politics. Because it can influence
the key resources like who does what to whom, where, when, why, how, etc. one can
visualize the organizational resistance. There are four factors that suggest innovating the
organization.
1.
2.
3.
4.
The nature of the IT innovation
The structure of the organizations
The culture of the organization
Tasks impacted by the innovation.
Moreover, organizational task management, structure, and people are influenced by
technology. In this model, you need to change the technology, structure, people, procedures,
tasks, and management. Organizational resistance is very hard to change. Because it is so
powerful. Check-integrated marketing communication.
The internet and organizations
The internet increases some factors like the accessibility, storage, and distribution of
information and knowledge for organizations. The internet can greatly lower costs.
Businesses are growing rapidly because of access to internet technology. It is a key
component of the business infrastructures. Now, organizations enjoy lower costs, fewer
employees, and better production and efficiency.
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Implications for the design and understanding of information systems
If you want to deliver real benefits to the organization, you must build information systems.
Which is important for understanding the clear information of the organization. There exist
some factors which are important for planning a new system.
1. Organizational environment
2. Structure of the organization like hierarchy, specialization, the division of labor,
routines, rules and regulations, and business processes.
3. Organizational culture and politics
4. The types of organizations
5. The style of the leadership
6. Who are the principal interest groups?
7. Attitudes of the workers
8. Under which situation information system is designed to assist.