1. Master of Business Administration
Semester II
MB0047 – Management Information Systems
Assignment
Set- 1
1. What is MIS? Define the characteristics of MIS? What are the basic Functions of MIS?
Give some Disadvantage of MIS?
Ans.
A management information system (MIS) provides information which is needed to
manage organizations efficiently and effectively. Management information systems involve three
primary resources: people, technology, and information or decision making. Management
information systems are distinct from other information systems in that they are used to analyze
operational activities in the organization. Academically, the term is commonly used to refer to
the group of information management methods tied to the automation or support of human
decision making, e.g. decision support systems, expert systems, and executive information
systems.
Overview
Initially in businesses and other organizations, internal reporting was produced manually and
only periodically, as a by-product of the accounting system and with some additional statistic(s),
and gave limited and delayed information on management performance. Data was organized
manually according to the requirements and necessity of the organization. As computational
technology developed, information began to be distinguished from data and systems were
developed to produce and organize abstractions, summaries, relationships and generalizations
based on the data.
Early business computers were used for simple operations such as tracking sales or payroll data,
with little detail or structure. Over time, these computer applications became more
complex, hardware storage capacities grew, and technologies improved for connecting
previously isolated applications. As more and more data was stored and linked, managers sought
greater detail as well as greater abstraction with the aim of creating entire management reports

2. from the raw, stored data. The term "MIS" arose to describe such applications providing
managers with information about sales, inventories, and other data that would help in managing
the enterprise. Today, the term is used broadly in a number of contexts and includes (but is not
limited to): decision support systems, resource and people management applications, enterprise
resource planning (ERP), enterprise performance management (EPM), supply chain
management (SCM), customer relationship management (CRM),project management and
database retrieval applications.
The successful MIS supports a business's long range plans, providing reports based upon
performance analysis in areas critical to those plans, with feedback loops that allow for titivation
of every aspect of the enterprise, including recruitment and training regimens. MIS not only
indicate how things are going, but why and where performance is failing to meet the plan. These
reports include near-real-time performance of cost centers and projects with detail sufficient for
individual accountability.
Types
Most management information systems specialize in particular commercial and industrial
sectors, aspects of the enterprise, or management substructure.
Management information systems (MIS), per se, produce fixed, regularly scheduled
reports based on data extracted and summarized from the firm’s underlying transaction
processing systems to middle and operational level managers to identify and inform
structured and semi-structured decision problems.
Decision support systems (DSS) are computer program applications used by middle
management to compile information from a wide range of sources to support problem
solving and decision making.
Executive information systems (EIS) is a reporting tool that provides quick access to
summarized reports coming from all company levels and departments such as accounting,
human resources and operations.
Marketing information systems are MIS designed specifically for managing
the marketing aspects of the business.
Office automation systems (OAS) support communication and productivity in the
enterprise by automating work flow and eliminating bottlenecks. OAS may be
implemented at any and all levels of management.
School management information systems (MIS) cover school administration, often
including teaching and learning materials.

3. Advantages
The following are some of the benefits that can be attained for different types of management
information systems.
 Companies are able to highlight their strengths and weaknesses due to the presence of
revenue reports, employees' performance record etc. The identification of these aspects can
help the company improve their business processes and operations.
 Giving an overall picture of the company and acting as a communication and planning tool.
 The availability of the customer data and feedback can help the company to align their
business processes according to the needs of the customers. The effective management of
customer data can help the company to perform direct marketing and promotion activities.
 Information is considered to be an important asset for any company in the modern
competitive world. The consumer buying trends and behaviours can be predicted by the
analysis of sales and revenue reports from each operating region of the company.
Enterprise applications
Enterprise systems, also known as enterprise resource planning (ERP) systems provide an
organization with integrated software modules and a unified database which enable efficient
planning, managing, and controlling of all core business processes across multiple locations.
Modules of ERP systems may include finance, accounting, marketing, human resources,
production, inventory management and distribution.
 Supply chain management (SCM) systems enable more efficient management of the supply
chain by integrating the links in a supply chain. This may include suppliers, manufacturer,
wholesalers, retailers and final customers.
 Customer relationship management (CRM) systems help businesses manage relationships
with potential and current customers and business partners across marketing, sales, and
service.
 Knowledge management system (KMS) helps organizations facilitate the collection,
recording, organization, retrieval, and dissemination of knowledge. This may include
documents, accounting records, and unrecorded procedures, practices and skills.
Developing Information Systems.
"The actions that are taken to create an information system that solves an organizational problem
are called system development. These include system analysis, system
design,programming/implementation, testing, conversion, production and finally maintenance.
These actions usually take place in that specified order but some may need to repeat or be
accomplished concurrently.

4. Conversion is the process of changing or converting the old system into the new. This can be
done in four ways:
 Direct cutover – The new system replaces the old at an appointed time.
 Pilot study – Introducing the new system to a small portion of the operation to see how it
fares. If good then the new system expands to the rest of the company.
 Phased approach – New system is introduced in stages.

5. 2. Explain Knowledge based system? Explain DSS and OLAP with example?
Ans.
Knowledge-based systems
Knowledge based systems are artificial intelligent tools working in a narrow domain to provide
intelligent decisions with justification. Knowledge is acquired and represented using various
knowledge representation techniques rules, frames and scripts. The basic advantages offered by
such system are documentation of knowledge, intelligent decision support, self learning,
reasoning and explanation. Knowledge-based systems are systems based on the methods and
techniques of Artificial Intelligence.
Their core components are:
 knowledge base
 acquisition mechanisms
 inference mechanisms
Knowledge Base Systems (KBS) goes beyond the decision support philosophy to indicate the
expert system technology into the decision making framework. Expert Systems (ES) have been
the tools and techniques perfected by artificial intelligence (AI) researchers to deduce decision
influences based on codification of knowledge. The codification of knowledge use the principles
of knowledge representation (part of the large theoretical ideas of knowledge engineering).
Typically such codification uses rules like IF-THEN rules to represent logical implications.
While for some authors expert systems, case-based reasoning systems and neural networks are
all particular types of knowledge-based systems, there are others who consider that neural
networks are different, and exclude it from this category.
KBS is a frequently used abbreviation for knowledge-based system.
Decision support system
A decision support system (DSS) is a computer-based information system that supports business
or organizational decision-making activities. DSSs serve the management, operations, and
planning levels of an organization and help to make decisions, which may be rapidly changing
and not easily specified in advance.
DSSs include knowledge-based systems. A properly designed DSS is an interactive software-
based system intended to help decision makers compile useful information from a combination
of raw data, documents, personal knowledge, or business models to identify and solve problems
and make decisions.

6. Typical information that a decision support application might gather and present are:
 inventories of information assets (including legacy and relational data sources, cubes, data
warehouses, and data marts),
 comparative sales figures between one period and the next,
 projected revenue figures based on product sales assumptions.
Three fundamental components of a DSS architecture are:
1. the database (or knowledge base),
2. the model (i.e., the decision context and user criteria), and
3. the user interface.
The users themselves are also important components of the architecture.[5][12]
Applications
As mentioned above, there are theoretical possibilities of building such systems in any
knowledge domain.
One example is the clinical decision support system for medical diagnosis. Other examples
include a bank loan officer verifying the credit of a loan applicant or an engineering firm that has
bids on several projects and wants to know if they can be competitive with their costs.
DSS is extensively used in business and management. Executive dashboard and other business
performance software allow faster decision making, identification of negative trends, and better
allocation of business resources.
A growing area of DSS application, concepts, principles, and techniques is in agricultural
production, marketing for sustainable development. For example, the DSSAT4
package, developed through financial support of USAID during the 80's and 90's, has allowed
rapid assessment of several agricultural production systems around the world to facilitate
decision-making at the farm and policy levels. There are, however, many constraints to the
successful adoption on DSS in agriculture.
DSS are also prevalent in forest management where the long planning time frame demands
specific requirements. All aspects of Forest management, from log transportation, harvest
scheduling to sustainability and ecosystem protection have been addressed by modern DSSs.
A specific example concerns the Canadian National Railway system, which tests its equipment
on a regular basis using a decision support system. A problem faced by any railroad is worn-out
or defective rails, which can result in hundreds of derailments per year. Under a DSS, CN
managed to decrease the incidence of derailments at the same time other companies were
experiencing an increase.

7. OLAP
An OLAP cube is a set of data, organized in a way that facilitates non-predetermined queries
for aggregated information, or in other words, online analytical processing. OLAP is one of the
computer-based techniques for analyzing business data that are collectively called business
intelligence.
OLAP operations
The analyst can understand the meaning contained in the databases using multi-dimensional
analysis. By aligning the data content with the analyst's mental model, the chances of confusion
and erroneous interpretations are reduced. The analyst can navigate through the database and
screen for a particular subset of the data, changing the data's orientations and defining analytical
calculations. The user-initiated process of navigating by calling for page displays interactively,
through the specification of slices via rotations and drill down/up is sometimes called "slice and
dice". Common operations include slice and dice, drill down, roll up, and pivot.

8. 3. What are Value Chain Analysis & describe its significance in MIS? Explain what is
meant by BPR? What is its significance? How Data warehousing & Data Mining is useful
in terms of MIS?
Ans.
Value chain
A value chain is a chain of activities for a firm operating in a specific industry. The business unit
is the appropriate level for construction of a value chain, not the divisional level or corporate
level. Products pass through all activities of the chain in order, and at each activity the product
gains some value. The chain of activities gives the products more added value than the sum of
the independent activities' values.
It is important not to mix the concept of the value chain with the costs occurring throughout the
activities. A diamond cutter, as a profession, can be used to illustrate the difference of cost and
the value chain. The cutting activity may have a low cost, but the activity adds much of the value
to the end product, since a rough diamond is significantly less valuable than a cut diamond.
Typically, the described value chain and the documentation of processes, assessment and
auditing of adherence to the process routines are at the core of the quality certification of the
business, e.g. ISO 9001.
Significance
The value chain framework quickly made its way to the forefront of management thought as a
powerful analysis tool for strategic planning. The simpler concept of value streams, a cross-
functional process which was developed over the next decade, had some success in the early
1990s.
The value-chain concept has been extended beyond individual firms. It can apply to
whole supply chains and distribution networks. The delivery of a mix of products and services to
the end customer will mobilize different economic factors, each managing its own value chain.
The industry wide synchronized interactions of those local value chains create an extended value
chain, sometimes global in extent. Porter terms this larger interconnected system of value chains
the "value system." A value system includes the value chains of a firm's supplier (and their
suppliers all the way back), the firm itself, the firm distribution channels, and the firm's buyers
(and presumably extended to the buyers of their products, and so on).
Capturing the value generated along the chain is the new approach taken by many management
strategists. For example, a manufacturer might require its parts suppliers to be located nearby its
assembly plant to minimize the cost of transportation. By exploiting the upstream and
downstream information flowing along the value chain, the firms may try to bypass the
intermediaries creating new business models, or in other ways create improvements in its value
system.
Value chain analysis has also been successfully used in large Petrochemical Plant Maintenance
Organizations to show how Work Selection, Work Planning, Work Scheduling and finally Work

9. Execution can (when considered as elements of chains) help drive Lean approaches to
Maintenance. The Maintenance Value Chain approach is particularly successful when used as a
tool for helping Change Management as it is seen as more user friendly than other business
process tools.
Value chain approach could also offer a meaningful alternative to valuate private or public
companies when there is a lack of publically known data from direct competition, where the
subject company is compared with, for example, a known downstream industry to have a good
feel of its value by building useful correlations with its downstream companies.
Value chain analysis has also been employed in the development sector as a means of identifying
poverty reduction strategies by upgrading along the value chain. Although commonly associated
with export-oriented trade, development practitioners have begun to highlight the importance of
developing national and intra-regional chains in addition to international ones.
Business process reengineering
Business process re-engineering is the analysis and design of workflows and processes within
an organization. According to Davenport (1990) a business process is a set of logically related
tasks performed to achieve a defined business outcome. Re-engineering is the basis for many
recent developments in management. The cross-functional team, for example, has become
popular because of the desire to re-engineer separate functional tasks into complete cross-
functional processes. Also, many recent management information systems developments aim to
integrate a wide number of business functions. Enterprise resource planning, supply chain
management, knowledge management systems, groupware and collaborative systems, Human
Resource Management Systems and customer relationship management.
Business process re-engineering is also known as business process redesign, business
transformation, or business process change management.
Business Process Re-engineering (BPR) is basically the fundamental re-thinking and radical re-
design, made to an organization's existing resources. It is more than just business improvising.
It is an approach for redesigning the way work is done to better support the
organization's mission and reduce costs. Reengineering starts with a high-level assessment of the
organization's mission, strategic goals, and customer needs. Basic questions are asked, such as
"Does our mission need to be redefined? Are our strategic goals aligned with our mission? Who
are our customers?" An organization may find that it is operating on questionable assumptions,
particularly in terms of the wants and needs of its customers. Only after the organization rethinks
what it should be doing, does it go on to decide how best to do it.
Within the framework of this basic assessment of mission and goals, re-engineering focuses on
the organization's business processes—the steps and procedures that govern how resources are
used to create products and services that meet the needs of particular customers or markets. As a
structured ordering of work steps across time and place, a business process can be decomposed
into specific activities, measured, modeled, and improved. It can also be completely redesigned
or eliminated altogether. Re-engineering identifies, analyzes, and re-designs an organization's

10. core business processes with the aim of achieving dramatic improvements in critical performance
measures, such as cost, quality, service, and speed.
Re-engineering recognizes that an organization's business processes are usually fragmented into
sub processes and tasks that are carried out by several specialized functional areas within the
organization. Often, no one is responsible for the overall performance of the entire process. Re-
engineering maintains that optimizing the performance of sub processes can result in some
benefits, but cannot yield dramatic improvements if the process itself is fundamentally inefficient
and outmoded. For that reason, re-engineering focuses on re-designing the process as a whole in
order to achieve the greatest possible benefits to the organization and their customers. This drive
for realizing dramatic improvements by fundamentally re-thinking how the organization's work
should be done distinguishes re-engineering from process improvement efforts that focus on
functional or incremental improvement.
The role of information technology
Information technology (IT) has historically played an important role in the reengineering
concept. It is considered by some as a major enabler for new forms of working and collaborating
within an organization and across organizational borders.
Early BPR literature identified several so called disruptive technologies that were supposed to
challenge traditional wisdom about how work should be performed.
 Shared databases, making information available at many places
 Expert systems, allowing generalists to perform specialist tasks
 Telecommunication networks, allowing organizations to be centralized and decentralized at
the same time
 Decision-support tools, allowing decision-making to be a part of everybody's job
 Wireless data communication and portable computers, allowing field personnel to work
office independent
 Interactive videodisk, to get in immediate contact with potential buyers
 Automatic identification and tracking, allowing things to tell where they are, instead of
requiring to be found
 High performance computing, allowing on-the-fly planning and revisioning
In the mid 1990s, especially workflow management systems were considered as a significant
contributor to improved process efficiency. Also ERP (Enterprise Resource Planning) vendors,
such as SAP, JD Edwards, Oracle, PeopleSoft, positioned their solutions as vehicles for business
process redesign and improvement.
Benefiting from lessons learned from the early adopters, some BPR practitioners advocated a
change in emphasis to a customer-centric, as opposed to an IT-centric, methodology. One such
methodology, that also incorporated a Risk and Impact Assessment to account for the impact that
BPR can have on jobs and operations, was described by Lon Roberts (1994). Roberts also
stressed the use of change management tools to proactively address resistance to change—a

11. factor linked to the demise of many reengineering initiatives that looked good on the drawing
board.
Some items to use on a process analysis checklist are: Reduce handoffs, Centralize data, Reduce
delays, Free resources faster, Combine similar activities. Also within the management consulting
industry, a significant number of methodological approaches have been developed.
Adequate IT Infrastructure Researchers consider adequate IT infrastructure reassessment and
composition as a vital factor in successful BPR implementation (Al-Mashari & Zairi, 1999).
Hammer (1990) prescribes the use of IT to challenge the assumptions inherent in the work
process that have existed since long before the advent of modern computer and communications
technology (Malhotra, 1998). Factors related to IT infrastructure have been increasingly
considered by many researchers and practitioners as a vital component of successful BPR efforts
(Ross, 1998). Effective alignment of IT infrastructure and BPR strategy, building an effective IT
infrastructure, adequate IT infrastructure investment decision, adequate measurement of IT
infrastructure effectiveness, proper information systems (IS) integration, effective reengineering
of legacy IS, increasing IT function competency, and effective use of software tools are the most
important factors that contribute to the success of BPR projects. These are vital factors that
contribute to building an effective IT infrastructure for business processes (Al-Mashari & Zairi,
1999). BPR must be accompanied by strategic planning which addresses leveraging IT as a
competitive tool (Weicher, et al., 1995).
An IT infrastructure is made up of physical assets, intellectual assets, shared services (Broadbent
& Weill, 1997), and their linkages (Kayworth, et al., 1997). The way in which the IT
infrastructure components are composed and their linkages determines the extent to which
information resources can be delivered. An effective IT infrastructure composition process
follows a top-down approach, beginning with business strategy and IS strategy and passing
through designs of data, systems, and computer architecture (Malhotra, 1996). Linkages between
the IT infrastructure components, as well as descriptions of their contexts of interaction, are
important for ensuring integrity and consistency among the IT infrastructure components (Ross,
1998). Furthermore, IT standards have a major role in reconciling various infrastructure
components to provide shared IT services that are of a certain degree of effectiveness to support
business process applications, as well as to guide the process of acquiring, managing, and
utilizing IT assets (Kayworth, et al., 1997). The IT infrastructure shared services and the human
IT infrastructure components, in terms of their responsibilities and their needed expertise, are
both vital to the process of the IT infrastructure composition. IT strategic alignment is
approached through the process of integration between business and IT strategies, as well as
between IT and organizational infrastructures (Al-Mashari & Zairi, 1999).
Most analysts view BPR and IT as irrevocably linked. Walmart, for example, would not have
been able to reengineer the processes used to procure and distribute mass-market retail goods
without IT. Ford was able to decrease its headcount in the procurement department by 75 percent
by using IT in conjunction with BPR, in another well-known example (Weicher, et al., 1995).
The IT infrastructure and BPR are interdependent in the sense that deciding the information
requirements for the new business processes determines the IT infrastructure constituents, and a
recognition of IT capabilities provides alternatives for BPR (Ross, 1998). Building a responsive
IT infrastructure is highly dependent on an appropriate determination of business process

12. information needs. This, in turn, is determined by the types of activities embedded in a business
process, and their sequencing and reliance on other organizational processes (Sabherwal & King,
1991).
Ongoing Continuous Improvement Many organizational change theorists hold a common view
of organizations adjusting gradually and incrementally and responding locally to individual
crises as they arise (Dooley & Johnson, 2001). BPR is a successive and ongoing process and
should be regarded as an improvement strategy that enables an organization to make the move
from traditional functional orientation to one that aligns with strategic business processes
(Vakola & Rezgui, 2000). Continuous improvement is defined as the propensity of the
organization to pursue incremental and innovative improvements in its processes, products, and
services (Dooley & Johnson, 2001). The incremental change is governed by the knowledge
gained from each previous change cycle. It is essential that the automation infrastructure of the
BPR activity provides for performance measurements in order to support continuous
improvements. It will need to efficiently capture appropriate data and allow access to appropriate
individuals. To ensure that the process generates the desired benefits, it must be tested before it is
deployed to the end users. If it does not perform satisfactorily, more time should be taken to
modify the process until it does.
A fundamental concept for quality practitioners is the use of feedback loops at every step of the
process and an environment that encourages constant evaluation of results and individual efforts
to improve (Gore, 1999). At the end user’s level, there must be a proactive feedback mechanism
that provides for and facilitates resolutions of problems and issues. This will also contribute to a
continuous risk assessment and evaluation which are needed throughout the implementation
process to deal with any risks at their initial state and to ensure the success of the reengineering
efforts. Anticipating and planning for risk handling is important for dealing effectively with any
risk when it first occurs and as early as possible in the BPR process (Clemons, 1995). It is
interesting that many of the successful applications of reengineering described by its proponents
are in organizations practicing continuous improvement programs. Hammer and Champy (1993)
use the IBM Credit Corporation as well as Ford and Kodak, as examples of companies that
carried out BPR successfully due to the fact that they had long-running continuous improvement
programs (Gore, 1999).
In conclusion, successful BPR can potentially create substantial improvements in the way
organizations do business and can actually produce fundamental improvements for business
operations. However, in order to achieve that, there are some key success factors that must be
taken into consideration when performing BPR. BPR success factors are a collection of lessons
learned from reengineering projects and from these lessons common themes have emerged. In
addition, the ultimate success of BPR depends on the people who do it and on how well they can
be committed and motivated to be creative and to apply their detailed knowledge to the
reengineering initiative. Organizations planning to undertake BPR must take into consideration
the success factors of BPR in order to ensure that their reengineering related change efforts are
comprehensive, well-implemented, and have minimum chance of failure.

13. 4. Explain DFD & Data Dictionary? Explain in detail how the information requirement is
determined for an organization?
Ans.
Data flow diagram
A data flow diagram (DFD) is a graphical representation of the "flow" of data through
an information system, modeling its process aspects. Often they are a preliminary step used to
create an overview of the system which can later be elaborated. DFDs can also be used for
the visualization of data processing (structured design).
A DFD shows what kinds of data will be input to and output from the system, where the data will
come from and go to, and where the data will be stored. It does not show information about the
timing of processes, or information about whether processes will operate in sequence or in
parallel (which is shown on a flowchart).
It is common practice to draw the context-level data flow diagram first, which shows the
interaction between the system and external agents which act as data sources and data sinks. On
the context diagram the system's interactions with the outside world are modelled purely in terms
of data flows across the system boundary. The context diagram shows the entire system as a
single process, and gives no clues as to its internal organization.
This context-level DFD is next "exploded", to produce a Level 0 DFD that shows some of the
detail of the system being modeled. The Level 0 DFD shows how the system is divided into sub-
systems (processes), each of which deals with one or more of the data flows to or from an
external agent, and which together provide all of the functionality of the system as a whole. It
also identifies internal data stores that must be present in order for the system to do its job, and
shows the flow of data between the various parts of the system.
Data flow diagrams were proposed by Larry Constantine, the original developer of structured
design based on Martin and Estrin's "data flow graph" model of computation.
Data flow diagrams (DFDs) are one of the three essential perspectives of the structured-systems
analysis and design method SSADM. The sponsor of a project and the end users will need to be
briefed and consulted throughout all stages of a system's evolution. With a data flow diagram,
users are able to visualize how the system will operate, what the system will accomplish, and
how the system will be implemented. The old system's dataflow diagrams can be drawn up and
compared with the new system's data flow diagrams to draw comparisons to implement a more
efficient system. Data flow diagrams can be used to provide the end user with a physical idea of
where the data they input ultimately has an effect upon the structure of the whole system from
order to dispatch to report. How any system is developed can be determined through a data flow
diagram.
In the course of developing a set of levelled data flow diagrams the analyst/designers is forced to
address how the system may be decomposed into component sub-systems, and to identify
the transaction data in the data model.

14. There are different notations to draw data flow diagrams (Yourdon & Coad and Gane & Sarso),
defining different visual representations for processes, data stores, data flow, and external
entities.
Data dictionary
A data dictionary, or metadata repository, as defined in the IBM Dictionary of Computing, is a
"centralized repository of information about data such as meaning, relationships to other data,
origin, usage, and format."[1] The term may have one of several closely related meanings
pertaining to databases and database management systems (DBMS):
 a document describing a database or collection of databases
 an integral component of a DBMS that is required to determine its structure
 a piece of middleware that extends or supplants the native data dictionary of a DBMS
Documentation
The term Data Dictionary and Data Repository are used to indicate a more general software
utility than a catalogue. A Catalogue is closely coupled with the DBMS Software; it provides
the information stored in it to user and the DBA, but it is mainly accessed by the various
software modules of the DBMS itself, such as DDL and DML compilers, the query optimiser,
the transaction processor, report generators, and the constraint enforcer. On the other hand, a
Data Dictionary is a data structure that stores meta-data, i.e., data about data. The Software
package for a stand-alone Data Dictionary or Data Repository may interact with the software
modules of the DBMS, but it is mainly used by the Designers, Users and Administrators of a
computer system for information resource management. These systems are used to maintain
information on system hardware and software configuration, documentation, application and
users as well as other information relevant to system administration.
If a data dictionary system is used only by the designers, users, and administrators and not by the
DBMS Software , it is called a Passive Data Dictionary; otherwise, it is called an Active Data
Dictionary or Data Dictionary. An Active Data Dictionary is automatically updated as changes
occur in the database. A Passive Data Dictionary must be manually updated.
The data Dictionary consists of record types (tables) created in the database by systems
generated command files, tailored for each supported back-end DBMS. Command files contain
SQL Statements for CREATE TABLE, CREATE UNIQUE INDEX, ALTER TABLE (for
referential integrity), etc., using the specific statement required by that type of database.
Database users and application developers can benefit from an authoritative data dictionary
document that catalogs the organization, contents, and conventions of one or more
databases. This typically includes the names and descriptions of various tables and fields in each

15. database, plus additional details, like the type and length of each data element. There is no
universal standard as to the level of detail in such a document, but it is primarily a weak kind of
data.
The information requirement is determined for an organization
A data dictionary is a structured repository of data about data. It is a set of rigorous definitions
of all DFD data elements and data structures. Most of the data flow in the DFD are specified
here. Some of the most obvious ones are not shown here. The data dictionary entry for weekly
timesheet specifies that this data flow is composed of three basic data entities - the employee
name, employee ID and many occurrences of the two - tuple consisting of regular hours and
overtime hours. The data dictionary for this DFD is shown below:
Weekly timesheet = Emplyee_Name + Employee_ID + {Regular_hours + overtime_hours}
Pay_rate = {Horly | Daily | Weekly} + Dollar_amount
Employee_Name = Last + First + Middle_Initial
Employee_ID = digit + digit + digit + digit
Once we have constructed a DFD and its associated data dictionary, we have to somehow verify
that they are "correct". There can be no formal verification of a DFD, because what the DFD is
modeling is not formally specify anywhere against which verification can be done. Human
processes and rule of thumb must be used for verification. In addition to the walkthrough with
the client, the analyst should look for common errors. Some common errors are
1. Unlabeled data flows.
2. Missing data flows: Information required by a process is not available.
3. Extraneous data flows: Some information is not bein used in the process
4. Consistency not maintained during refinement
5. Missing processes
6. Contains some control information
The DFDs should be carefully scrutinized to make sure that all the processes in the physical
environment are shown in the DFD. It should also be ensured that none of the data flows is
actually carrying control information.

16. 5. What is ERP? Explain its existence before and its future after? What are the advantages
& Disadvantages of ERP? What is Artificial Intelligence? How is it different from Neural
Networks?
Ans.
Enterprise resource planning
Enterprise resource planning (ERP) systems integrate internal and external management
information across an entire organization, embracing finance/accounting, manufacturing, sales
and service, customer relationship management, etc. ERP systems automate this activity with an
integrated software application. Their purpose is to facilitate the flow of information between all
business functions inside the boundaries of the organization and manage the connections to
outside stakeholders.
ERP systems can run on a variety of computer hardware and network configurations, typically
employing a database as a repository for information.
Characteristics
ERP (Enterprise Resource Planning) systems typically include the following characteristics:
An integrated system that operates in real time (or next to real time), without relying on periodic
updates.
A common database, which supports all applications.
A consistent look and feel throughout each module.
Installation of the system without elaborate application/data integration by the Information
Technology (IT) department.
Connectivity to plant floor information
ERP systems connect to real–time data and transaction data in a variety of ways. These systems
are typically configured by systems integrators, who bring unique knowledge on process,
equipment, and vendor solutions.
Direct integration—ERP systems have connectivity (communications to plant floor equipment)
as part of their product offering. This requires the vendors to offer specific support for the plant

17. floor equipment that their customers operate. ERP vendors must be expert in their own products,
and connectivity to other vendor products, including competitors.
Database integration—ERP systems connect to plant floor data sources through staging tables in
a database. Plant floor systems deposit the necessary information into the database. The ERP
system reads the information in the table. The benefit of staging is that ERP vendors do not need
to master the complexities of equipment integration. Connectivity becomes the responsibility of
the systems integrator.
Enterprise appliance transaction modules (EATM)—These devices communicate directly
with plant floor equipment and with the ERP system via methods supported by the ERP system.
EATM can employ a staging table, Web Services, or system–specific program interfaces (APIs).
The benefit of an EATM is that it offers an off–the–shelf solution.
Custom–integration solutions—Many system integrators offer custom solutions. These systems
tend to have the highest level of initial integration cost, and can have a higher long term
maintenance and reliability costs. Long term costs can be minimized through careful system
testing and thorough documentation. Custom–integrated solutions typically run on workstation
or server class computers.
Implementation
ERP's scope usually implies significant changes to staff work processes and practices. Generally,
three types of services are available to help implement such changes—consulting, customization,
and support. Implementation time depends on business size, number of modules, customization,
the scope of process changes, and the readiness of the customer to take ownership for the project.
Modular ERP systems can be implemented in stages. The typical project for a large enterprise
consumes about 14 months and requires around 150 consultants. Small projects can require
months; multinational and other large implementations can take years. Customization can
substantially increase implementation times.
Process preparation
Implementing ERP typically requires changes in existing business processes.[14] Poor
understanding of needed process changes prior to starting implementation is a main reason for
project failure. It is therefore crucial that organizations thoroughly analyze business processes
before implementation. This analysis can identify opportunities for process modernization. It
also enables an assessment of the alignment of current processes with those provided by the ERP
system. Research indicates that the risk of business process mismatch is decreased by:

18. Linking current processes to the organization's strategy;
Analyzing the effectiveness of each process;
Understanding existing automated solutions.
ERP implementation is considerably more difficult (and politically charged) in decentralized
organizations, because they often have different processes, business rules, data semantics,
authorization hierarchies and decision centers. This may require migrating some business units
before others, delaying implementation to work through the necessary changes for each unit,
possibly reducing integration (e.g. linking via Master data management) or customizing the
system to meet specific needs.
A potential disadvantage is that adopting "standard" processes can lead to a loss of competitive
advantage. While this has happened, losses in one area are often offset by gains in other areas,
increasing overall competitive advantage.
Configuration
Configuring an ERP system is largely a matter of balancing the way the customer wants the
system to work with the way it was designed to work. ERP systems typically build many
changeable parameters that modify system operation. For example, an organization can select the
type of inventory accounting—FIFO or LIFO—to employ, whether to recognize revenue by
geographical unit, product line, or distribution channel and whether to pay for shipping costs
when a customer returns a purchase.
Customization
ERP systems are theoretically based on industry best practices and are intended to be deployed
"as is". ERP vendors do offer customers configuration options that allow organizations to
incorporate their own business rules but there are often functionality gaps remaining even after
the configuration is complete. ERP customers have several options to reconcile functionality
gaps, each with their own pros/cons. Technical solutions include rewriting part of the delivered
functionality, writing a homegrown bolt-on/add-on module within the ERP system, or interfacing
to an external system. All three of these options are varying degrees of system customization,
with the first being the most invasive and costly to maintain. Alternatively, there are non-
technical options such as changing business practices and/or organizational policies to better
match the delivered ERP functionality.
Key differences between customization and configuration include:
Customization is always optional, whereas the software must always be configured before use
(e.g., setting up cost/profit center structures, organizational trees, purchase approval rules, etc.)

19. The software was designed to handle various configurations, and behaves predictably in any
allowed configuration.
The effect of configuration changes on system behavior and performance is predictable and is the
responsibility of the ERP vendor. The effect of customization is less predictable, is the
customer's responsibility and increases testing activities.
Configuration changes survive upgrades to new software versions. Some customizations (e.g.
code that uses pre–defined "hooks" that are called before/after displaying data screens) survive
upgrades, though they require retesting. Other customizations (e.g. those involving changes to
fundamental data structures) are overwritten during upgrades and must be reimplemented[26].
Customization Advantages:
Improves user acceptance
Offers the potential to obtain competitive advantage vis-à-vis companies using only standard
features.
Customization Disadvantages:
Increases time and resources required to both implement and maintain.
Data becomes visible across the organization. Tasks that benefit from this integration
include:
• Sales forecasting, which allows inventory optimization
• Order tracking, from acceptance through fulfillment
• Revenue tracking, from invoice through cash receipt
• Matching purchase orders (what was ordered), inventory receipts (what arrived), and costing
(what the vendor invoiced)
Disadvantages of ERP
• Customization is problematic.
• Re–engineering business processes to fit the ERP system may damage competitiveness and/or
divert focus from other critical activities
• ERP can cost more than less integrated and/or less comprehensive solutions.
• High switching costs increase vendor negotiating power vis a vis support, maintenance and
upgrade expenses.
• Overcoming resistance to sharing sensitive information between departments can divert
management attention.
• Integration of truly independent businesses can create unnecessary dependencies.
• Extensive training requirements take resources from daily operations.

20. Artificial Intelligence
Artificial intelligence (AI) is the intelligence of machines and the branch of computer science
that aims to create it. AI textbooks define the field as "the study and design of intelligent agents"
where an intelligent agent is a system that perceives its environment and takes actions that
maximize its chances of success.
John McCarthy, who coined the term in 1956, defines it as "the science and engineering of
making intelligent machines.
Theoretical and computational neuroscience is the field concerned with the theoretical analysis
and computational modeling of biological neural systems. Since neural systems are intimately
related to cognitive processes and behaviour, the field is closely related to cognitive and
behavioural modeling.
The aim of the field is to create models of biological neural systems in order to understand how
biological systems work. To gain this understanding, neuroscientists strive to make a link
between observed biological processes (data), biologically plausible mechanisms for neural
processing and learning (biological neural network models) and theory (statistical learning
theory and information theory).

21. 6. Distinguish between closed decision making system & open decision making system?
What is – if ‘analysis? Why is more time spend in problem analysis & problem definition
as compared to the time spends on decision analysis?
Ans.
CLASSIFICATION OF DECISION MAKING SYSTEMS [MIS]
The decision making systems can be classified in a number of ways. There are two types of
systems based on the manager’s knowledge about the environment.
A. Closed decision making system:
If the manager operates in a known environment then it is a closed decision making system. The
conditions of the closed decision making system are:
(a) The manager has a known set of decision alternatives and knows their outcomes fully in
terms of value, if implemented.
(b) The manager has a model, a method or a rule whereby the decision alternatives can be
generated, tested, and ranked.
(c) The manager can choose one of them, based on some goal or objective.
A few examples are:
a product mix problem,
an examination system to declare pass or fail, or
an acceptance of the fixed deposits.
B. Open decision making system:
If the manager operates in an environment not known to him, then the decision making system is
termed as an open decision making system. The conditions of this system are:
(a) The manager does not know all the decision alternatives.
(b) The outcome of the decision is also not known fully. The knowledge of the outcome may be
a probabilistic one.
(c) No method, rule or model is available to study and finalize one decision among the set of
decision alternatives.

22. (d) It is difficult to decide an objective or a goal and, therefore, the manager resorts to that
decision, where his aspirations or desires are met best.
Deciding on the possible product diversification lines, the pricing of a new product, and the plant
location, are some decision making situations which fall in the category of the open decision
making systems.
The MIS tries to convert every open system to a closed decision making system by providing
information support for the best decision. The MIS gives the information support, whereby the
manager knows more and more about the environment and the outcomes, he is able to generate
the decision alternatives, test them and select one of them. A good MIS achieves this.
Open and Closed Systems
A system is commonly defined as a group of interacting units or elements that have a common
purpose. The units or elements of a system can be cogs, wires, people, computers, and so on.
Systems are generally classified as open systems and closed systems and they can take the form
of mechanical, biological, or social systems. Open systems refer to systems that interact with
other systems or the outside environment, whereas closed systems refer to systems having
relatively little interaction with other systems or the outside environment. For example, living
organisms are considered open systems because they take in substances from their environment
such as food and air and return other substances to their environment. Humans, for example,
inhale oxygen out of the environment and exhale carbon dioxide into the environment. Similarly,
some organizations consume raw materials in the production of products and emit finished goods
and pollution as a result. In contrast, a watch is an example of a closed system in that it is a
relatively self-contained, self-maintaining unit that has little interacts or exchange with its
environment.
All systems have boundaries, a fact that is immediately apparent in mechanical systems such as
the watch, but much less apparent in social systems such as organizations. The boundaries of
open systems, because they interact with other systems or environments, are more flexible than
those of closed systems, which are rigid and largely impenetrable. A closed-system perspective
views organizations as relatively independent of environmental influences. The closed-system
approach conceives of the organization as a system of management, technology, personnel,
equipment, and materials, but tends to exclude competitors, suppliers, distributors, and
governmental regulators. This approach allows managers and organizational theorists to analyze
problems by examining the internal structure of a business with little consideration of the
external environment. The closed-system perspective basically views an organization much as a
thermostat; limited environmental input outside of changes in temperature is required for
effective operation. Once set, thermostats require little maintenance in their ongoing, self-
reinforcing function. While the closed-system perspective was dominant through the 1960s,

23. organization scholarship and research subsequently emphasized the role of the environment. Up
through the 1960s, it was not that managers ignored the outside environment such as other
organizations, markets, government regulations and the like, but that their strategies and other
decision-making processes gave relatively little consideration to the impact these external forces
might have on the internal operations of the organization.
Open-systems theory originated in the natural sciences and subsequently spread to fields as
diverse as computer science, ecology, engineering, management, and psychotherapy. In contrast
to closed-systems, the open-system perspective views an organization as an entity that takes
inputs from the environment, transforms them, and releases them as outputs in tandem with
reciprocal effects on the organization itself along with the environment in which the organization
operates. That is, the organization becomes part and parcel of the environment in which it is
situated. Returning for a moment to the example of biological systems as open-systems, billions
of individual cells in the human body, themselves composed of thousands of individual parts and
processes, are essential for the viability of the larger body in which they are a part. In turn,
"macro-level" processes such as eating and breathing make the survival of individual cells
contingent on these larger processes. In much the same way, open-systems of organizations
accept that organizations are contingent on their environments and these environments are also
contingent on organizations.
As an open-systems approach spread among organizational theorists, managers began
incorporating these views into practice. Two early pioneers in this effort, Daniel Katz and Robert
Kahn, began viewing organizations as open social systems with specialized and interdependent
subsystems and processes of communication, feedback, and management linking the subsystems.
Katz and Kahn argued that the closed-system approach fails to take into account how
organizations are reciprocally dependent on external environments. For example, environmental
forces such as customers and competitors exert considerable influence on corporations,
highlighting the essential relationship between an organization and its environment as well as the
importance of maintaining external inputs to achieve a stable organization.
Furthermore, the open-system approach serves as a model of business activity; that is, business
as a process of transforming inputs to outputs while realizing that inputs are taken from the
external environment and outputs are placed into this same environment. Companies use inputs
such as labor, funds, equipment, and materials to produce goods or to provide services and they
design their subsystems to attain these goals. These subsystems are thus analogous to cells in the
body, the organization itself is analogous to the body, and external market and regulatory
conditions are analogous to environmental factors such as the quality of housing, drinking water,
air and availability of nourishment.
The production subsystem, for example, focuses on converting inputs into marketable outputs
and often constitutes a primary purpose of a company. The boundary subsystem's goal is to
obtain inputs or resources, such as employees, materials, equipment, and so forth, from the

24. environment outside of the company, which are necessary for the production subsystem. This
subsystem also is responsible for providing an organization with information about the
environment. This adaptive subsystem collects and processes information about a company's
operations with the goal of aiding the company's adaptation to external conditions in its
environment. Another subsystem, management, supervises and coordinates the other subsystems
to ensure that each subsystem functions efficiently. The management subsystem must resolve
conflicts, solve problems, allocate resources, and so on.
To simplify the process of evaluating environmental influences, some organizational theorists
use the term "task environment" to refer to aspects of the environment that are immediately
relevant to management decisions related to goal setting and goal realization. The task
environment includes customers, suppliers, competitors, employees, and regulatory bodies.
Furthermore, in contrast to closed-systems, the open-system perspective does not assume that the
environment is static. Instead, change is the rule rather than the exception. Consequently,
investigation of environmental stability and propensity to change is a key task of a company,
making the activities of an organization contingent on various environmental forces. As an open
system, an organization maintains its stability through feedback, which refers to information
about outputs that a system obtains as an input from its task environment. The feedback can be
positive or negative and can lead to changes in the way an organization transforms inputs to
outputs. Here, the organization acts as a thermostat, identified previously as an example of a
relatively closed-system. The difference between closed-systems and open-systems, then, is in
the complexity of environmental interactions. Closed-systems assume relatively little
complexity; a thermostat is a simple device dependent mainly on temperature fluctuations.
Conversely, open-system such as the human body and modern organizations are more intricately
dependent on their environments. The point is that closed-systems versus open-systems do not
represent a dichotomy, but rather a continuum along which organizations are more open or less
open to their environments. The key defining variable governing this degree of openness is the
complexity of the environment in which the organization is situated.
Managers must take into consideration their organization's position along the open-closed
continuum. The Linux computer operating system, for instance, is "open-source" and Red Hat,
Inc., the corporation selling the bundled revisions-the multiple inputs from geographically
dispersed users-represents an organization that would cease to exist if it were not for an open-
systems perspective. Thus, stable environments with low complexity are more consistent with a
relatively closed-system or mechanistic management style, while rapidly-changing environments
are more consistent with flexible, decentralized, or "organic" management styles.

25. SET 2
1. How hardware & software support in various MIS activities of the organization?
Explain the transaction stages from manual system to automated systems?
Ans.
Hardware support for MIS
Generally hardware in the form of personal computers and peripherals like
printers, fax machines, copier, scanners etc are used in organization
to support various MIS activities of the organization.
Advantages of a PC:
Advantages a personal computer offers are –
a) Speed – A PC can process data
at a very high speed. It can process millions of instructions within fraction of seconds.
b) Storage – A PC can store large quantity of data in a small space. It eliminates the need of
storing the conventional office flat files and box files which requires lots of space. The storage
system in a PC is such that the information can be transferred from place to another
place in electronic form.
c) Communication – A PC on the network can offer great support as a communicator in
communicating information in the forms of text and images. Today a PC with internet is used
as a powerful tool of communication for every business activity.
d) Accuracy – A PC is highly reliable in the sense that it could be used to perform
calculations continuously for hours with a great degree of accuracy. It is possible to obtain
mathematical results correct up to a great degree of accuracy.
e) Conferencing – A PC with internet offers facility of video conferencing worldwide.
Business people across the globe travel a lot to meet their business partner, colleagues,
customers etc to discuss about business activities.
By video conferencing inconvenience of traveling can be avoided.

26. Input unit is used to give input to the processor. Examples of input unit –Keyboard,
scanner, mouse, bar code reader etc.
A processor refers to unit which processes the input received the way it has been instructed. In a
computer the processor is the CPU – Central Processing Unit. It does all
mathematical calculations, logical tasks, storing details in the memory etc.
Output unit is used to give output s from the computer. Examples of output unit –Monitor,
printer, speakers etc.
Classification of computers:
Computers are classified as follows –
a) Depending upon the processor used – eg: Intel PI, PII, PIII, PIV, AMD, Celerons etc.
b) Depending upon the purpose for which it is used a Computer may be a general purpose
computer or a specific purpose computer. General purpose computers are the ones used
for general tasks like business analysis, letter typing, generating reports for
management decisions, scheduling activities, preparing balance sheets, invoice etc, Specific
purpose computers are custom build for specific tasks like space research, weather forecasting,
satellite sensing etc.
Unit computers are designed to perform tasks for which they are intended for and for no other
applications.
c) Depending upon the size: A computer may be classified based upon its size and
voluminous computing speed as micro computers, mini computers, main frames and super
computers. Super computer is the largest in size and also fastest in computing speed.

27. MIS (Managing Information Software) Software
MIS software helps for managing your accounts, inventory, taxation, payroll, stock, banking,
financial and other records.
MIS involves all aspects of gathering, storing, tracking, retrieving and using information within a
business or organization. All the policies, procedures, and practices that direct an organization's
operations and the staff that interact with the information, combined with the software and
hardware, comprise an information system.
MIS Software was developed specifically for the management and tracking of every transaction
in regulated environments. Our high-performance, relational database program tracks and
maintains accurate, real-time information, yet it is easy to implement and use.
This MIS Software manages your Daily Schedules, Job Summary, Inventory, Accounts and all
the Daily transaction. Records include Full Accounting and Inventory Features.
We offer complete custom development Information systems that can take care of business
operations.
Management Information (MIS), as it is popularly known, deals with the entry and exit of
information in a computer system specially designed for the business purpose. It has several
subcomponents like the Decision support system, marketing information system, financial
information system, HR information system, production information system and many more.
MIS Manager is a readily implementable solution, with capability to interface with any existing
Data source towards faster and efficient implementation and management. With capability to
deploy across the Enterprise, MIS Manager can provide the advantage of managing outputs and
Reports generated from various sources and technologies.
Our System Offers Complete Solutions, which include:
Cost Management
Product Development
Inventory Management
Integration with Accounting & Invoice Systems
Document Management System
MIS Features:
Speed of Deployment
Customer Support
Ease to Use
Functionality
Achievement of business goals

28. Many inventory reports are available. There are alphabetizing methods that can be used. You can
print physical inventory sheets, parts under minimum stocking quantity, value of inventory (by
sales category) and replacement cost.

29. 2. Explain the various behavioral factors of management organization? As per Porter, how
can performance of individual corporations be determined?
Ans.
Organizational behavior
Organizational behavior is the study of individuals and their actions within the context of
the organization in a workplace setting. It is an interdisciplinary field that includes sociology,
psychology, communication, and management; and it complements the academic studies
of organizational theory (which is more macro-level) and human resource studies (which is more
applied and business-related). It may also be referred to as organizational
studies or organizational science. The field has its roots in industrial and organizational
psychology.
Overview
Organizational studies encompass the study of organizations from multiple viewpoints, methods,
and levels of analysis. For instance, one textbook divides these multiple viewpoints into three
perspectives: modern, symbolic, and postmodern. Another traditional distinction, present
especially in American academia, is between the study of "micro" organizational behaviour —
which refers to individual and group dynamics in an organizational setting — and "macro"
strategic management and organizational theory which studies whole organizations and
industries, how they adapt, and the strategies, structures and contingencies that guide them. To
this distinction, some scholars have added an interest in "meso" scale structures - power, culture,
and the networks of individuals and i.e. ronit units in organizations — and "field" level analysis
which study how whole populations of organizations interact.
Whenever people interact in organizations, many factors come into play. Modern organizational
studies attempt to understand and model these factors. Like all modernist social sciences,
organizational studies seek to control, predict, and explain. There is some controversy over the
ethics of controlling workers' behavior, as well as the manner in which workers are treated (see
Taylor's scientific management approach compared to the human relations movement of the
1940s). As such, organizational behaviour or OB (and its cousin, Industrial psychology) have at
times been accused of being the scientific tool of the powerful.Those accusations
notwithstanding, OB can play a major role in organizational development, enhancing
organizational performance, as well as individual and group
performance/satisfaction/commitment.
One of the main goals of organizational theorists is, according to Simms (1994) "to revitalize
organizational theory and develop a better conceptualization of organizational life." An
organizational theorist should carefully consider levels assumptions being made in theory, and is
concerned to help managers and administrators.

30. While Classical philosophies rarely took upon a task of developing a specific theory of
organizations, some had used implicit conceptions of general organization in construct views on
politics and virtue; the Greek philosopher Plato, for example, wrote about the essence of
leadership, emphasized the importance of specialization and discussed a primordial form of
incentive structures in speculating how to get people to embody the goal of the just city in The
Republic. Aristotle also addressed such topics as persuasive communication. The writings of
16th century Italian philosopher Niccolò Machiavelli laid the foundation for contemporary work
on organizational power and politics. In 1776, Adam Smith advocated a new form of
organizational structure based on the division of labour. One hundred years later, German
sociologist Max Weber wrote about rational organizations and initiated discussion of charismatic
leadership. Soon after, Frederick Winslow Taylor introduced the systematic use of goal setting
and rewards to motivate employees. In the 1920s, Australian-born Harvard professor Elton
Mayo and his colleagues conducted productivity studies at Western Electric's Hawthorne plant in
the United States.
Though it traces its roots back to Max Weber and earlier, organizational studies began as an
academic discipline with the advent of scientific management in the 1890s,
with Taylorism representing the peak of this movement. Proponents of scientific management
held that rationalizing the organization with precise sets of instructions and time-motion studies
would lead to increased productivity. Studies of different compensation systems were carried
out.
After the First World War, the focus of organizational studies shifted to how human factors and
psychology affected organizations, a transformation propelled by the identification of
the Hawthorne Effect. This Human Relations Movement focused on teams, motivation, and the
actualization of the goals of individuals within organizations.
Prominent early scholars included Chester Barnard, Henri Fayol, Frederick Herzberg, Abraham
Maslow, David McClelland, and Victor Vroom.
The Second World War further shifted the field, as the invention of large-scale logistics
and operations research led to a renewed interest in rationalist approaches to the study of
organizations. Interest grew in theory and methods native to the sciences, including systems
theory, the study of organizations with a complexity theory perspective and complexity strategy.
Influential work was done by Herbert Alexander Simon and James G. March and the so-called
"Carnegie School" of organizational behavior.
In the 1960s and 1970s, the field was strongly influenced by social psychology and the emphasis
in academic study was on quantitative research. An explosion of theorizing, much of it at
Stanford University and Carnegie Mellon, produced Bounded Rationality, Informal
Organization, Contingency Theory, Resource Dependence, Institutional Theory,
and Organizational Ecology theories, among many others.
Starting in the 1980s, cultural explanations of organizations and change became an important
part of study. Qualitative methods of study became more acceptable, informed
by anthropology,psychology and sociology. A leading scholar was Karl Weick.

31. Methods used in organizational studies
A variety of methods are used in organizational studies. They include quantitative methods found
in other social sciences such as multiple regression, non-parametric statistics, time series
analysis,Meta-analysis and ANOVA. In addition, computer simulation in organizational
studies has a long history in organizational studies. Qualitative methods are also used, such
as ethnography, which involves direct participant observation, single and multiple case analysis,
grounded theory approaches, and other historical methods. Fred Arthur.
Systems framework
The systems framework is also fundamental to organizational theory as organizations are
complex dynamic goal-oriented processes. One of the early thinkers in the field was Alexander
Bogdanov, who developed his Tectology, a theory widely considered a precursor of Bertalanffy's
General Systems Theory, aiming to model and design human organizations. Kurt Lewin was
particularly influential in developing the systems perspective within organizational theory and
coined the term "systems of ideology", from his frustration with behavioural psychologies that
became an obstacle to sustainable work in psychology (see Ash 1992: 198-207). The complexity
theory perspective on organizations is another systems view of organizations.
The systems approach to organizations relies heavily upon achieving negative
entropy through openness and feedback. A systemic view on organizations is transdisciplinary
and integrative. In other words, it transcends the perspectives of individual disciplines,
integrating them on the basis of a common "code", or more exactly, on the basis of the formal
apparatus provided by systems theory. The systems approach gives primacy to the
interrelationships, not to the elements of the system. It is from these dynamic interrelationships
that new properties of the system emerge. In recent years,systems thinking has been developed to
provide techniques for studying systems in holistic ways to supplement
traditional reductionistic methods. In this more recent tradition, systems theory in organizational
studies is considered by some as a humanistic extension of the natural sciences.
Managerial roles
In the late 1960s Henry Mintzberg, a graduate student at MIT undertook a careful study of five
executives to determine what those managers did on their jobs. On the basis of his observations,
Mintzberg classifies managerial roles into 3 categories
1. Interpersonal Roles
2. Decisional Roles
3. Informational Roles
 Rational Decision-Making Model
 Scientific management
 Garbage can model

32. Theories of decision making can be subdivided into three categories
 Normative (concentrates on how decision should be made)
 Descriptive (concerned with how the thinker came up with their judgement)
 Prescripted (aim to improve decision making)
Motivation in organizations
Motivation the forces either internal or external to a person that arouse enthusiasm and resistance
to pursue a certain course of action. According to Baron et al. (2008):[ "Although motivation is a
broad and complex concept, organizational scientists have agreed on its basic characteristics.
Drawing from various social sciences, we define motivation as the set of processes that arouse,
direct, and maintain human behavior toward attaining some goal"

33. 3. Compare various types of development aspect of Information System? Explain the
various stages of SDLC?
Ans.
The Various Types of Information Systems Analysis Projects
There are three types of information systems projects: manual, manual to automated, and
reautomation. The last, reautomation, has four subtypes: system rewrite, system redesign and
redevelopment, system enhancement, and system maintenance. Each of these involves different,
and yet similar, work. The work is similar in that the development activities which are involved
in each follow the same general phases and approach. They are different in that the environment
that the analyst must examine has substantially different characteristics.
This chapter examines each of the various types of analysis projects, along with a brief
discussion of the Gibson-Nolan electronic data processing (EDP) stages of growth theory and its
impact on the analysis process. In addition there is a brief discussion of the Anthony model of
organizational structure.
A definition
Personal Computer (PC) - also known as microcomputers or workstations, by the model name of
the specific vendor (i.e. Apple , Macintosh , or PS/2 or by the brand name, model and speed of
the processor (i.e. Pentium, Intel or 486/33 Any combination of processor, input device and
output device designed for use by a single individual. Personal computers may also be called
workstations.
Personal computers may have a character orientation, a graphical orientation, may be connected
to other personal computers, or may operate in a stand alone mode, and may or may not have
connectivity to a mainframe.
Personal computer software is normally characterized by an operating system which provides
basic file access, management and display services and well as application scheduling and
management.
Reasons For Initiating Information Systems Analysis Projects
Information systems analysis projects are initiated for a variety of reasons. These include:
As part of a program of System Modernization.
Many firms undertake a series of projects to upgrade all data processing technology - both
hardware, operating system and support software and automated business applications. This is

34. usually initiated as part of a desire to eliminate the older centralized applications and to replace
them with newer personal computer based system.
A change in the basic aspects of the user's functional role
As the companies redesign their basic processes either as a result of a continuous improvement
effort, or a more radical Business Process Reengineering effort
A change in company strategic objectives
Increased competition, both in the local and international markets have forced many firms to
rethink not only how they do business but also what business they should be in. In some
instances, manufacturing firms are becoming service firms, primary producers are becoming
assemblers of components produced by others, companies are changing their lines of business,
and reexamining the customer base they are focused on. Large firms are divesting themselves of
divisions and whole product lines and reverting back to what they feel are their core businesses.
A need for increased performance, greater or different functionality, different operating
characteristics, or increased user friendliness from the automated systems
As business conditions change, there are increased user demands for greater or in some cases
different functionality from the exiting systems. Increased user computer literacy, and exposure
to PC applications with Graphical User Interfaces (GUI) have changed user expectations for and
tolerance of sometimes awkward, character based systems.
A need for more direct and immediate access to the firm's automated files.
The exposure to the wide variety of workstation based tools and systems. Most user
workstations or PCs have extensive files of their own. The data in these files may have come
from information keyed in by the user, transferred to the user’s machine from another user
machine via diskette, or down-loaded to the user’s machine from either another workstation or
from a mini-computer or mainframe via a file transfer mechanism. These transfers are time
consuming and awkward. Users are increasingly looking for faster access to data regardless of
where it resides.
A need to upgrade the system to take advantage of more current technology.
Vendors are increasing the power (speed and capacity) of their offerings. Capacity includes both
Random Access Memory (RAM) and hard drive storage. The speed, capacity and variety of
peripheral equipment (printers, plotters, scanners, fax, CD-ROM (Compact Disk - Read Only
Memory), high resolution monitors, etc.) continues to expand as well. As capacity and speed
increase and as more and more peripheral capability becomes available the variety of
applications available increases as well and users rush to acquire these new tools.
A need to clean up the system -

35. All computer systems tend to get cluttered over time with a patchwork of add-on modules, files,
and processes. These pieces do not work together in a harmonious manner but rather interact
awkwardly and inefficiently.
Given the above, we can no long assume that a systems analysis project has been undertaken as
the first step toward developing a new or improved .application. Nor can we assume that many
of the constraints that applied to the development of mainframe systems are still in effect. In fact
we can no longer assume that we will be developing a mainframe resident system at all. Today’s
systems can reside on a variety of hardware platforms and take a variety of forms.
The Three Types of Information Systems Analysis Projects
The scope and magnitude of the functional and procedural changes may be fairly narrow or wide
ranging. In some cases, aside from re-coding the system, there may be no changes in
functionality at all.
Given the variety of reasons for a project being undertaken, the starting point may also be quite
different from project to project. These starting points reflect the differences in current user
processing environments and the current level of user automation. Because of these differences
in current user processing environments and user automation, information systems projects can
be categorized into three types.
1. Manual
2. Manual to automated
3. Re automation
4. The last, re automation, has four subtypes.
a) System rewrite
b) System redesign and redevelopment
c) System enhancement
d) System maintenance
From an analysis perspective, each of these types of projects involves different, and yet similar,
work. The work is similar in that the development activities, which are involved in each, follow
the same general phases and approach. They are different in that each of the starting or current
environments that the analyst must examine have substantially different characteristics. Briefly,
these six environmental types and subtypes are as follows.

36. Manual
From the analyst's viewpoint, this is the simplest environment in that all the components of the
environment are overt. That is, they are clearly visible from observation and analysis. All work is
performed by user personnel, who work directly with their files, forms, and documents. The
processing of these forms and documents, the work flows, and the individual steps are easily
followed.
At their core all systems analysis projects are concerned with the examination of what are, or
once were, essentially manual operations. In fact, it is helpful, regardless of the type of project,
to view all the activities of the user as if they were still being performed by hand. This allows the
analyst to examine in detail each task being performed, each data operation, each data
movement, and each data carrier (a data carrier is a piece of paper, a form, a report, a worksheet,
a transaction, etc.).
The analyst's task in the manual environment is to simplify the work flows, streamline the
processes, reduce redundant processing, rearrange the tasks so as to ensure more orderly
processing, and ensure that the forms, documents, and reports contain all necessary data. Each
task, and each task step, must be examined to determine (a) if its execution is appropriate and (b)
if it is appropriately defined, positioned, and performed.
The results of the analysis of manual systems are usually new or revised standards and
procedures which clearly define the processing sequence for the task to be performed and the
rules which govern their performance. In addition the analyst may develop new input forms,
control procedures, monitoring procedures, and reports. The output from the analysis may also
include new or revised work and data flow diagrams.
Manual to automated
Working in this type of environment differs from working in the strictly manual environment in
that the analyst's task is to determine whether the manual environment, in whole or in part, can
be augmented by automation, and if so, to what extent. The existing environment must be
analyzed in the same manner as the purely manual, but as the analysis progresses, the analyst
must also find ways of substituting automated processing for manual processing. To accomplish
this, the analyst must break each process and task into its component steps and determine if the
rules for performing the step lend themselves to machine automation.
The analyst's output for this type of project closely resembles that produced from the strictly
manual project. However, here the analyst must also develop (a) new, input forms suitable to an
automated environment, (b) file content requirements for ongoing master and transaction files,
(c) report layouts, and (d) a processing flow which intermixes the original and unmodified
manual processes, new manual processes, and new automated processes. The analyst must also
make a determination as to the costs involved in the automation process, provide project
schedules, and make hardware and software analyses and recommendations.

37. Reautomation
There have been many attempts to set down analytical and design methodologies for
development projects in automated environments. What many of them ignore is that there are
different types of automated business environments, which, while seemingly similar, must in fact
be treated differently.
What distinguishes these environments is the extent and depth of automation. Early analysis
methodologies were predicated on a manual environment. The aim of the analysis was to
develop an automated solution to user business problems. In today's environment, most firms of
any size have existing levels of automation. Many in fact have gone through two and three
rounds of automation and reautomation.
Many of the existing processes and procedures are either totally automated or were developed as
a result of a partial automation of the user area. Many of the forms and transaction flows within
this type of environment are automated or semi-automated.
This prior automation poses a trap for the unwary analyst in that the currently used forms and
documents of the business may in fact have been designed to support and accommodate an
automated system. These automated systems may have been designed for the business using a
level of technology which is now outdated or inefficient, or for a set of user requirements or a
business environment which has since become wholly or partially obsolete. Additionally, these
forms and documents are the result of some prior analyst's efforts and may not in fact reflect the
natural information or data needs of the firm.
The processing flows themselves may be unnatural, to the extent that they reflect the intrusion of
automated processing sequences. These flows may have been structured to accommodate the
needs of the then prevalent technology rather than the needs of the business. Each of the
documents, transactions and process flows must be reexamined in the light of the current
business environment and the current business processing needs. They may merely need to be
refurbished, or they may need to be scrapped entirely in favor of a new and more streamlined
processing flow.
The analyst must look with care on batch flows, "processing windows," and transaction holding
queues. These constraints may have been imposed on the processing environment by the
requirements of prior automation efforts, most probably implemented under what is now an
outdated, or, worse, obsolete technology. Re automation is a major type of project which
incorporates the following sub-categories.
Platform is the term used to distinguish between the different classes or sizes of computing
machinery –mainframe, minicomputer and microcomputer (or personal computer or
workstation), between the various operating systems on each machine, and in some cases
between stand-alone machines and networked machines.
In some cases the term platform is used to distinguish between one combination of machine and
software and some other combination.

38. Throughout this book we will use the qualified term hardware platform to represent differences
in computing machinery and the qualified term software platform to represent differences in
operating systems on a given class of machinery.
The Corporate level
This level consists those information and business systems which are designed for use by all
areas of the corporation. These systems are normally characterized by:
1. Specific functional area responsibility
2. Centralized development and maintenance
3. Requirements that conform to and are constrained by corporate-wide policies and
procedures
4. Cross-function or cross-business boundary use
5. Mainframe or Minicomputer residence
6. Supported by additional, non-automated forms
7. Augmented by extensive manual procedures.
The Departmental Level
This level consists of information and business systems which are designed for use by a specific
area or areas of the corporation. These systems are normally characterized by:
1. Specific functional area responsibility
2. Central development and maintenance, local development and maintenance or vendor
supplied and supported
3. Support for a single function or activity
4. Minicomputer or Mainframe residence
The Personal Level
This level consists of information and business systems which are designed for use by a single
individual. These systems are normally characterized by:
1. Personal computer residence
2. Support for a single user
3. Customized processing or general facility
4. Customized settings.
5. User built or vendor supplied and maintained.

39. 4. Compare & Contrast E-enterprise business model with traditional business organization
model? Explain how in E-enterprise manager role & responsibilities are changed? Explain
how manager is a knowledge worker in E-enterprise?
Ans.
Business process modeling
Business Process Modeling (BPM) in systems engineering is the activity of representing
processes of an enterprise, so that the current process may be analyzed and improved. BPM is
typically performed by business analysts and managers who are seeking to improve process
efficiency and quality. The process improvements identified by BPM may or may not require
Information Technology involvement, although that is a common driver for the need to model a
business process, by creating a process master.
Change management programs are typically involved to put the improved business processes
into practice. With advances in technology from large platform vendors, the vision of BPM
models becoming fully executable (and capable of simulations and round-trip engineering) is
coming closer to reality every day.
Techniques to model business process such as the flow chart, functional flow block
diagram, control flow diagram, Gantt chart, PERT diagram, and IDEF have emerged since the
beginning of the 20th century. The Gantt charts were among the first to arrive around 1899, the
flow charts in the 1920s, Functional Flow Block Diagram and PERT in the 1950s, Data Flow
Diagrams and IDEF in the 1970s. Among the modern methods are Unified Modeling
Language and Business Process Modeling Notation. Still, these represent just a fraction of the
methodologies used over the years to document business processes.[1] The term "business process
modeling" itself was coined in the 1960s in the field of systems engineering by S. Williams in

40. his 1967 article "Business Process Modeling Improves Administrative Control".[2] His idea was
that techniques for obtaining a better understanding of physical control systems could be used in
a similar way for business processes. It took until the 1990s before the term became popular.
In the 1990s the term "process" became a new productivity paradigm.[3] Companies were
encouraged to think in processes instead of functions and procedures. Process thinking looks at
the chain of events in the company from purchase to supply, from order retrieval to sales etc. The
traditional modeling tools were developed to picture time and costs, while modern methods focus
on cross-function activities. These cross-functional activities have increased severely in number
and importance due to the growth of complexity and dependencies. New methodologies such
as business process redesign, business process innovation, business process
management, integrated business planning among others all "aiming at improving processes
across the traditional functions that comprise a company".
In the field of software engineering the term "business process modeling" opposed the
common software process modeling, aiming to focus more on the state of the practice
during software development. In that time early 1990s all existing and new modeling techniques
to picture business processes were considered and called "business process modeling languages."
In the Object Oriented approach, it was considered to be an essential step in the specification of
Business Application Systems. Business process modeling became the base of new
methodologies, that for example also supported data collection, data flow analysis, process flow
diagrams and reporting facilities. Around 1995 the first visually oriented tools for business
process modeling and implementation were being presented.
Business process
A business process is a collection of related, structured activities or tasks that produce a specific
service or product (serve a particular goal) for a particular customer or customers. There are
three main types of business processes:
1. Management processes, the processes that govern the operation of a system. Typical
management processes include "Corporate Governance" and "Strategic Management".
2. Operational processes, processes that constitute the core business and create the primary
value stream. Typical operational processes are Purchasing, Manufacturing, Marketing,
and Sales.
3. Supporting processes, which support the core processes. Examples
include Accounting, Recruitment, Technical support.

41. A business process can be decomposed into several sub-processes, which have their own
attributes, but also contribute to achieving the goal of the super-process. The analysis of business
processes typically includes the mapping of processes and sub-processes down to activity level.
A business process model is a model of one or more business processes, and defines the ways in
which operations are carried out to accomplish the intended objectives of an organization. Such a
model remains an abstraction and depends on the intended use of the model. It can describe the
workflow or the integration between business processes. It can be constructed in multiple levels.
A business reference model is a reference model, concentrating on the functional and
organizational aspects of an enterprise, service organization or government agency. In general
a reference model is a model of something that embodies the basic goal or idea of something and
can then be looked at as a reference for various purposes. A business reference model is a means
to describe the business operations of an organization, independent of the organizational
structure that perform them. Other types of business reference model can also depict the
relationship between the business processes, business functions, and the business area’s business
reference model. These reference models can be constructed in layers, and offer a foundation for
the analysis of service components, technology, data, and performance.
The most familiar business reference model is the Business Reference Model of the US Federal
Government. That model is a function-driven framework for describing the business operations
of the Federal Government independent of the agencies that perform them. The Business
Reference Model provides an organized, hierarchical construct for describing the day-to-day
business operations of the Federal government. While many models exist for describing
organizations - organizational charts, location maps, etc. - this model presents the business using
a functionally driven approach.
A business model, which may be considered an elaboration of a business process model,
typically shows business data and business organizations as well as business processes. By
showing business processes and their information flows a business model allows business
stakeholders to define, understand, and validate their business enterprise. The data model part of
the business model shows how business information is stored, which is useful for
developing software code. See the figure on the right for an example of the interaction between
business process models and data models.
Usually a business model is created after conducting an interview, which is part of the business
analysis process. The interview consists of a facilitator asking a series of questions to extract
information about the subject business process. The interviewer is referred to as a facilitator to
emphasize that it is the participants, not the facilitator, who provide the business process

42. information. Although the facilitator should have some knowledge of the subject business
process, but this is not as important as the mastery of a pragmatic and rigorous method
interviewing business experts. The method is important because for most enterprises a team of
facilitators is needed to collect information across the enterprise, and the findings of all the
interviewers must be compiled and integrated once completed.
Business models are developed as defining either the current state of the process, in which case
the final product is called the "as is" snapshot model, or a concept of what the process should
become, resulting in a "to be" model. By comparing and contrasting "as is" and "to be" models
the business analysts can determine if the existing business processes and information systems
are sound and only need minor modifications, or if reengineering is required to correct problems
or improve efficiency. Consequently, business process modeling and subsequent analysis can be
used to fundamentally reshape the way an enterprise conducts its operations.
Business process reengineering (BPR) is an approach aiming at improvements by means of
elevating efficiency and effectiveness of the processes that exist within and across organizations.
The key to business process reengineering is for organizations to look at their business processes
from a "clean slate" perspective and determine how they can best construct these processes to
improve how they conduct business.
Business process reengineering (BPR) began as a private sector technique to help organizations
fundamentally rethink how they do their work in order to dramatically improve customer service,
cut operational costs, and become world-class competitors. A key stimulus for reengineering has
been the continuing development and deployment of sophisticated information systems and
networks. Leading organizations are becoming bolder in using this technology to support
innovative business processes, rather than refining current ways of doing work
Business process management
Business process management is a field of management focused on aligning organizations with
the wants and needs of clients. It is a holistic management approach that promotes business
effectiveness and efficiency while striving for innovation, flexibility and integration with
technology. As organizations strive for attainment of their objectives, business process
management attempts to continuously improve processes - the process to define measure and
improve your processes – a "process optimization" process.