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THE EFFECTIVENESS OF SAP IMPLEMENTATION IN FINANCE
         DEPARTMENT WITH REFERENCE TO
        SOUTH INDIAN CORPORATION (P) LTD


                                By


                       DINESH BABU T


                         0702MBA2003
                          68107201009

                    A PROJECT REPORT


                        Submitted to the


        FACULTY OF MANAGEMENT SCIENCES


        in partial fulfillment for the award of the degree


                               of


        MASTER OF BUSINESS ADMINISTRATION




          CENTRE FOR DISTANCE EDUCATION
             ANNA UNIVERSITY CHENNAI
                 CHENNAI 600 025


                           July, 2009
BONAFIDE CERTIFICATE


Certified that the Project report titled _________________________________________
_______________________________________________________________________
is the bonafide work of Mr. / Ms. ________________________________who carried out
the work under my supervision. Certified further that to the best of my knowledge the
work reported herein does not form part of any other project report or dissertation on the
basis of which a degree or award was conferred on an earlier occasion on this or any
other candidate.




       Signature of student                                 Signature of Guide

       Name: T DINESH BABU                                  Name: Mr. D JAYAKUMAR
       Roll No: 0702MBA2003                                 Designation: ERP Consultant
       Reg No: 68107201009                                  Address: Anna University




                              Signature of Project-in-charge

                              Name: Mrs A THIRUCHELVI
                              Designation: Professor, Anna University




                                                                   ii
Certificate of Viva-voce-Examination


This is to certify that Thiru/Ms. /Tmt ………………………………….............................
(Roll No……………….…….; Register No. …………………….) has been subjected to
Viva-voce-Examination on …………………… (Date) at …………….. (Time) at the
Study centre ……………………………………………………………..……………......
……………………………………………………………… ……………………………
(Name and Address of the Study centre).




             Internal Examiner                         External Examiner

             Name:                                     Name:
             Designation:                              Designation:
             Address:                                  Address:




                                  Coordinator Study centre

                                  Name:
                                  Designation:
                                  Address:
                                  Date:




                                                             iii
ACKNOWLEDGEMENT


I am thankful to South Indian Corporation India (P) Ltd, which has imparted me
sufficient knowledge and confidence to complete the project successfully in the field of
corporate training.


I express my special thanks to My Parents and Family Members for the constant support
and encouragement extended to me in completing this project on time.


I would especially like to express my gratitude towards Mr. D. JAYAKUMAR,
ERP Consultant, Sun Direct Television P Ltd, who was my project guide and
Mrs. A. THIRUCHELVI, Professor, Dept of Management Studies, Anna University,
who was my Project-in-charge for all the support and constant feedback on my progress
made during the project.


I would also like to thank Mr. JASON PEARCE, Operations Head, NewGen and all
office staff for their support and encouragement, which helped me to complete this
project successfully.


I extend my heart felt thanks to Ms. S NIRMALA, H.O.D, Department of Computer
Science and Engineering, I.F.ET College of Engg for encouraging me towards the
professional degree in Management Studies.


My heart felt thanks to all the noble hearts that has helped me to do complete this project
successfully.



Place: Chennai
Date:                                                   (DINESH BABU T)



                                                                  iv
ABSTRACT




The project work has been undertaken at South Indian Corporation (P) Ltd.


The project is titled as “THE EFFECTIVENESS OF SAP IMPLEMENTATION IN
FINANCE DEPARTMENT” with reference to South Indian Corporation (P) Ltd


The objective of this project is the effectiveness of sap implementation measures of
employees of in South Indian Corporation (P) Ltd


Sampling technique used is Random sampling and the sample size is 250.


A statistical tool like t-test, correlation & chi-square test used for analysis and
interpretation was carried out by using percentage method, and weighted average method.


The collected data are tabulated, analyzed and interpreted. Finally the results are given as
findings and recommendations to the company for better prospects.




                                                                    v
CHAPTER NO                    CONTENTS                PAGE
                                                       NO

             LIST OF TABLES                            vii
             LIST OF CHARTS                            viii


     I       1.1 INTRODUCTION                           2
             1.2 SCOPE OF THE STUDY                     5
             1.3 IMPORTANCE OF THE STUDY                6
             1.4 OBJECTIVE OF THE RESEARCH              7
                    • PRIMARY OBJECTIVE
                    • SECONDARY OBJECTIVE
             1.5 RESEARCH DESIGN                        8
             1.6 SAMPLING DESIGN                       10
             1.7 HYPOTHESIS                            14
             1.8 EXPECTED CONTRIBUTION OF THE STUDY    15
             1.9 LIMITATIONS OF THE STUDY              16



    II       THEORETICAL ANALYSIS

             2.1 COMPANY PROFILE                       18
             2.2 PRODUCT PROFILE                       20
             2.3 REVIEW OF LITERATURE                  22



    III      3.1 DATA ANALYSIS & INTERPRETATION        30
             3.2 STATISTICAL TOOLS FOR ANALYSIS        50



    IV       4.1 FINDINGS                              58
             4.2 SUGGETIONS                            60
             4.3 CONCLUSION                            61

             BIBLIOGRAPHY                              62
             ANNEXTURES                                63




                                             vi
LIST OF TABLES



S No                               PARTICULARS                                Page No
 1.    Distribution of respondents based on Gender                              30
 2.    Distribution of respondents based on Age                                 31
 3.    Distribution of respondents based on Software package using              32
 4.    Distribution of respondents based on Experience held                     33
 5.    Distribution of respondents based on Full filled requirements            34
 6.    Distribution of respondents based on Time efficient                      35
 7.    Distribution of respondents based on Implementation cost                 36
 8.    Distribution of respondents based on Confidentiality                     37
 9.    Distribution of respondents based on Quality of service                  38
10.    Distribution of respondents based on Data lossage                        39
11.    Distribution of respondents based on Initial training of respondents     40
12.    Distribution of respondents based on Training duration                   41
13.    Distribution of respondents based on Expecting training                  42
14.    Distribution of respondents based on Additional training                 43
15.    Distribution of respondents based on Emerging technology                 44
16.    Distribution of respondents based on Co-ordination between dept.,        45
17.    Distribution of respondents based on Technology driven                   46
18.    Distribution of respondents based on Complete package of sap             47
19.    Distribution of respondents based on Satisfaction level                  48
20.    Distribution of respondents based on Usage of SAP                        49
21.    Correlation                                                              50
22.    Chi-Square                                                               51
23.    Sample Kolmogorov-Smirnov Test                                           53
24.    ANOVA                                                                    54
25.    Paired Samples Statistics                                                55




                                                                vii
LIST OF CHARTS



S No                             PARTICULARS                                  Page No
 1.    Distribution of respondents based on Gender                             30
 2.    Distribution of respondents based on Age                                31
 3.    Distribution of respondents based on Software package using             32
 4.    Distribution of respondents based on Experience held                    33
 5.    Distribution of respondents based on Full filled requirements           34
 6.    Distribution of respondents based on Time efficient                     35
 7.    Distribution of respondents based on Implementation cost                36
 8.    Distribution of respondents based on Confidentiality                    37
 9.    Distribution of respondents based on Quality of service                 38
10.    Distribution of respondents based on Data lossage                       39
11.    Distribution of respondents based on Initial training of respondents    40
12.    Distribution of respondents based on Training duration                  41
13.    Distribution of respondents based on Expecting training                 42
14.    Distribution of respondents based on Additional training                43
15.    Distribution of respondents based on Emerging technology                44
16.    Distribution of respondents based on Co-ordination between dept.,       45
17.    Distribution of respondents based on Technology driven                  46
18.    Distribution of respondents based on Complete package of sap            47
19.    Distribution of respondents based on Satisfaction level                 48
20.    Distribution of respondents based on Usage of SAP                       49




                                                                viii
CHAPTER I

INTRODUCTION
1.1 INTRODUCTION

An Introduction to SAP

                       SAP was founded in 1972 in Walldorf, Germany. It stands for
Systems, Applications and Products in Data Processing. Over the years, it has grown and
devolved to become the world premier provider of client/server business solutions for
which it is so well known today. The SAP R/3 enterprise application suite for open client/
server systems has established a new standard for providing business information
management solutions.

SAP products are considered excellent but not perfect. The main problem with software
product is that it can never be perfect.

The main advantage of using SAP as your company ERP system is that SAP have a very
high level of integration among its individual applications which guarantee consistency
of data throughout the system and the company itself.

In a standard SAP project system, it is divided into three environments, Development,
Quality Assurance and Production.

 The development system is where most of the implementation work takes place. The
quality assurance system is where all the final testing is conducted before moving the
transports to the production environment. The production system is where all the daily
business activities occur. It is also the client that all the end users use to perform their
daily job functions.

To all company, the production system should only contain transport that has passed all
the tests. SAP is table drive customization software. It allows businesses to make rapid
changes in their business requirements with a common set of programs. User-exits are
provided for business to add in additional source code. Tools such as screen variants are
provided to let you set fields attributes whether to hide, display and make them
mandatory fields.

This is what makes ERP system and SAP in particular so flexible. The table driven
customization are driving the program functionality instead of those old fashioned hard-
coded programs. Therefore, new and changed business requirements can be quickly
implemented and tested in the system.

Many other business application software have seen this table driven customization
advantage and are now changing their application software based on this table
customizing concept.




                                                                    2
In order to minimize your upgrading costs, the standard programs and tables should not
be changed as far as possible. The main purpose of using standard business application
software like SAP is to reduce the amount of time and money spends on developing and
testing all the programs. Therefore, most companies will try to utilize the available tools
provided by SAP.

What is SAP R3?

We know that SAP R/3 is software, it particular it is client-server software. This means
that the groups/layers that make up a R/3 System are designed to run simultaneously
across several separate computer systems. When you install Microsoft Excel on your PC,
each component of Excel (printing components, graphing components, word processing
components, and etc.) is stored, managed, and processed via the hardware of your PC.
When a company installs SAP’s software each component (or "layer” in R/3’s case) is
stored, managed, and processed via the hardware of separate and specialized computer
systems. Each of the various layers is capable of calling upon the specialty of any of the
other installed layers in order to complete a given task.

Successfully Implementing SAP

Implementing a package can be a traumatic affair for both the customer and the vendor.
Get it wrong and the vendor may get paid late or have to resort to lawyers to get paid and
tarnish their reputation. For the company the new package may not work the way they
expected, be late or cost a more than budgeted for and take management will take their
eye off running their business.

Recently a client asked me what I would consider to be the five most important things
one should consider before embarking on an implementation. This isn't a simple
question, although there are many factors to think about after some consideration for me
the top five are way ahead of the others.

My top five factors to consider would be:

      Set up a Project Board
      Secure the resources
      Complete the GAP Analysis
      Have detailed Cut Over Plans
      Train the users.




                                                                   3
What Is The Purpose Of R/3?

       The sole purpose of an R/3 system is to provide a suite of tightly integrated, large-
scale business applications.

The standard set of applications delivered with each R/3 system is the following:

   •   PP (Production Planning)
   •   MM (Materials Management)
   •   SD (Sales and Distribution)
   •   FI (Financial Accounting)
   •   CO (Controlling)
   •   AM (Fixed Assets Management)
   •   PS (Project System)
   •   WF (Workflow)
   •   IS (Industry Solutions)
   •   HR (Human Resources)
   •   PM (Plant Maintenance)
   •   QM (Quality Management)
   •   CRM (Customer Relationship Management)


These applications are called the functional areas, or application areas, or at times the
functional modules of R/3. All of these terms are synonymous with each other.

Traditionally, businesses assemble a suite of data processing applications by evaluating
individual products and buying these separate products from multiple software vendors.
Interfaces are then needed between them. For example, the materials management system
will need links to the sales and distribution and to the financial systems, and the
workflow system will need a feed from the HR system. A significant amount of IS time
and money is spent in the implementation and maintenance of these interfaces.

R/3 comes prepackaged with the core business applications needed by most large
corporations. These applications coexist in one homogenous environment. They are
designed from the ground up to run using a single database and one (very large) set of
tables. Current production database sizes range from 12 gigabytes to near 3 terabytes
Around 8,000 database tables are shipped with the standard delivery R/3 product.




                                                                    4
1.2 SCOPE OF THE STUDY



The study focuses on the perception and level of satisfaction of employees in SAP in
finance department of SIC. It also helps the company to evaluate their operating
efficiency relating to various queries or employees requirements and to evaluate the
employee’s awareness level about the sap knowledge available to them.

The study enables the SIC to understand the service that are unsatisfactory to the
employees and that requires improvement and also helps them in identifying the critical
success factors.




                                                                 5
1.3 IMPORTANCE OF THE STUDY



The main importance of the study goes to understand the employee’s satisfaction

level towards SAP.


SAP strives to define and establish undisputed leadership in the emerging market for

business process platform offerings and accelerate business innovation powered by IT

for companies and industries worldwide. As part of its commitment to corporate

citizenship, SAP also contributes to economic development on a grand scale.


"SAP is recognized as a leader in demonstrating the highest level of integrity in its

corporate governance and practices. These efforts are informed and driven by the core

values of SAP – customer focus, integrity, quality, commitment, product excellence,

and passion."




                                                                   6
1.4 OBJECTIVE OF THE RESEARCH



 Primary Objectives:

 To identify the employees interest in implementation of SAP in finance
  department.

 To identify the difference between SAP and other software using in finance
  department.

 To identify employees satisfactory level by implementing SAP in SIC.

 To identify the understanding level of employees towards SAP.


 Secondary Objectives:

 To identify additional areas of expertise that is contained within the organization.

 To identify areas in which the staff would like to develop further.

 To analyze the importance of SAP in finance department of an organization.

 To identify the expectations of employees towards SAP.




                                                               7
RESEARCH METHODOLOGY


        Research methodology is a way to systematically solve the research problem.


1.5 RESEARCH DESIGN
        “A research design is the arrangement of the conditions for the collection and
analysis of data in a manner that aims to combine relevance to the research purpose with
economy in procedure”. The study is based on both ‘descriptive research’ and
‘Hypothesis testing research’.


Descriptive research:
        The study is based on descriptive research descriptive research includes surveys
and fact-finding enquiries of different kinds. The major purpose of descriptive research is
description of state of affairs, as it exists as present. The main characteristics of this
method are that the researcher has no control over the variables; he can only report what
has happened or what is happening. The methods of research utilized in descriptive
research are survey methods of all kinds, including comparative and correlation methods.



Methods of data collection:
        The study is carried out with the help of the following methods of collection.
                1. Primary data
                2. Secondary data.


Primary data:
        I have collected the primary data through the structured questionnaire from the
employees of SIC




                                                                       8
Secondary data:


The secondary data are gathered from various sources such as website SIC of
newspapers, journals, magazines etc.


Nature of data:


In the survey the nature of data collected was primary, through the help of questionnaires.


Questionnaire design:

The questionnaire framed for the research study is a structured questionnaire in which all
the questions are predetermined before conducting the survey. The form of questionnaire
is of both closed and open type.

Close-ended questions:


The closed Type of questions is of


       1. Dichotomous scale                   (Yes/No)


       2. Likert 5-point scale                (S.A,A,NA.ND,D.A,S.D.A)


       3. Category scale                      (multiple items)




Multiple-choice questions:


In this case, the respondents are offered two or more choices. The respondent has to
indicate which is applicable in this study.




                                                                   9
1.6 SAMPLING DESIGN

This survey will be carried out through stratified random sampling.

Stratified Random sampling

Under stratified random sampling the population is divided into several sub – populations
that are individually more homogeneous than the total population ( the different sub –
populations are called ‘ strata’ ) and then we select items from each stratum to constitute
a sample.

Since each stratum is homogeneous than the total population, we are able to get more
precise estimates for each stratum and by estimating more accurately each of the
component parts, we get a better estimates of the whole. In brief stratified sampling
results in more reliable and detailed information.

Sampling method

The sample method used for the research is “stratified random sampling”, where the
customers visiting the bank for transacting are administered with the questionnaire and
were asked to answer the questions that help in determining their satisfaction level,
awareness level and the perceived bank’s operating efficiency.

Sampling size:


A sample size of 250 has been taken for the purpose of the project.


Data analysis and interpretation:


Data collection:


With the prepared questionnaire, where the respondents were approached in the
appropriate time and at the appropriate places.


                                                                   10
Data analysis:


Considering the manner of data collection adopted, the study analyzed the data on
qualitative basis. Various options collected from respective respondents are analyzed
separately.


The statistical bank is a collection of statistical procedures for extracting managed
information from data, it consists of usual statistical routines for calculating averages
measures of dispersion and cross tabulation of data, percentages and ratios, which are
highly useful when comparing two or more of data.


Data analysis has been done for 250 samples. The graphical tools used are Bar Diagram,
Pie Diagram, the statistical tools are percentage analysis, chi-square and ratio analysis,
cash flow analysis and fund flow analysis.


Data interpretation:


The data from each and every user was analyzed and interpreted individually and then
complied together and presented in the form of tables and charts.


In each table, the total respondents answering for a particular question is noted. Among
them the alternate answers were given and traced, finally, the percentage of each answer
for particular option is traced.




                                                                    11
STATISTICAL TOOLS USED FOR ANALYSIS


Chi-square test


Chi-square test is a non parametric test used most frequently by marketing researchers to
test the hypothesis. This test is employed for testing hypothesis when distribution of
population is not known and when nominal data is to be analyzed.


Chi-square test aims at determining whether a significant difference exists among the
graphs or whether the differences are due to sampling. Chi-square test is similar to T test
in which the degrees of freedom increase, where the distribution becomes more
symmetrical and resembles the normal curve. The following is the formula for calculating
chi-square test.


               X= (Oij-Eij) ^2
                       Eij
Where Oij Observed Frequency
       Eij  Expected Frequency



Analysis of Variance (ANOVA)

Analysis of Variance is an extremely useful technique concerning researches in the
economics, education, business/industry and researches of several other disciplines. This
technique is used when multiple sample cases are involved. The ANOVA technique
enables us to perform this simultaneous test and as such is considered to be an important
tool of analysis in the hands of a researcher. Using this technique, one can draw
inferences about whether the samples have been drawn from the populations having the
same mean.




                                                                   12
Percentage analysis


Percentage refers to a special kind of ratio. Percentages are used in making comparison
between two or more series of data. Percentages are used to describe relationships.
Percentages can also be used to compare the relative terms, the distribution of to be more
series of data with a given table, it was difficult to interpret the table with absolute figures
but when percentages are used, it is very easy to find the relative differences in
distributions.


Ratio analysis
An analysis of financial statements based on ratios is known as ratio analysis. A ratio is a
mathematical relationship between two or more items taken from the financial
statements. It helps in measuring the profitability, solvency, and activity of a firm.


Cash flow analysis
It depicts the inflows and outflows of cash. Cash flow statement is the device for such
analysis. It highlights causes which bring changes in cash position between two balance
sheet dates.


Fund flow analysis
Fund flow analysis clearly shows internal and external sources of working capital and the
way funds have been used. It is derived from the analysis of changes which have taken
place in assets and equities between two balance sheet dates. It is helpful in judging the
credit worthiness, financial planning and budget preparation.




                                                                      13
1.7 HYPOTHESIS

Hypothesis may be defined as a proposition or a set of proposition set forth as an
explanation for the occurrence of some specified group of phenomena either asserted
merely as a provisional conjecture to guide some investigation or accepted as highly
probable in the light of established facts.

HYPOTHESIS I

There is no significant difference between the occupation and deposits.

Null Hypothesis:

There is no significant difference between the occupation and deposits.

Alternative Hypothesis:

There is a significant difference between the occupation and deposits.

HYPOTHESIS II

There is no significant difference between the perception and age.

Null Hypothesis:

There is no significant difference between the perception and age.

Alternative Hypothesis:

There is a significant difference between the perception and age.




                                                                    14
1.8 EXPECTED CONRIBUTION OF THE RESEARCH


       This research work is will create the interest of the employees on SAP and this
study is recommended to the employees about the company act ivies for understanding to
the all the employees and also given some suggestion and technical view about the SAP
and there performance in company.




                                                                 15
1.9 LIMITATION OF THE STUDY


   The study was undertaken only in the Chennai branch. Hence the conclusion
      drawn from thus study can’t be generalized.


   The data has been collected with the help of structured schedule and the validity
      of the study depends, on the accuracy of the response given by the respondents.


   Due to non availability of the all employees because of the tight schedule most of
      the respondents are reducing to give response.


   Due to various factors associated the information provided by employees has its
      own bias


   For collecting relevant information from employees prior appointment had to be
      fixed.


   The method of survey was very expensive.


   Major part of the work is concern with financial data, adequate was not able to
      pool because of secrecy maintain by the company.


      The study revels the finding for the present and it will not reflect the future


      The total cost factor involved in the entire training process




                                                                  16
CHAPTER II

THEORETICAL ANALYSIS




                   17
2.1 COMPANY PROFILE:

                      Souh Indian Corporation (SIC) situated at Sipcot Industrial Park
Irungattukottai, Sriperumpudur Taluk , Kanchipuram District is a wholly owned
subsidiary M/s SIC project Indian Gmbh and belongs to the SIG group of Companies
who at the market leaders in manufacturing equipments relating to construction industry
more specifically for preparation transportation and placement of Ready Mix Concrete
(RMC).

                      SIC was incorporated as a private limited company on 18th June
1998 and the necessary permission was obtained from the Secretariat for industrial
assistance. Ministry of industries Government of India for a 100% foreign holding. The
Total market share in India for various types of construction equipments ranges between
40-65% respectively. The group is known for its quality products and has been
recognized one of the best manufacturers of these equipments


                    Looking at the design and software potential in India the group
management decided to off load the group’s design and development work and software
development works to the Indian company and accordingly SIC has set up a Software
Technology park. The company has its good won at Pondicherry and branch offices at
Mumbai, New Delhi, Kolkatta, Hyderabad, Behror (Rajasthan) and Bangalore. The
Company has its Resident engineers stationed at Ahmadabad, Bangalore, Vizag,
Belgaum, Kundankulam Camper, and Gaya & Chitogarh.


                       The company completed construction of the new factory at
Irungattukottai and commenced production in November 2001. The investment in the
project was appox Rs14 Crores. The market appears very good for the infrastructure
industry and considering the thrust on infrastructure development in India, SIC is
confident of achieving better in the years to come with substantial growth and demand
for quality equipment.




                                                               18
Associated Enterprises:

SIC Gmbh, Germany


Herne:
                   Founded in the year of 1934, The headquarters of the SIC Gmbh is
the administrative and technical center of the whole SIC Group, as well as being the
main production base for concrete pumps and placing booms, slurry pumps and fire
fighting equipment in Herne alone the SIC Gmbh employs more than 900 persons.


Memmingen:
                    The headquarters of the SIC Gmbh, with a workforce of over 300,
is located in Memmingen, Bavaria. This facility is the development and production
centre for batching plants, truck mixers and concrete recycling plants. SIC Gmbh and
SIC Gmbh have been team now for almost 20 years.

SIC Gmbh, Austria:

St. Stefam:
                  This plant was founded as a subsidiary 30 years ago and employs
more than 300 persons. St. Stefan Plant produces structural components for concrete
pumps and placing booms.

Vienna:
                 After founding a production plant in Carinthia in 1971, SIC Opened
a branch in Vienna in 1982 employing 8 persons.

SIC America Inc:

White Bear Lake:

                   SIC America Inc., White Bear, Minnesota, has been serving the
North American Market since 1974. White Bear is responsible for sales and service,
as well as local production and truck mounting of the SIC and SIC products.




                                                            19
2.2 PRODUCT PROFILE OF THE COMPANY

SIC – Group

                      On March 17th 1934 Friedrich Wilhelm SIC established a
company in Germany’s most important industrial area, the Ruhr Valley. SIC products
major customers were in the mining industry, in road construction, in civil
engineering and construction. When post-war reconstruction began in1945 the company
Developed several types of machinery, some of which are still today of the art. Among
Them were hoists an inevitable concrete and mortar mixing machines. The SIC
company was founded in Memmingen, Bavaria and is in manufacturing concrete
mixing machines SIC made the first oil-hydraulic double-cylinder pump.
This construction principle has been taken over by almost all of today’s manufactures.

            In 1958 SIC started ready-mixed concrete with its first truck mixer
two years later with the development of filling stations for truck mixers and in
1964, concrete batching plants with considerable capcities.In1965, SIC put the first
truck mounted concrete pump on the market and upgraded it three years later by
adding a placing boom. SIC also started activities in the field of
environmental protection, building the first concrete recycling plant in 1976.

                   In addition to the 900 employees in the headquarters in Herne
(Including 77 trainees) the SIC group employs a further 1500 persons worldwide in
production plants in Germany. Austria the USA, Brazil, Russia, China and India.
They sales and service centre in France, the Nether land, Austria, the Czech Republic
and Swden as well as representations in more than100 countries worldwide. The SIC
group is the world’s No.1 System house in all matters concerning concrete from batching
and mixing to transport.

                        SIC’s concrete mixing plants represents the first link of a chain.
SIC truck mixers take the concrete to the site. SIC concrete pumps make concrete
alive, creating residential properties, tunnels, football stadiums or skyscrapers. The
recycling of residual concreter guarantees a perfect use of concrete and environmental
protection.

Brief description of SIC’s Main Product Line:

                       SIC’s product range as already indicated else where, caters to the
equipment requirement mixing transporting and applying ready mix concrete at the
project sites. The equipment manufactured by SIC with brief description are described
below in the same order of the process.




                                                                    20
Batching Plants- Mixing Of Ready Mix Concrete (RMC)

                      These plants in variant capacities are usually located within 100 km
distance of the application sites, for mixing the RMC. The plant is manually controlled
by a control panel, which software oriented, where the specification of the mixer can be
fed and the plant will draw the raw materials in appropriate quantities for delivering the
specified mixer specification. The micro control apparatus is entirely software driven.

Functions Performed by SIC:

                           The whole process of manufacture is carried out by SIC at its
facility using the technology provided by the AE. Important functions that need to be
mentioned in this context are:

Raw Material Sourcing:

      This consists of identification of sources of raw materials that are required for the
       purpose of manufacturing of concrete mixers pumps evaluating the competence
       and ability to deliver, placing through a process of venture evaluation placing of
       orders, quality inspection on receipt and organsing for contingency plans given
       the market environment in India.

      The manufacturing process demand engineering skills and SIC carry out the
       function of recruiting, training, rewarding and retaining the relevant technical
       skills required for the manufacturing of the products.

      Needless to say all support functions like accounting, human resources
       management are also within the province of SIC.

      Functions relating to protection of assets through insurance are also carried out by
       SIC.

      Market development assessment of market requirements ascertainment of
       demands and sales as per requirements of the Indian market and assumption of
       credit risks associated with the sales.

      The function of operation to ensure availability of funds for procurement, process,
       cost, and personnel cost and sales and delivery cost is also carried out by the AE.

      Warranty servicing of sales is also within the domain of SIC.

      Taking care of all functions relating to managing and complying with the Indian
       laws and regulation connected with pollution control, labor and industrial
       legislations in carrying out its functions.

                                                                  21
2.3 REVIEW OF LITERATURE:


                         In 1972, five systems analysts began working nights and weekends
to create standard software with real-time data processing. Twenty-five years later their
vision is a reality: SAP is the world’s market and technology leader in business
application software.

                            On April 1, 1972 five former IBM employees founded SAP as
System analyzes und Programment wicklung (“Systems Analysis and Program
Development”) in Mannheim, Germany. Their vision was to develop and market standard
enterprise software which would integrate all business processes. The idea came to them
through their work as systems consultants for IBM when they noticed that client after
client was developing the same, or very similar, computer programs. The second part of
their vision was that data should be processed interactively in real-time, and the computer
screen should become the focal point of data processing.

                                 From a start-up software vendor to global market leader
over the course of twenty-five years, their vision has transformed SAP from a small
regional enterprise into a world-class international company. Today, the SAP Group is
the global market leader in enterprise resource planning software, and has subsidiaries,
affiliates and branch offices in nearly every industrial nation in the world. Important
milestones in the company's corporate history include its conversion to a GmbH (a
closely-held corporation) in 1977, the opening of the company's headquarters in
Walldorf, and its conversion into a publicly-held corporation whose shares are listed on
several stock markets.

                             By changing its structure to a publicly-held corporation, SAP
significantly strengthened its capital base and laid the foundations for its employees to
enjoy more of a share in the company's success. In the end, it is SAP’s employees –
currently more than 9,000 of them - whose know-how, motivation and performance have



                                                                  22
nurtured the company’s progress. And it is their commitment and innovative drive which
will pace the company’s future success and keep it ahead of the competition.

                        Over one million R/3 users .Products have played the central role
in SAP’s success story. In this area, two milestones stand out: first, the development and
1979 market release of the R/2 software system for mainframes, and, second, the R/3
client/server software system introduced in 1992. Since its debut, the R/3 System use has
grown explosively and now accounts for the lion's share of SAP product sales. At
present, more than one million end users around the world work with the R/3 System.

                        The development of SAP products has continually benefited from
major advances in the hardware sector. Back in 1972, the limited storage capacity of
computers posed one of the biggest challenges. In those days, mainframes only had 500
kilobytes of storage capacity. Slow data input and output meant that only partial
applications with a limited data volume were feasible. It was against this technological
background that SAP signed its first customer, the German ICI subsidiary in stringer.

                        With the successful implementation of its initial project, SAP had
nine employees and, at the end of its first fiscal year, posted a profit on revenues of DM
620,000. In the second year of operation, two local businesses – the tobacco and cigarette
manufacturer Roth-Handle and the pharmaceutical company Knoll - selected the newly
developed SAP Financial Accounting (RF) System. This system quickly earned a
reputation as an excellent standard package and installations expanded to 40 customers.
But product development did not slow on this success, and a second standard product, the
Materials Management (RM) System, with modules for purchasing, inventory
management and invoice verification, soon followed. The benefits of SAP's integration
philosophy showed through, with data from Materials Management flowing straight into
Financial Accounting.

                     SAP moves to Walldorf. In its fifth year of operations, SAP became
a GmbH (a closely-held corporation) and took on a new name: System, Anwendungen,
Product in deer Datenverarbeitung ("Systems, Applications, Products in Data


                                                                  23
Processing"). Revenues were now close to DM 4 million, and the number of employees
had grown to 25. In 1977, SAP moved its offices and headquarters to Walldorf.

           In the same year, it signed its first two foreign customers, two companies from
Austria. Just one year later, the customer base had grown to 100 and the number of
employees stood at 50. SAP had also introduced another central module of the SAP
System – Asset Accounting (RA). At the same time, through the development of a French
version of the accounting module, SAP made additional steps toward the international
markets.

                         By the end of the 1970s, new generations of powerful computers
provided the framework for a comprehensive software system, and a major step in the
development of SAP software - the R/2 System – was taken in 1978. In the same year, as
sales headed toward the DM 10 million milestones, SAP began operation of its own
computer center in Walldorf which, when completed in 1980, united development teams
under one roof. That year SAP’s software became even more attractive with the addition
of order history to the product range. At the end of 1980, 50 of the 100 largest industrial
companies in Germany were SAP customers.

                            R/2 System goes international SAP’s close relationships with
customers led to continuous enhancements in the existing program modules, while
important new additions were made, such as the Cost Accounting (RK) System. The R/2
System was now ready for the international market. New computers with drastically
improved price/performance ratios helped expand the customer base, and SAP raised its
profile still further by appearing at the Systems trade fair in Munich - the company's first-
ever presence at an industry trade show.

                         In 1982, SAP celebrated its tenth anniversary, with sales soaring
48% to over DM 24 million. By the end of the year, 236 companies in Germany, Austria
and Switzerland were working with the SAP standard programs. Sales continued to climb
in the following year, increasing by 45%.




                                                                   24
In 1984 SAP took additional steps into the international arena with
the founding of SAP (International) AG in Switzerland, whose focus was to increase
sales of the R/2 System in international markets.

                                Development teams began work on two new applications,
Personnel Management and Plant Maintenance, while the Production Planning and
Control System was installed at its first pilot customers. 1985 was characterized by
further expansion. The Walldorf headquarters had grown to 10,000 square meters of
space, while at the Swiss subsidiary a new headquarters was occupied. SAP systems were
now in use in most European countries, and SAP began to penetrate markets outside
Europe - with customers in South Africa, Kuwait, Trinidad, Canada and the US.

                              The DM 100 million sales mark exceeded SAP continued to
pursue international growth with the founding in 1986 of SAP’s Austrian subsidiary SAP
Österreich Ges.m.b.H. in Vienna. At the parent company, SAP GmbH, the capital stock
was increased from DM 500,000 to DM 5 million. The largest single hardware
investment to date was made in Walldorf with the installation of an IBM mainframe
costing DM 7 million. The year's sales topped DM 100 million, and SAP exhibited at
CeBIT, the world's largest IT trade fair, for the first time.

                        The 15th year of the company's history was again characterized by
powerful growth. Branch offices were opened in Munich and Hamburg, and subsidiaries
established in four European countries - the Netherlands, France, Spain and the UK. Staff
grew to 750, and sales more than doubled to DM 245 million, with 850 companies now
using SAP's software systems. In 1987, SAP announced its strategy for a new generation
of software, and the R/3 System was born.

                               SAP goes public SAP continued to grow in 1988 with the
international sales network strengthened by the establishment of subsidiaries in Denmark,
Sweden, Italy and the US. Other events included: the founding of SAP Consulting GmbH
as a joint project between SAP and the consulting firm Arthur Andersen; the opening of
an International Training Center in Walldorf; and the welcoming of Dow Chemical as


                                                                  25
SAP’s 1,000th customer. However, the most significant events of the year were the
increase of SAP’s capital stock from DM 5 million to DM 60 million, the subsequent
conversion    of    SAP        GmbH      into   a    stock    corporation,   SAP     AG
During the next year, 1989, SAP shares began trading on the Zurich stock exchange.

                     SAP expanded its alliance and strategic cooperation approaches by
taking a majority investment in TOS GmbH in Freiberg. Through the "International User
Conference" in Lausanne, Switzerland, and the first "SAPPHIRE" user conference in
North America, SAP demonstrated its solid commitment to direct international customer
contact. This crucial commitment was to become more and more important to SAP’s
success in the coming years.

                          Over 1,000 employees SAP (International) soon grew to twelve
subsidiaries, including Canada, Singapore and Australia. SAP's growing profile in 1989
was evidenced by a number of events: the large number of participants attending the first
Annual Stockholders' Meeting, the strong employee growth to more than 1,000, and the
expansion of the customer base. Recognizing this success manager magazin named SAP
"Company of the Year" – a distinction SAP would receive twice more in the next few
years.

                      In 1990, SAP's capital stock was expanded to DM 85 million with
the issue of preference shares. SAP strengthened its commitment to small- and medium-
sized businesses by an investment in the software company Steeb and the acquisition of
software vendor CAS. In the same year, SAP and Siemens Nixdorf founded SRS GmbH
in Dresden, gaining a firm foothold in the East German market. Sales grew strongly to
over DM 500 million, and the number of staff grew to 1,700.

                               SAP develops Russian R/2 version Strong growth continued
unabated in 1991. The acquisition of Steeb GmbH was completed and its activities were
merged with CAS to form STEEB-CAS GmbH, creating a high-caliber software
company with an attractive product offering for the small- and medium-sized company
market. With SAP’s Eastern European business developing quickly, SAP collaborated


                                                                 26
with a local Russian software company to develop an R/2 version in Russian. The first
Japanese installation of SAP software was successfully completed. At the end of the
fiscal year, the SAP Group boasted 2,225 customers in 31 countries and
sales of more than DM 700 million – an increase of over 40 percent. The company had
more than 2,500 employees.

                          In its twentieth year, SAP opened a new Development and Sales
Center in Walldorf. The two-year project cost roughly DM 140 million and represented
the company's largest single investment to date. In preparation for additional
development, SAP’s share capital was expanded by DM 15 million to DM 100 million
through the issue of 300,000 preference shares. SAP was now firmly established as a
global company, with South Africa, Malaysia and Japan the newest additions to its 15
subsidiary companies. By 1992, almost half of the DM 831 million in product revenues
were being generated outside Germany, and the availability of the software in 14
different languages was adding significantly to its attractiveness.

                            Shipment of the client/server system R/3 With the R/3 System
release in mid-1992, SAP began to penetrate the mid-size market, and into branches and
subsidiaries of large companies. The release of the R/3 client/server system was the most
significant event in SAP’s history and started a record of growth that even SAP’s most
optimistic planners had not predicted.

                          SAP took top position among German software vendors in 1993.
On an international scale, the company moved to 7th place among software companies,
establishing a clear lead in the global business applications software market. Sales
surpassed the important DM 1 billion mark for the first time in 1993, and the global
customer base stood at 3,500 companies. SAP made an investment in iXOS Software
GmbH with the aim of developing and marketing graphical user interfaces and optical
archiving of documents.

    New development center in Foster City, California Releases 2.0 and 2.1 provided R/3
users with even more functionality. With the R/3 System already running on six hardware


                                                                      27
platforms, SAP and Microsoft signed an agreement to port R/3 to Windows NT. Other
events included: the founding of SAP’s 18th subsidiary in the Czech Republic, the
establishment by SAP America of a development center in Foster City in Silicon Valley,
California, and the introduction by SAP Japan of a Kanji version of R/3.

                  1994 was yet another record-breaking year with sales jumping 66% to
over DM 1.8 billion. By the end of the year, SAP employed more than 5,000 staff
worldwide, and 200 of the more than 4,000 customers were using the R/3 System in
production operation. A Swiss customer was the first customer to go live with R/3 on
Microsoft’s Windows NT – a mere four months after the platform became available.
Since its rollout in 1992, R/3 had now been installed more than 1,000 times. SAP
development received ISO 9000 certification, and R/3 Release 2.2 was completed on
schedule and included a wide range of enhancements in Logistics. SAP continued to
expand its sales organization and strategic alliances. In Germany, SAP acquired a 52%
stake in DACOS Software GmbH with the aim of developing an integrated software
solution for the retail industry. The 19th subsidiary opened in Mexico City.

                  The Annual Stockholders' Meeting agreed to a DM 400 million capital
increase out of retained earnings, bringing total capital to DM 500 million. The resulting
1:4 stock split was positively received by the market and led to a significant increase in
stock price levels. Microsoft chooses R/3 more than 6,000 companies of all sizes were
among SAP customers in 1995, some two-thirds of which solved their IT tasks using the
R/3 System. During the year Microsoft joined IBM as an R/3 customer from the high-
tech sector.

                  In 1995, R/3 became the largest source of overall revenues, with a DM
1.7 billion share of total sales of DM 2.7 billion. Growth prospects were strengthened still
further with the new R/3 Release 3.0, a functional and technical milestone in R/3
development. With this version the important areas of production planning and control
were now comprehensively covered. Another technical addition was the availability of R/
3 on the widely used IBM AS/400 platform.



                                                                   28
CHAPTER III


   DATA ANALYSIS &
INTERPRETATION




                          29
3.1 DATA ANALYSIS AND INTERPRETATION


Table 1 DISTRIBUTION OF RESPONDENTS BASED ON THE GENDER

  S No           Particulars               Respondents                Percent
    1                Male                       177                      69
    2               Female                       73                      31
    3                Total                      250                     100

Sources: Data collected from respondents


INTERPRETATION:
Table 1 shows the distribution of employees based on the gender. From the above table it
is inferred that 69% belong to the male category, 31% belong to the female category.


Chart 1 DISTRIBUTION OF RESPONDENTS BASED ON THE GENDER


                                         Frequency

           200
           180
           160
           140
           120
           100                                                        Frequency
            80
            60
            40
            20
             0
                             male                 female




                                                                30
Table 2 DISTRIBUTION OF RESPONDENTS BASED ON THEIR AGE

   S No            Particulars              Respondents               Percent
     1              Below 20                       57                    23

     2               21-35                         131                   52

     3               36-45                         47                    19

     4               46-65                         15                     6

     5                Total                        250                  100

Sources: Data collected from respondents

INTERPRETATION:
Table 2 shows that distribution of respondents based on the age wise classification From
the above table 23% belong to the below20years, 52%belong to the21-35 years,19%
belong to the 36-45years, 6% belong to the 46-65years.


Chart 2 DISTRIBUTION OF RESPONDENTS BASED ON THEIR AGE

                                         Frequency

            140

            120

            100

              80
                                                                  Frequency
              60

              40

              20

               0
                    below20      21-35     36-45         46-65




                                                                 31
Table 3 DISTRIBUTION OF RESPONDENTS BASED ON THEIR SOFTWARE USAGE

      S No             Particulars           Respondents          Percent

         1                    SAP                214                85

         2              TALLY                    29                 12
                                                  5
         3               FOXPRO                                      2

         4             MANUALLY                   2                  1

         5                   Total               250                100

  Sources: Data collected from respondents

INTERPRETATION:
Table 3 shows that distribution of respondents based the SOFTWARE USAGE From the
above Table 85% belong to the SAP 12%belong to the tally, 2% belong to the FoxPro,
1% belong to the manually.


Chart 3 DISTRIBUTION OF RESPONDENTS BASED ON THEIR SOFTWARE USAGE

                                 Frequency




   MANUALLY

      FOXPRO
                                                        Frequency
         TALLY

             SAP

                   0         100      200      300




                                                           32
Table 4 DISTRIBUTION OF RESPONDENTS BASED ON THEIR EXPERIENCE


    S No                 Particulars                Respondents            Percent
       1                  Below 1Yr                     94                   38

       2                  1-2 Years                     111                  44

       3                  2-4 Years                     24                   10

       4                  > 4 Years                     21                    8

       5                    Total                       250                  100

Sources: Data collected from respondents

INTERPRETATION:
Table 4 shows that distribution of respondents based on their experience. From the above
table 38% belong to the below one year, 44% belong to the 1-2years, 10% belong to the
2-4 years, 8% belong to the more than 4 years.


Chart 4 DISTRIBUTION OF RESPONDENTS BASED ON THEIR EXPERIENCE

                                        Frequency




                  MORETHAN
                   4 YEARS


                     2-4YEAR
                                                               Frequency

                     1-2YEAR


                      BELOW
                      1YEAR

                               0       50        100    150




                                                                33
Table 5 DISTRIBUTION OF RESPONDENTS BASED ON THEIR REQURIMENTS FULLFILLD

  S.No            Particulars              Respondents                  Percent

     1           EXCELLENT                       44                        17

     2              GOOD                        139                        55

     3                O.K                        64                        26

     4            NOT GOOD                       3                          2

     5              TOTAL                       250                        100

Sources: Data collected from respondents

INTERPRETATION:
Table 5 shows that distribution of respondents based the requirement fulfilled. From the
above chart 17% belong to the Excellent, 55% belong to the Good, 26% belong to the
O.K, 2% belong to the Not good.


Chart 5 DISTRIBUTION OF RESPONDENTS BASED ON THEIR REQURIMENTS FULLFILLD



                                     Frequency




                                                                     EXCELLENT
                                                                     GOOD
                                                                     O.K
                                                                     NOT GOOD




                                                                34
Table 6 DISTRIBUTION OF RESPONDENTS BASED ON THE TIME EFFICIENT


    S.No           Particulars             Respondents              Percent
        1            FASTER                      86                    34

        2          MODERATE                      27                    51

        3             SLOW                       37                    15

        4              Total                    250                    100

Sources: Data collected from respondents

INTERPRETATION:
Table 6 shows that distribution of respondents based on the Time efficient. From the
above table 34% belong to the Faster, 51% belong to the Moderate, 15% belong to the
Slow.


Chart 6 DISTRIBUTION OF RESPONDENTS BASED ON THE TIME EFFICIENT


                                  EFFICIENT


                                              Frequency

                    140
                    120
                    100
                      80
                      60
                      40
                      20
                       0
                               FASTER      MODERATE         SLOW
              Frequency          86            127            37


                                                             35
Table 7 DISTRIBUTION OF RESPONDENTS BASED ON THE COST OF SAP

   S.No            Particulars             Respondents                Percent
     1           HIGH COSTLY                     120                     48

     2           AFFORDABLE                      78                      31

     3           ECONOMICAL                      52                      21

     4                 Total                     250                    100




Sources: Data collected from respondents


INTERPRETATION:
Table 7 shows that distribution of respondents based on the Cost factor. From the above
table 48% belong to the High costly,31% belong to the Affordable, 21% belong to the
Economical,


Chart 7 DISTRIBUTION OF RESPONDENTS BASED ON THE COST OF SAP




                                                               36
Frequency


           AL
         IC
        M
      O
     N
   O




                                                     Frequency
 EC


           LE
        AB
      D
     R
   FO
 AF



           LY
         ST
        O
      C




                    0%      50%            100%
    H
  IG
 H




Table 8 DISTRIBUTION OF RESPONDENTS BASED ON THE CONFIDENTIALITY

           S.No              Particulars          Respondents              Percent

                1           EXCELLENT                   53                    21

                2              GOOD                    153                    61

                3                 O.K                   40                    16

                4           NOT FAVOUR                   4                     2

                5               Total                  250                    100


Sources: Data collected from respondents

INTERPRETATION:
Table 8 shows that distribution of respondents based on confidentiality. From the above
chart 21% belong to the Excellent, 61% belong to Good, 16% belong to the ok, 2%
belong to the Not favour.
Chart 8 DISTRIBUTION OF RESPONDENTS BASED ON THE CONFIDENTIALITY


                                                               37
Frequency




                                                            EXCELLENT
                                                            GOOD
                                                            O.K
                                                            NOT FAVOUR




Table 9 DISTRIBUTION OF RESPONDENTS BASED ON THE QUALITY OF SERVICE


            S.No           Particulars         Respondents            Percent
               1          EXCELLENT                   54                 22
               2            GOOD                     148                 59
               3             O.K                      48                 19
               4             Total                   250                100




Sources: Data collected from respondents

INTERPRETATION:
Table 9 shows that distribution of respondents based on the Quality service. From the
above table 22% belong to the Excellent, 59%belong to the Good, 19% belong to the OK.


Chart 9 DISTRIBUTION OF RESPONDENTS BASED ON THE QUALITY OF SERVICE

                                                              38
Frequency



 150

 100

   50
                                                                   Frequency
     0
                                             Frequency
           EXCELLENT


                         GOOD


                                     O.K




Table 10 DISTRIBUTION OF RESPONDENTS BASED ON THE DATA LOSSAGE

   S.No                Particulars          Respondents            Percent
     1                    YES                     67                  27
     2                    NO                      128                 51
                   IN SOME OCCASION
     3                                            55                  22
                         ONLY
                         Total                    250                100

Sources: Data collected from respondents

INTERPRETATION:
Table 10 shows that distribution of respondents based on the Data lossage. From the

above table 27% belong to the Yes, 51% belong to the No, 22% belong to
the some occasion only.

                                                            39
Chart 10 DISTRIBUTION OF RESPONDENTS BASED ON THE DATA LOSSAGE


                                       Frequency


             140
             120
             100
              80
              60
              40
               20                                                          Frequency
                0
                                                      Frequency
                      YES


                               NO


                                       OCCASION
                                        IN SOME

                                          ONLY




Table 11 DISTRIBUTION OF RESPONDENTS BASED ON THEIR TRAINING


      S.No          Particulars            Respondents            Percent

        1              YES                      131                  53

        2               NO                      119                  47

        3              Total                    250                  100

Sources: Data collected from respondents

INTERPRETATION:
Table 11 shows that distribution of respondents based on the training from the above
table 53% belong to the Yes, 47% belong to the No.




                                                             40
Chart 11 DISTRIBUTION OF RESPONDENTS BASED ON THEIR TRAINING


                                   Frequency



   132
   130
   128
   126
   124
   122                                                               Frequency
   120
   118
   116
   114
   112
                 YES                       NO


Table 12 DISTRIBUTION OF RESPONDENTS BASED ON THE DURATION OF TRAINING


       S.No       Particulars          Respondents                  Percent

         1            YES                       82                    33
         2             NO                    168                      67
                      Total                  250                      100

Sources: Data collected from respondents

INTERPRETATION:
Table 12 shows that distribution of respondents based on training. From the above table
33% belong to the Yes and 67% belong to the No.


Chart 12 DISTRIBUTION OF RESPONDENTS BASED ON THE DURATION OF TRAINING

                                                               41
Frequency




         NO


                                                                     Frequency


       YES



               0      50         100        150      200




Table 13 DISTRIBUTION OF RESPONDENTS BASED ON THE TRAINING EXPECTATION


         S.No                              Respondents              Percent
                     Particulars
           1          1MONTH                    67                     27
           2         2-3MONTH                  151                     60
           3         3-4MONTH                   32                     13
                         Total                 250                    100


Sources: Data collected from respondents

INTERPRETATION:
Table 13 shows that distribution of respondents based on the training expectation. From
the above table 27% belong to the one month, 60% belong to the 2-3 month, 13% belong
to the 3-4 month.


                                                               42
Chart 13 DISTRIBUTION OF RESPONDENTS BASED ON THE TRAINING EXPECTATION


                                        Frequency


        160

        140

        120

        100

         80                                                              Frequency

         60

         40

         20

            0
                1MONTH          2-3MONTH        3-4MONTH




Table 14 DISTRIBUTION OF RESPONDENTS BASED ON THE ADDITIONAL TRAINING


      S.No          Particulars            Respondents               Percent

        1              YES                      150                     60
        2               NO                      100                     40
                       Total                    250                    100

Sources: Data collected from respondents

INTERPRETATION:
 Table 14 shows that distribution of respondents based on additional training. From the
above table 60% belong to the Yes and 40% belong to the No.

                                                               43
Chart 14 DISTRIBUTION OF RESPONDENTS BASED ON THE ADDITIONAL TRAINING



                                      Frequency




                 NO



                                                              YES




Table 15 DISTRIBUTION OF RESPONDENTS BASED ON THE EMERGING TECHNOLOGY



  S.No           Particulars               Respondents         Percent

    1                 YES                      163                  65

    2                 NO                       87                   35

    3                 Total                    250               100



Sources: Data collected from respondents

INTERPRETATION:

                                                         44
Table 15 shows that distribution of respondents based on emerging technology. From
the above table 65% belong to the Yes and 35% belong to the No.


Chart 15 DISTRIBUTION OF RESPONDENTS BASED ON THE EMERGING TECHNOLOGY


                                       Frequency




       NO
                            87




                                        163



      YES




            0                 50                100               150             200

                                           Frequency


Table 16 DISTRIBUTION OF RESPONDENTS BASED ON THE CO-ORDINATION


    S.No           Particulars                Respondents               Percent
      1               YES                         177                     70
      2                NO                         73                      30
      3               Total                       250                     100

Sources: Data collected from respondents

INTERPRETATION:
Table 16 shows that distribution of respondents based on the co-ordination. From the
above table 70% belong to the Yes and 30% belong to the No.


                                                              45
Chart 16 DISTRIBUTION OF RESPONDENTS BASED ON THE CO-ORDINATION

       S.No         Particulars            Respondents              Percent

         1              YES                    177                    60

         2              NO                      73                    40

         3             Total                   250                    100



                                        Frequency



          180
          160
          140
          120
          100
                                                                       Frequency
           80
             60
             40
             20
              0
                       YES                    NO




Table 17 DISTRIBUTION OF RESPONDENTS BASED ON THE TECHNOLOGY DRIVEN

Sources: Data collected from respondents

INTERPRETATION:
Table 17 shows that distribution of respondents based on technology driven. From the
above chart 60% belong to the Yes, and 40% belong to the No.


                                                               46
Chart 17 DISTRIBUTION OF RESPONDENTS BASED ON THE TECHNOLOGY DRIVEN

                                            Frequency


             200

             180

             160

             140

             120

             100                                                              Frequency

              80

              60

              40

              20

              0
                              YES                         NO




Table 18 DISTRIBUTION OF RESPONDENTS BASED ON THE COMPLETE PACKAGE


     S.No           Particulars            Respondents              Percent

         1              YES                     176                   70

         2              NO                      74                    30

                       Total                    250                   100
         3

Sources: Data collected from respondents

INTERPRETATION:
Table 18 shows that distribution of respondents based on the complete package. From
the above table 70% belong to the Yes, and 30% belong to the No.


                                                               47
Chart 18 DISTRIBUTION OF RESPONDENTS BASED ON THE COMPLETE PACKAGE




          180
          160
          140
          120
          100
                                                                         Frequency
           80
           60
           40
           20
            0
                        YES                     NO




Table 19 DISTRIBUTION OF RESPONDENTS BASED ON THE SATISFICATION LEVEL


   S.No           Particulars              Respondents                Percent

     1               YES                        156                      62

     2                NO                        94                       38

     3               Total                      250                     100

Sources: Data collected from respondents

INTERPRETATION:
Table 19 shows that distribution of respondents based on satisfaction level. From the
above table 62% belong to the Yes and 38% belong to the No.



                                                              48
Chart 19 DISTRIBUTION OF RESPONDENTS BASED ON THE SATISFICATION LEVEL



                                           Frequency




               NO




                                                                          YES




Table 20 DISTRIBUTION OF RESPONDENTS BASED ON THE USAGE OF SAP

   S.No              Particulars               Respondents            Percent
     1           EXHAUSTIVELY                       74                   29
     2              MODERATE                        155                  61

     3               MINIMUM                        19                   10

     4                  Total                       248                  100

Sources: Data collected from respondents

INTERPRETATION:
Table 20 shows that distribution of respondents based on usage of sap. From the above
table 29% belong to the Exhaustively, 61% belong to the Moderate, 10% belong to the
Minimum.

                                                             49
Chart 20 DISTRIBUTION OF RESPONDENTS BASED ON THE USAGE OF SAP


                                        Frequency




                 MINIMUM



             MODERATE                                                   Frequency


          EXHAUSTIVELY


                           0       50      100      150     200




3.2 STATISTICAL TOOLS FOR ANALYSIS


CORRELATIONS

Ho: There is no significant difference between the time efficient and
implementation cost.


H1: There is significant difference between the time efficient and implementation
cost...




                                                            50
Correlations
                                                                       IMPLEMENTATION
                                                 TIME EFFICIENT
                                                                            COST
                                Pearson
                                                        1.000               .384**
                              Correlation
 TIME EFFICIENT
                             Sig. (2-tailed)                                .000
                                    N                  250.000               250
                                Pearson
                                                        .384**              1.000
IMPLEMENTATION                Correlation
     COST                    Sig. (2-tailed)             .000
                                    N                     250              250.000
    *** Correlation is significant at the 0.01 level (2-tailed)




RESULT:


Ho is accepted. Significant level is (.000).




CHI-SQUARE TEST



Ho: There is no significant difference between the confidentiality and quality.


H1: There is significant difference between the time confidentiality and quality.

Frequencies




                                                                  51
Confidentiality
               Observed N               Expected N          Residual
EXCELLENT             53                       62.5           -9.5
  GOOD             153                         62.5           90.5
   O.K                40                       62.5           -22.5
NOT FAVOUR            4                        62.5           -58.5
   Total           250




                              Quality
             Observed N            Expected N              Residual
EXCELLENT        54                     83.3                -29.3
  GOOD          148                     83.3                 64.7
   O.K           48                     83.3                -35.3
   Total        250




                                                      52
Test Statistics
                          Confidentiality              Quality

                              195.344a                    75.488b
   Chi-Square

                                 3                          2
        df

                                .000                       .000
   Asymp. Sig.

   A) 0 cells (.0%) have expected frequencies less than 5. The minimum
                      expected cell frequency is 62.5.

   B). 0 cells (.0%) have expected frequencies less than 5. The minimum
                       expected cell frequency is 83.3.




RESULT:


Ho is accepted. Significant level is (.000).




SAMPLE KOLMOGOROV-SMIRNOV TEST




                                                     53
Ho: There is no significant difference between the sap usage and fulfilled.


 H1: There is significant difference between the sap usage and fulfilled.



                  One-Sample Kolmogorov-Smirnov Test


                                                SAPUSAGE        FULLFILLED
                N                                 250                 250
   Normal Parameters            Mean             1.8880             2.1040
                                Std.
                                                 .89367             .68634
                              Deviation
Most Extreme Differences      Absolute             .270               .292
                              Positive             .270               .292
                             Negative             -.174              -.264
       Kolmogorov-Smirnov Z                       4.271              4.620
        Asymp. Sig. (2-tailed)                     .000               .000
    a. Test distribution is Normal.




 RESULT


 Ho is accepted. Significant level is (.000).




 ONE-WAY


 Ho: There is no significant difference between the sap usage and fulfilled.


                                                              54
H1: There is significant difference between the sap usage and fulfilled.



                                      ANOVA
TECHNOLOGY DRIVEN

                       Sum of Squares          df       Mean Square         F   Sig.
 Between Groups             1.141               3           .380       1.537    .206
  Within Groups             60.895            246           .248
       Total                62.036            249




 RESULT


 Ho is not accepted. Significant level is (.206).




 PAIRED SAMPLES STATISTICS



 Ho: There is no significant difference between the coordination and emerging
 technology.


                                                              55
H1: There is significant difference between the coordination and emerging
   technology.




                           Paired Samples Statistics

                          Mean        N           Std. Deviation       Std. Error Mean
Pair 1 COORDINATION       1.2920     250             .45559                .02881
          EMERGING
                          1.4320     250             1.06297               .06723
         TECHNOLOGY




                          Paired Samples Correlations
                                            N             Correlation          Sig.
         COORDINATION & EMERGING
Pair 1                                      250                -.029           .644
               TECHNOLOGY




                                                              56
Paired Samples Test
                                       Paired Differences
                                            95% Confidence
                         Std.   Std. Error Interval of the                  Sig. (2-
                  Mean                                           t    df
                       Deviation Mean          Difference                   tailed)
                                            Lower     Upper
P
a
  COORDINATIO
i                                                              -1.894
  N - EMERGING -.14000 1.16870     .07392   -.28558   .00558          249    .059
r                                                                E0
  TECHNOLOGY
1




    RESULT:


    95% Confidence interval of the difference (lower -.285) & (upper .005)

    Ho is accepted.




                                                        57
CHAPTER IV


FINDINGS & CONCLUSION




                   58
4.1 FINDINGS


The Findings of the study are

    From the data analysis it is inferred that 70% belong to the male category, 30% of
     the respondents belong to the female category.

    From the data analysis it is inferred that 23% belong to the below 20years
     category, 52% of the respondents belong to the 21-35 category, 19% belong to
     the 36-45 category, 6% belong to the 46-65 category.

    From the data analysis it is inferred that 85% belong to the Sap category, 12% of
     the respondents belong to the tally category and 2% belong to the manually.

    From the data analysis it is inferred that 37% belong to the below one year, 44%
     belong to the 1-2 years, 10% belong to the 2-4 years 9% belong to the more than 4
     years.

    From the data analysis it is inferred that 17% belong to the excellent category,
     55% belong to the good, 26% belong to the o.k., 2% belong to the not good.

    From the data analysis it is inferred that 34% belong to the faster category, 51%
     belong to the moderate, and 15% belong to the slow.

    From the data analysis it is inferred that 48% belong to the high costly category,
     31% belong to the affordable, and 21% belong to the economical.

    From the data analysis it is inferred that 21% belong to the excellent category,
     31% belong to the good, 16% belong to the o.k., 2% belong to the nof favour

    From the data analysis it is inferred that 22% belong to the excellent category,
     59% belong to the good, and 19% belong to the o.k.

    From the data analysis it is inferred that 27% belong to the yes category, 59%
     belong to the no, and 22% belong to the some occasion only.

    From the data analysis it is inferred that 52% belong to the yes category, 48%
     belong to the no.

    From the data analysis it is inferred that 33% belong to the yes category, 67%
     belong to the no, and 22% belong to the some occasion only.




                                                               59
 From the data analysis it is inferred that 27% belong to the one year category,
  60% belong to the 2-3, and 13% belong to the 3-4.

 From the data analysis it is inferred that 60% belong to the yes category, 40%
  belong to the no.

 From the data analysis it is inferred that 65% belong to the yes category, 35%
  belong to the no

 From the data analysis it is inferred that 70% belong to the yes category, 30%
  belong to the no

 From the data analysis it is inferred that 70% belong to the yes category, 30%
  belong to the no

 From the data analysis it is inferred that 70% belong to the yes category, 30%
  belong to the no

 From the data analysis it is inferred that 70% belong to the yes category, 30%
  belong to the no

 From the data analysis it is inferred that 62% belong to the yes category, 38%
  belong to the no

 From the data analysis it is inferred that 29% belong to the exhaustively category,
  29% belong to the moderate category, 8% belong to the minimum category.




                                                             60
4.2 SUGGESTIONS:


Suggestions based on the study are:


    The organization can take some measures to improve the career
       development of the employees in using the SAP applications more
       effectively in the organization.


    Company should provide additional training program in SAP applications
       to improve the organization standards.


    The quality of SAP service provider and day to day operation should
       improve.


    The company must give the additional training on any changes, updation,
       upgradation with regards to SAP


    The company should reduce the cost for implementation of SAP to lower
       level.


    The company should provide awareness of SAP for all employees.


        The company must adopt new technologies to increase the Knowledge
       there by it can increase the effectiveness of the employees.




                                                             61
4.3 CONCLUSION


                In SIC all the departments are using SAP. But implementation and
testing works are made by Germany. By using SAP in SIC all employees are
satisfied .From the study it is known that employees at SIC are happy with
implementation of sap and they are working efficiently and effectively by saving.
Thus implementation of sap has improved the satisfaction level of employees.




                                                           62
BIBLIOGRAPHY


Joghnson CM. Implementation of SAP, 2nd Edn. Oxford University Publication: London,
  pp 45–52.

Singaravelu CVK. Probability and Statistics, 3rd Edn. Amudham Publications: Chennai,
  India, p. 228.

Kothari CR. Research Methodology, 2nd Edn. Newage Publication: New York, pp 128–
  182.

Williams LK. Basic Concepts of SAP, 3rd Edn. Emerald Group Publication Limited:
  Paris, France, p. 248.

Pannierselvam KV. Enterprise Resources Planning, 3rd Edn. Himalaya Publications:
  New Delhi, India, pp 248–250.

Savkin AV, Petersen IR. Management Concepts and Statistical Analysis (USA) 1999; 44:
  1037–1041

Rafaely B. Advanced concepts of Enterprise Resource Planning. PhD thesis, University
  of Southampton, UK, 1997. http://adsabs.harvard.edu/abs/1997PhDT.......115R

Premount A. Vibration Control of Project Report. 2nd edn. Springer Verlag, 2002

Pal B, Chaudhuri B. Robust Systems Application Products in Data Processing. Springer
  Verlag, 2005

Isidori A, Byrnes CI. Global Industrial Database and Control 1990; 25: 131–140

Marconi L, Praly L, Isidori A. Mathematics for Management Studies. SIAM J Control
  Optim (USA) 2007; 45: 2277–2298




                                                               63
Annexure I

THE EFFECTIVENESS OF SAP IMPLEMENTATION IN
  FINANCE DEPARTMENT WITH REFERENCE TO
        SOUTH INDIAN CORPORATION

 1) NAME:           __________________

 2) Designations : __________________

 3) AGE:            ___________________

 4) GENDER:               Male                 Female

 5) Which Software package tool you are using in your finance department?
    a) SAP          b) Tally        c) FoxPro         d) Manually

 6) Since how long you are using SAP?
    a) Below 1year   b) 1-2 years   c) 2-4 years     d) More than 4 years

 7) Has SAP fulfilled your requirements with regard to formats of Accounts
    Receivables, Payables & other General ledgers?
    a) Excellent   b) Good      c) O.K         d) Not good

 8) How Time efficient is SAP?
    a) Faster     b) Moderate c) Slow

 9) Your opinion on implementation cost of SAP?
    a) High costly b) Affordable     c) Economical

 10) SAP contribution in maintain confidentiality in finance department?
     a) Excellent   b) Good        c) Ok        d) Not favour

 11) How do you rate the quality of service by your SAP service provider?
     a) Excellent   b) Good         c) Ok       d) Poor

 12) Have you come across any data loss after the SAP being installed?
     a) Yes       b) No      C) In some Occasions only?

 13) Does Company provide initial training on SAP to employees?
     a) Yes          b) No


                                                              64
14) If yes, is the duration of training is sufficient?
      a) Yes              b) No

 15) If no, how many month do you expecting for such training?
      a) 1 months b) 2-3 month      c) 3-4 month      d) more than4

 16) Does the company is giving additional training on any changes, updation,
     Upgradation with regard to SAP?
     a) Yes                    b) No

 17) Will SAP hold well in the emerging technology?
     a) Yes                    b) No

 18) In your Opinion, Is there proper co-ordination between finance department and
     other departments with regard to data processing?
      a) Yes                     b) No

 19) Is SAP Technology driven?
      a) Yes                 b) No

 20) In your Opinion, Is SAP a Complete Package?
      a) Yes                   b) No

 21) Are you satisfied with SAP in your department?
      a) Yes                  b) No

 22) To what extent you are using SAP?
      a) Exhaustively b) Moderate     c) Minimum




I SINCERELY THANK YOU FOR YOUR CO-OPERATION




                             T. Dinesh Babu, B.E., M.B.A.,


                                                             65

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The Effectiveness of SAP Implementation in the Finance Department

  • 1. THE EFFECTIVENESS OF SAP IMPLEMENTATION IN FINANCE DEPARTMENT WITH REFERENCE TO SOUTH INDIAN CORPORATION (P) LTD By DINESH BABU T 0702MBA2003 68107201009 A PROJECT REPORT Submitted to the FACULTY OF MANAGEMENT SCIENCES in partial fulfillment for the award of the degree of MASTER OF BUSINESS ADMINISTRATION CENTRE FOR DISTANCE EDUCATION ANNA UNIVERSITY CHENNAI CHENNAI 600 025 July, 2009
  • 2. BONAFIDE CERTIFICATE Certified that the Project report titled _________________________________________ _______________________________________________________________________ is the bonafide work of Mr. / Ms. ________________________________who carried out the work under my supervision. Certified further that to the best of my knowledge the work reported herein does not form part of any other project report or dissertation on the basis of which a degree or award was conferred on an earlier occasion on this or any other candidate. Signature of student Signature of Guide Name: T DINESH BABU Name: Mr. D JAYAKUMAR Roll No: 0702MBA2003 Designation: ERP Consultant Reg No: 68107201009 Address: Anna University Signature of Project-in-charge Name: Mrs A THIRUCHELVI Designation: Professor, Anna University ii
  • 3. Certificate of Viva-voce-Examination This is to certify that Thiru/Ms. /Tmt …………………………………............................. (Roll No……………….…….; Register No. …………………….) has been subjected to Viva-voce-Examination on …………………… (Date) at …………….. (Time) at the Study centre ……………………………………………………………..……………...... ……………………………………………………………… …………………………… (Name and Address of the Study centre). Internal Examiner External Examiner Name: Name: Designation: Designation: Address: Address: Coordinator Study centre Name: Designation: Address: Date: iii
  • 4. ACKNOWLEDGEMENT I am thankful to South Indian Corporation India (P) Ltd, which has imparted me sufficient knowledge and confidence to complete the project successfully in the field of corporate training. I express my special thanks to My Parents and Family Members for the constant support and encouragement extended to me in completing this project on time. I would especially like to express my gratitude towards Mr. D. JAYAKUMAR, ERP Consultant, Sun Direct Television P Ltd, who was my project guide and Mrs. A. THIRUCHELVI, Professor, Dept of Management Studies, Anna University, who was my Project-in-charge for all the support and constant feedback on my progress made during the project. I would also like to thank Mr. JASON PEARCE, Operations Head, NewGen and all office staff for their support and encouragement, which helped me to complete this project successfully. I extend my heart felt thanks to Ms. S NIRMALA, H.O.D, Department of Computer Science and Engineering, I.F.ET College of Engg for encouraging me towards the professional degree in Management Studies. My heart felt thanks to all the noble hearts that has helped me to do complete this project successfully. Place: Chennai Date: (DINESH BABU T) iv
  • 5. ABSTRACT The project work has been undertaken at South Indian Corporation (P) Ltd. The project is titled as “THE EFFECTIVENESS OF SAP IMPLEMENTATION IN FINANCE DEPARTMENT” with reference to South Indian Corporation (P) Ltd The objective of this project is the effectiveness of sap implementation measures of employees of in South Indian Corporation (P) Ltd Sampling technique used is Random sampling and the sample size is 250. A statistical tool like t-test, correlation & chi-square test used for analysis and interpretation was carried out by using percentage method, and weighted average method. The collected data are tabulated, analyzed and interpreted. Finally the results are given as findings and recommendations to the company for better prospects. v
  • 6. CHAPTER NO CONTENTS PAGE NO LIST OF TABLES vii LIST OF CHARTS viii I 1.1 INTRODUCTION 2 1.2 SCOPE OF THE STUDY 5 1.3 IMPORTANCE OF THE STUDY 6 1.4 OBJECTIVE OF THE RESEARCH 7 • PRIMARY OBJECTIVE • SECONDARY OBJECTIVE 1.5 RESEARCH DESIGN 8 1.6 SAMPLING DESIGN 10 1.7 HYPOTHESIS 14 1.8 EXPECTED CONTRIBUTION OF THE STUDY 15 1.9 LIMITATIONS OF THE STUDY 16 II THEORETICAL ANALYSIS 2.1 COMPANY PROFILE 18 2.2 PRODUCT PROFILE 20 2.3 REVIEW OF LITERATURE 22 III 3.1 DATA ANALYSIS & INTERPRETATION 30 3.2 STATISTICAL TOOLS FOR ANALYSIS 50 IV 4.1 FINDINGS 58 4.2 SUGGETIONS 60 4.3 CONCLUSION 61 BIBLIOGRAPHY 62 ANNEXTURES 63 vi
  • 7. LIST OF TABLES S No PARTICULARS Page No 1. Distribution of respondents based on Gender 30 2. Distribution of respondents based on Age 31 3. Distribution of respondents based on Software package using 32 4. Distribution of respondents based on Experience held 33 5. Distribution of respondents based on Full filled requirements 34 6. Distribution of respondents based on Time efficient 35 7. Distribution of respondents based on Implementation cost 36 8. Distribution of respondents based on Confidentiality 37 9. Distribution of respondents based on Quality of service 38 10. Distribution of respondents based on Data lossage 39 11. Distribution of respondents based on Initial training of respondents 40 12. Distribution of respondents based on Training duration 41 13. Distribution of respondents based on Expecting training 42 14. Distribution of respondents based on Additional training 43 15. Distribution of respondents based on Emerging technology 44 16. Distribution of respondents based on Co-ordination between dept., 45 17. Distribution of respondents based on Technology driven 46 18. Distribution of respondents based on Complete package of sap 47 19. Distribution of respondents based on Satisfaction level 48 20. Distribution of respondents based on Usage of SAP 49 21. Correlation 50 22. Chi-Square 51 23. Sample Kolmogorov-Smirnov Test 53 24. ANOVA 54 25. Paired Samples Statistics 55 vii
  • 8. LIST OF CHARTS S No PARTICULARS Page No 1. Distribution of respondents based on Gender 30 2. Distribution of respondents based on Age 31 3. Distribution of respondents based on Software package using 32 4. Distribution of respondents based on Experience held 33 5. Distribution of respondents based on Full filled requirements 34 6. Distribution of respondents based on Time efficient 35 7. Distribution of respondents based on Implementation cost 36 8. Distribution of respondents based on Confidentiality 37 9. Distribution of respondents based on Quality of service 38 10. Distribution of respondents based on Data lossage 39 11. Distribution of respondents based on Initial training of respondents 40 12. Distribution of respondents based on Training duration 41 13. Distribution of respondents based on Expecting training 42 14. Distribution of respondents based on Additional training 43 15. Distribution of respondents based on Emerging technology 44 16. Distribution of respondents based on Co-ordination between dept., 45 17. Distribution of respondents based on Technology driven 46 18. Distribution of respondents based on Complete package of sap 47 19. Distribution of respondents based on Satisfaction level 48 20. Distribution of respondents based on Usage of SAP 49 viii
  • 10. 1.1 INTRODUCTION An Introduction to SAP SAP was founded in 1972 in Walldorf, Germany. It stands for Systems, Applications and Products in Data Processing. Over the years, it has grown and devolved to become the world premier provider of client/server business solutions for which it is so well known today. The SAP R/3 enterprise application suite for open client/ server systems has established a new standard for providing business information management solutions. SAP products are considered excellent but not perfect. The main problem with software product is that it can never be perfect. The main advantage of using SAP as your company ERP system is that SAP have a very high level of integration among its individual applications which guarantee consistency of data throughout the system and the company itself. In a standard SAP project system, it is divided into three environments, Development, Quality Assurance and Production. The development system is where most of the implementation work takes place. The quality assurance system is where all the final testing is conducted before moving the transports to the production environment. The production system is where all the daily business activities occur. It is also the client that all the end users use to perform their daily job functions. To all company, the production system should only contain transport that has passed all the tests. SAP is table drive customization software. It allows businesses to make rapid changes in their business requirements with a common set of programs. User-exits are provided for business to add in additional source code. Tools such as screen variants are provided to let you set fields attributes whether to hide, display and make them mandatory fields. This is what makes ERP system and SAP in particular so flexible. The table driven customization are driving the program functionality instead of those old fashioned hard- coded programs. Therefore, new and changed business requirements can be quickly implemented and tested in the system. Many other business application software have seen this table driven customization advantage and are now changing their application software based on this table customizing concept. 2
  • 11. In order to minimize your upgrading costs, the standard programs and tables should not be changed as far as possible. The main purpose of using standard business application software like SAP is to reduce the amount of time and money spends on developing and testing all the programs. Therefore, most companies will try to utilize the available tools provided by SAP. What is SAP R3? We know that SAP R/3 is software, it particular it is client-server software. This means that the groups/layers that make up a R/3 System are designed to run simultaneously across several separate computer systems. When you install Microsoft Excel on your PC, each component of Excel (printing components, graphing components, word processing components, and etc.) is stored, managed, and processed via the hardware of your PC. When a company installs SAP’s software each component (or "layer” in R/3’s case) is stored, managed, and processed via the hardware of separate and specialized computer systems. Each of the various layers is capable of calling upon the specialty of any of the other installed layers in order to complete a given task. Successfully Implementing SAP Implementing a package can be a traumatic affair for both the customer and the vendor. Get it wrong and the vendor may get paid late or have to resort to lawyers to get paid and tarnish their reputation. For the company the new package may not work the way they expected, be late or cost a more than budgeted for and take management will take their eye off running their business. Recently a client asked me what I would consider to be the five most important things one should consider before embarking on an implementation. This isn't a simple question, although there are many factors to think about after some consideration for me the top five are way ahead of the others. My top five factors to consider would be:  Set up a Project Board  Secure the resources  Complete the GAP Analysis  Have detailed Cut Over Plans  Train the users. 3
  • 12. What Is The Purpose Of R/3? The sole purpose of an R/3 system is to provide a suite of tightly integrated, large- scale business applications. The standard set of applications delivered with each R/3 system is the following: • PP (Production Planning) • MM (Materials Management) • SD (Sales and Distribution) • FI (Financial Accounting) • CO (Controlling) • AM (Fixed Assets Management) • PS (Project System) • WF (Workflow) • IS (Industry Solutions) • HR (Human Resources) • PM (Plant Maintenance) • QM (Quality Management) • CRM (Customer Relationship Management) These applications are called the functional areas, or application areas, or at times the functional modules of R/3. All of these terms are synonymous with each other. Traditionally, businesses assemble a suite of data processing applications by evaluating individual products and buying these separate products from multiple software vendors. Interfaces are then needed between them. For example, the materials management system will need links to the sales and distribution and to the financial systems, and the workflow system will need a feed from the HR system. A significant amount of IS time and money is spent in the implementation and maintenance of these interfaces. R/3 comes prepackaged with the core business applications needed by most large corporations. These applications coexist in one homogenous environment. They are designed from the ground up to run using a single database and one (very large) set of tables. Current production database sizes range from 12 gigabytes to near 3 terabytes Around 8,000 database tables are shipped with the standard delivery R/3 product. 4
  • 13. 1.2 SCOPE OF THE STUDY The study focuses on the perception and level of satisfaction of employees in SAP in finance department of SIC. It also helps the company to evaluate their operating efficiency relating to various queries or employees requirements and to evaluate the employee’s awareness level about the sap knowledge available to them. The study enables the SIC to understand the service that are unsatisfactory to the employees and that requires improvement and also helps them in identifying the critical success factors. 5
  • 14. 1.3 IMPORTANCE OF THE STUDY The main importance of the study goes to understand the employee’s satisfaction level towards SAP. SAP strives to define and establish undisputed leadership in the emerging market for business process platform offerings and accelerate business innovation powered by IT for companies and industries worldwide. As part of its commitment to corporate citizenship, SAP also contributes to economic development on a grand scale. "SAP is recognized as a leader in demonstrating the highest level of integrity in its corporate governance and practices. These efforts are informed and driven by the core values of SAP – customer focus, integrity, quality, commitment, product excellence, and passion." 6
  • 15. 1.4 OBJECTIVE OF THE RESEARCH  Primary Objectives:  To identify the employees interest in implementation of SAP in finance department.  To identify the difference between SAP and other software using in finance department.  To identify employees satisfactory level by implementing SAP in SIC.  To identify the understanding level of employees towards SAP.  Secondary Objectives:  To identify additional areas of expertise that is contained within the organization.  To identify areas in which the staff would like to develop further.  To analyze the importance of SAP in finance department of an organization.  To identify the expectations of employees towards SAP. 7
  • 16. RESEARCH METHODOLOGY Research methodology is a way to systematically solve the research problem. 1.5 RESEARCH DESIGN “A research design is the arrangement of the conditions for the collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure”. The study is based on both ‘descriptive research’ and ‘Hypothesis testing research’. Descriptive research: The study is based on descriptive research descriptive research includes surveys and fact-finding enquiries of different kinds. The major purpose of descriptive research is description of state of affairs, as it exists as present. The main characteristics of this method are that the researcher has no control over the variables; he can only report what has happened or what is happening. The methods of research utilized in descriptive research are survey methods of all kinds, including comparative and correlation methods. Methods of data collection: The study is carried out with the help of the following methods of collection. 1. Primary data 2. Secondary data. Primary data: I have collected the primary data through the structured questionnaire from the employees of SIC 8
  • 17. Secondary data: The secondary data are gathered from various sources such as website SIC of newspapers, journals, magazines etc. Nature of data: In the survey the nature of data collected was primary, through the help of questionnaires. Questionnaire design: The questionnaire framed for the research study is a structured questionnaire in which all the questions are predetermined before conducting the survey. The form of questionnaire is of both closed and open type. Close-ended questions: The closed Type of questions is of 1. Dichotomous scale (Yes/No) 2. Likert 5-point scale (S.A,A,NA.ND,D.A,S.D.A) 3. Category scale (multiple items) Multiple-choice questions: In this case, the respondents are offered two or more choices. The respondent has to indicate which is applicable in this study. 9
  • 18. 1.6 SAMPLING DESIGN This survey will be carried out through stratified random sampling. Stratified Random sampling Under stratified random sampling the population is divided into several sub – populations that are individually more homogeneous than the total population ( the different sub – populations are called ‘ strata’ ) and then we select items from each stratum to constitute a sample. Since each stratum is homogeneous than the total population, we are able to get more precise estimates for each stratum and by estimating more accurately each of the component parts, we get a better estimates of the whole. In brief stratified sampling results in more reliable and detailed information. Sampling method The sample method used for the research is “stratified random sampling”, where the customers visiting the bank for transacting are administered with the questionnaire and were asked to answer the questions that help in determining their satisfaction level, awareness level and the perceived bank’s operating efficiency. Sampling size: A sample size of 250 has been taken for the purpose of the project. Data analysis and interpretation: Data collection: With the prepared questionnaire, where the respondents were approached in the appropriate time and at the appropriate places. 10
  • 19. Data analysis: Considering the manner of data collection adopted, the study analyzed the data on qualitative basis. Various options collected from respective respondents are analyzed separately. The statistical bank is a collection of statistical procedures for extracting managed information from data, it consists of usual statistical routines for calculating averages measures of dispersion and cross tabulation of data, percentages and ratios, which are highly useful when comparing two or more of data. Data analysis has been done for 250 samples. The graphical tools used are Bar Diagram, Pie Diagram, the statistical tools are percentage analysis, chi-square and ratio analysis, cash flow analysis and fund flow analysis. Data interpretation: The data from each and every user was analyzed and interpreted individually and then complied together and presented in the form of tables and charts. In each table, the total respondents answering for a particular question is noted. Among them the alternate answers were given and traced, finally, the percentage of each answer for particular option is traced. 11
  • 20. STATISTICAL TOOLS USED FOR ANALYSIS Chi-square test Chi-square test is a non parametric test used most frequently by marketing researchers to test the hypothesis. This test is employed for testing hypothesis when distribution of population is not known and when nominal data is to be analyzed. Chi-square test aims at determining whether a significant difference exists among the graphs or whether the differences are due to sampling. Chi-square test is similar to T test in which the degrees of freedom increase, where the distribution becomes more symmetrical and resembles the normal curve. The following is the formula for calculating chi-square test. X= (Oij-Eij) ^2 Eij Where Oij Observed Frequency Eij  Expected Frequency Analysis of Variance (ANOVA) Analysis of Variance is an extremely useful technique concerning researches in the economics, education, business/industry and researches of several other disciplines. This technique is used when multiple sample cases are involved. The ANOVA technique enables us to perform this simultaneous test and as such is considered to be an important tool of analysis in the hands of a researcher. Using this technique, one can draw inferences about whether the samples have been drawn from the populations having the same mean. 12
  • 21. Percentage analysis Percentage refers to a special kind of ratio. Percentages are used in making comparison between two or more series of data. Percentages are used to describe relationships. Percentages can also be used to compare the relative terms, the distribution of to be more series of data with a given table, it was difficult to interpret the table with absolute figures but when percentages are used, it is very easy to find the relative differences in distributions. Ratio analysis An analysis of financial statements based on ratios is known as ratio analysis. A ratio is a mathematical relationship between two or more items taken from the financial statements. It helps in measuring the profitability, solvency, and activity of a firm. Cash flow analysis It depicts the inflows and outflows of cash. Cash flow statement is the device for such analysis. It highlights causes which bring changes in cash position between two balance sheet dates. Fund flow analysis Fund flow analysis clearly shows internal and external sources of working capital and the way funds have been used. It is derived from the analysis of changes which have taken place in assets and equities between two balance sheet dates. It is helpful in judging the credit worthiness, financial planning and budget preparation. 13
  • 22. 1.7 HYPOTHESIS Hypothesis may be defined as a proposition or a set of proposition set forth as an explanation for the occurrence of some specified group of phenomena either asserted merely as a provisional conjecture to guide some investigation or accepted as highly probable in the light of established facts. HYPOTHESIS I There is no significant difference between the occupation and deposits. Null Hypothesis: There is no significant difference between the occupation and deposits. Alternative Hypothesis: There is a significant difference between the occupation and deposits. HYPOTHESIS II There is no significant difference between the perception and age. Null Hypothesis: There is no significant difference between the perception and age. Alternative Hypothesis: There is a significant difference between the perception and age. 14
  • 23. 1.8 EXPECTED CONRIBUTION OF THE RESEARCH This research work is will create the interest of the employees on SAP and this study is recommended to the employees about the company act ivies for understanding to the all the employees and also given some suggestion and technical view about the SAP and there performance in company. 15
  • 24. 1.9 LIMITATION OF THE STUDY  The study was undertaken only in the Chennai branch. Hence the conclusion drawn from thus study can’t be generalized.  The data has been collected with the help of structured schedule and the validity of the study depends, on the accuracy of the response given by the respondents.  Due to non availability of the all employees because of the tight schedule most of the respondents are reducing to give response.  Due to various factors associated the information provided by employees has its own bias  For collecting relevant information from employees prior appointment had to be fixed.  The method of survey was very expensive.  Major part of the work is concern with financial data, adequate was not able to pool because of secrecy maintain by the company.  The study revels the finding for the present and it will not reflect the future  The total cost factor involved in the entire training process 16
  • 26. 2.1 COMPANY PROFILE: Souh Indian Corporation (SIC) situated at Sipcot Industrial Park Irungattukottai, Sriperumpudur Taluk , Kanchipuram District is a wholly owned subsidiary M/s SIC project Indian Gmbh and belongs to the SIG group of Companies who at the market leaders in manufacturing equipments relating to construction industry more specifically for preparation transportation and placement of Ready Mix Concrete (RMC). SIC was incorporated as a private limited company on 18th June 1998 and the necessary permission was obtained from the Secretariat for industrial assistance. Ministry of industries Government of India for a 100% foreign holding. The Total market share in India for various types of construction equipments ranges between 40-65% respectively. The group is known for its quality products and has been recognized one of the best manufacturers of these equipments Looking at the design and software potential in India the group management decided to off load the group’s design and development work and software development works to the Indian company and accordingly SIC has set up a Software Technology park. The company has its good won at Pondicherry and branch offices at Mumbai, New Delhi, Kolkatta, Hyderabad, Behror (Rajasthan) and Bangalore. The Company has its Resident engineers stationed at Ahmadabad, Bangalore, Vizag, Belgaum, Kundankulam Camper, and Gaya & Chitogarh. The company completed construction of the new factory at Irungattukottai and commenced production in November 2001. The investment in the project was appox Rs14 Crores. The market appears very good for the infrastructure industry and considering the thrust on infrastructure development in India, SIC is confident of achieving better in the years to come with substantial growth and demand for quality equipment. 18
  • 27. Associated Enterprises: SIC Gmbh, Germany Herne: Founded in the year of 1934, The headquarters of the SIC Gmbh is the administrative and technical center of the whole SIC Group, as well as being the main production base for concrete pumps and placing booms, slurry pumps and fire fighting equipment in Herne alone the SIC Gmbh employs more than 900 persons. Memmingen: The headquarters of the SIC Gmbh, with a workforce of over 300, is located in Memmingen, Bavaria. This facility is the development and production centre for batching plants, truck mixers and concrete recycling plants. SIC Gmbh and SIC Gmbh have been team now for almost 20 years. SIC Gmbh, Austria: St. Stefam: This plant was founded as a subsidiary 30 years ago and employs more than 300 persons. St. Stefan Plant produces structural components for concrete pumps and placing booms. Vienna: After founding a production plant in Carinthia in 1971, SIC Opened a branch in Vienna in 1982 employing 8 persons. SIC America Inc: White Bear Lake: SIC America Inc., White Bear, Minnesota, has been serving the North American Market since 1974. White Bear is responsible for sales and service, as well as local production and truck mounting of the SIC and SIC products. 19
  • 28. 2.2 PRODUCT PROFILE OF THE COMPANY SIC – Group On March 17th 1934 Friedrich Wilhelm SIC established a company in Germany’s most important industrial area, the Ruhr Valley. SIC products major customers were in the mining industry, in road construction, in civil engineering and construction. When post-war reconstruction began in1945 the company Developed several types of machinery, some of which are still today of the art. Among Them were hoists an inevitable concrete and mortar mixing machines. The SIC company was founded in Memmingen, Bavaria and is in manufacturing concrete mixing machines SIC made the first oil-hydraulic double-cylinder pump. This construction principle has been taken over by almost all of today’s manufactures. In 1958 SIC started ready-mixed concrete with its first truck mixer two years later with the development of filling stations for truck mixers and in 1964, concrete batching plants with considerable capcities.In1965, SIC put the first truck mounted concrete pump on the market and upgraded it three years later by adding a placing boom. SIC also started activities in the field of environmental protection, building the first concrete recycling plant in 1976. In addition to the 900 employees in the headquarters in Herne (Including 77 trainees) the SIC group employs a further 1500 persons worldwide in production plants in Germany. Austria the USA, Brazil, Russia, China and India. They sales and service centre in France, the Nether land, Austria, the Czech Republic and Swden as well as representations in more than100 countries worldwide. The SIC group is the world’s No.1 System house in all matters concerning concrete from batching and mixing to transport. SIC’s concrete mixing plants represents the first link of a chain. SIC truck mixers take the concrete to the site. SIC concrete pumps make concrete alive, creating residential properties, tunnels, football stadiums or skyscrapers. The recycling of residual concreter guarantees a perfect use of concrete and environmental protection. Brief description of SIC’s Main Product Line: SIC’s product range as already indicated else where, caters to the equipment requirement mixing transporting and applying ready mix concrete at the project sites. The equipment manufactured by SIC with brief description are described below in the same order of the process. 20
  • 29. Batching Plants- Mixing Of Ready Mix Concrete (RMC) These plants in variant capacities are usually located within 100 km distance of the application sites, for mixing the RMC. The plant is manually controlled by a control panel, which software oriented, where the specification of the mixer can be fed and the plant will draw the raw materials in appropriate quantities for delivering the specified mixer specification. The micro control apparatus is entirely software driven. Functions Performed by SIC: The whole process of manufacture is carried out by SIC at its facility using the technology provided by the AE. Important functions that need to be mentioned in this context are: Raw Material Sourcing:  This consists of identification of sources of raw materials that are required for the purpose of manufacturing of concrete mixers pumps evaluating the competence and ability to deliver, placing through a process of venture evaluation placing of orders, quality inspection on receipt and organsing for contingency plans given the market environment in India.  The manufacturing process demand engineering skills and SIC carry out the function of recruiting, training, rewarding and retaining the relevant technical skills required for the manufacturing of the products.  Needless to say all support functions like accounting, human resources management are also within the province of SIC.  Functions relating to protection of assets through insurance are also carried out by SIC.  Market development assessment of market requirements ascertainment of demands and sales as per requirements of the Indian market and assumption of credit risks associated with the sales.  The function of operation to ensure availability of funds for procurement, process, cost, and personnel cost and sales and delivery cost is also carried out by the AE.  Warranty servicing of sales is also within the domain of SIC.  Taking care of all functions relating to managing and complying with the Indian laws and regulation connected with pollution control, labor and industrial legislations in carrying out its functions. 21
  • 30. 2.3 REVIEW OF LITERATURE: In 1972, five systems analysts began working nights and weekends to create standard software with real-time data processing. Twenty-five years later their vision is a reality: SAP is the world’s market and technology leader in business application software. On April 1, 1972 five former IBM employees founded SAP as System analyzes und Programment wicklung (“Systems Analysis and Program Development”) in Mannheim, Germany. Their vision was to develop and market standard enterprise software which would integrate all business processes. The idea came to them through their work as systems consultants for IBM when they noticed that client after client was developing the same, or very similar, computer programs. The second part of their vision was that data should be processed interactively in real-time, and the computer screen should become the focal point of data processing. From a start-up software vendor to global market leader over the course of twenty-five years, their vision has transformed SAP from a small regional enterprise into a world-class international company. Today, the SAP Group is the global market leader in enterprise resource planning software, and has subsidiaries, affiliates and branch offices in nearly every industrial nation in the world. Important milestones in the company's corporate history include its conversion to a GmbH (a closely-held corporation) in 1977, the opening of the company's headquarters in Walldorf, and its conversion into a publicly-held corporation whose shares are listed on several stock markets. By changing its structure to a publicly-held corporation, SAP significantly strengthened its capital base and laid the foundations for its employees to enjoy more of a share in the company's success. In the end, it is SAP’s employees – currently more than 9,000 of them - whose know-how, motivation and performance have 22
  • 31. nurtured the company’s progress. And it is their commitment and innovative drive which will pace the company’s future success and keep it ahead of the competition. Over one million R/3 users .Products have played the central role in SAP’s success story. In this area, two milestones stand out: first, the development and 1979 market release of the R/2 software system for mainframes, and, second, the R/3 client/server software system introduced in 1992. Since its debut, the R/3 System use has grown explosively and now accounts for the lion's share of SAP product sales. At present, more than one million end users around the world work with the R/3 System. The development of SAP products has continually benefited from major advances in the hardware sector. Back in 1972, the limited storage capacity of computers posed one of the biggest challenges. In those days, mainframes only had 500 kilobytes of storage capacity. Slow data input and output meant that only partial applications with a limited data volume were feasible. It was against this technological background that SAP signed its first customer, the German ICI subsidiary in stringer. With the successful implementation of its initial project, SAP had nine employees and, at the end of its first fiscal year, posted a profit on revenues of DM 620,000. In the second year of operation, two local businesses – the tobacco and cigarette manufacturer Roth-Handle and the pharmaceutical company Knoll - selected the newly developed SAP Financial Accounting (RF) System. This system quickly earned a reputation as an excellent standard package and installations expanded to 40 customers. But product development did not slow on this success, and a second standard product, the Materials Management (RM) System, with modules for purchasing, inventory management and invoice verification, soon followed. The benefits of SAP's integration philosophy showed through, with data from Materials Management flowing straight into Financial Accounting. SAP moves to Walldorf. In its fifth year of operations, SAP became a GmbH (a closely-held corporation) and took on a new name: System, Anwendungen, Product in deer Datenverarbeitung ("Systems, Applications, Products in Data 23
  • 32. Processing"). Revenues were now close to DM 4 million, and the number of employees had grown to 25. In 1977, SAP moved its offices and headquarters to Walldorf. In the same year, it signed its first two foreign customers, two companies from Austria. Just one year later, the customer base had grown to 100 and the number of employees stood at 50. SAP had also introduced another central module of the SAP System – Asset Accounting (RA). At the same time, through the development of a French version of the accounting module, SAP made additional steps toward the international markets. By the end of the 1970s, new generations of powerful computers provided the framework for a comprehensive software system, and a major step in the development of SAP software - the R/2 System – was taken in 1978. In the same year, as sales headed toward the DM 10 million milestones, SAP began operation of its own computer center in Walldorf which, when completed in 1980, united development teams under one roof. That year SAP’s software became even more attractive with the addition of order history to the product range. At the end of 1980, 50 of the 100 largest industrial companies in Germany were SAP customers. R/2 System goes international SAP’s close relationships with customers led to continuous enhancements in the existing program modules, while important new additions were made, such as the Cost Accounting (RK) System. The R/2 System was now ready for the international market. New computers with drastically improved price/performance ratios helped expand the customer base, and SAP raised its profile still further by appearing at the Systems trade fair in Munich - the company's first- ever presence at an industry trade show. In 1982, SAP celebrated its tenth anniversary, with sales soaring 48% to over DM 24 million. By the end of the year, 236 companies in Germany, Austria and Switzerland were working with the SAP standard programs. Sales continued to climb in the following year, increasing by 45%. 24
  • 33. In 1984 SAP took additional steps into the international arena with the founding of SAP (International) AG in Switzerland, whose focus was to increase sales of the R/2 System in international markets. Development teams began work on two new applications, Personnel Management and Plant Maintenance, while the Production Planning and Control System was installed at its first pilot customers. 1985 was characterized by further expansion. The Walldorf headquarters had grown to 10,000 square meters of space, while at the Swiss subsidiary a new headquarters was occupied. SAP systems were now in use in most European countries, and SAP began to penetrate markets outside Europe - with customers in South Africa, Kuwait, Trinidad, Canada and the US. The DM 100 million sales mark exceeded SAP continued to pursue international growth with the founding in 1986 of SAP’s Austrian subsidiary SAP Österreich Ges.m.b.H. in Vienna. At the parent company, SAP GmbH, the capital stock was increased from DM 500,000 to DM 5 million. The largest single hardware investment to date was made in Walldorf with the installation of an IBM mainframe costing DM 7 million. The year's sales topped DM 100 million, and SAP exhibited at CeBIT, the world's largest IT trade fair, for the first time. The 15th year of the company's history was again characterized by powerful growth. Branch offices were opened in Munich and Hamburg, and subsidiaries established in four European countries - the Netherlands, France, Spain and the UK. Staff grew to 750, and sales more than doubled to DM 245 million, with 850 companies now using SAP's software systems. In 1987, SAP announced its strategy for a new generation of software, and the R/3 System was born. SAP goes public SAP continued to grow in 1988 with the international sales network strengthened by the establishment of subsidiaries in Denmark, Sweden, Italy and the US. Other events included: the founding of SAP Consulting GmbH as a joint project between SAP and the consulting firm Arthur Andersen; the opening of an International Training Center in Walldorf; and the welcoming of Dow Chemical as 25
  • 34. SAP’s 1,000th customer. However, the most significant events of the year were the increase of SAP’s capital stock from DM 5 million to DM 60 million, the subsequent conversion of SAP GmbH into a stock corporation, SAP AG During the next year, 1989, SAP shares began trading on the Zurich stock exchange. SAP expanded its alliance and strategic cooperation approaches by taking a majority investment in TOS GmbH in Freiberg. Through the "International User Conference" in Lausanne, Switzerland, and the first "SAPPHIRE" user conference in North America, SAP demonstrated its solid commitment to direct international customer contact. This crucial commitment was to become more and more important to SAP’s success in the coming years. Over 1,000 employees SAP (International) soon grew to twelve subsidiaries, including Canada, Singapore and Australia. SAP's growing profile in 1989 was evidenced by a number of events: the large number of participants attending the first Annual Stockholders' Meeting, the strong employee growth to more than 1,000, and the expansion of the customer base. Recognizing this success manager magazin named SAP "Company of the Year" – a distinction SAP would receive twice more in the next few years. In 1990, SAP's capital stock was expanded to DM 85 million with the issue of preference shares. SAP strengthened its commitment to small- and medium- sized businesses by an investment in the software company Steeb and the acquisition of software vendor CAS. In the same year, SAP and Siemens Nixdorf founded SRS GmbH in Dresden, gaining a firm foothold in the East German market. Sales grew strongly to over DM 500 million, and the number of staff grew to 1,700. SAP develops Russian R/2 version Strong growth continued unabated in 1991. The acquisition of Steeb GmbH was completed and its activities were merged with CAS to form STEEB-CAS GmbH, creating a high-caliber software company with an attractive product offering for the small- and medium-sized company market. With SAP’s Eastern European business developing quickly, SAP collaborated 26
  • 35. with a local Russian software company to develop an R/2 version in Russian. The first Japanese installation of SAP software was successfully completed. At the end of the fiscal year, the SAP Group boasted 2,225 customers in 31 countries and sales of more than DM 700 million – an increase of over 40 percent. The company had more than 2,500 employees. In its twentieth year, SAP opened a new Development and Sales Center in Walldorf. The two-year project cost roughly DM 140 million and represented the company's largest single investment to date. In preparation for additional development, SAP’s share capital was expanded by DM 15 million to DM 100 million through the issue of 300,000 preference shares. SAP was now firmly established as a global company, with South Africa, Malaysia and Japan the newest additions to its 15 subsidiary companies. By 1992, almost half of the DM 831 million in product revenues were being generated outside Germany, and the availability of the software in 14 different languages was adding significantly to its attractiveness. Shipment of the client/server system R/3 With the R/3 System release in mid-1992, SAP began to penetrate the mid-size market, and into branches and subsidiaries of large companies. The release of the R/3 client/server system was the most significant event in SAP’s history and started a record of growth that even SAP’s most optimistic planners had not predicted. SAP took top position among German software vendors in 1993. On an international scale, the company moved to 7th place among software companies, establishing a clear lead in the global business applications software market. Sales surpassed the important DM 1 billion mark for the first time in 1993, and the global customer base stood at 3,500 companies. SAP made an investment in iXOS Software GmbH with the aim of developing and marketing graphical user interfaces and optical archiving of documents. New development center in Foster City, California Releases 2.0 and 2.1 provided R/3 users with even more functionality. With the R/3 System already running on six hardware 27
  • 36. platforms, SAP and Microsoft signed an agreement to port R/3 to Windows NT. Other events included: the founding of SAP’s 18th subsidiary in the Czech Republic, the establishment by SAP America of a development center in Foster City in Silicon Valley, California, and the introduction by SAP Japan of a Kanji version of R/3. 1994 was yet another record-breaking year with sales jumping 66% to over DM 1.8 billion. By the end of the year, SAP employed more than 5,000 staff worldwide, and 200 of the more than 4,000 customers were using the R/3 System in production operation. A Swiss customer was the first customer to go live with R/3 on Microsoft’s Windows NT – a mere four months after the platform became available. Since its rollout in 1992, R/3 had now been installed more than 1,000 times. SAP development received ISO 9000 certification, and R/3 Release 2.2 was completed on schedule and included a wide range of enhancements in Logistics. SAP continued to expand its sales organization and strategic alliances. In Germany, SAP acquired a 52% stake in DACOS Software GmbH with the aim of developing an integrated software solution for the retail industry. The 19th subsidiary opened in Mexico City. The Annual Stockholders' Meeting agreed to a DM 400 million capital increase out of retained earnings, bringing total capital to DM 500 million. The resulting 1:4 stock split was positively received by the market and led to a significant increase in stock price levels. Microsoft chooses R/3 more than 6,000 companies of all sizes were among SAP customers in 1995, some two-thirds of which solved their IT tasks using the R/3 System. During the year Microsoft joined IBM as an R/3 customer from the high- tech sector. In 1995, R/3 became the largest source of overall revenues, with a DM 1.7 billion share of total sales of DM 2.7 billion. Growth prospects were strengthened still further with the new R/3 Release 3.0, a functional and technical milestone in R/3 development. With this version the important areas of production planning and control were now comprehensively covered. Another technical addition was the availability of R/ 3 on the widely used IBM AS/400 platform. 28
  • 37. CHAPTER III DATA ANALYSIS & INTERPRETATION 29
  • 38. 3.1 DATA ANALYSIS AND INTERPRETATION Table 1 DISTRIBUTION OF RESPONDENTS BASED ON THE GENDER S No Particulars Respondents Percent 1 Male 177 69 2 Female 73 31 3 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 1 shows the distribution of employees based on the gender. From the above table it is inferred that 69% belong to the male category, 31% belong to the female category. Chart 1 DISTRIBUTION OF RESPONDENTS BASED ON THE GENDER Frequency 200 180 160 140 120 100 Frequency 80 60 40 20 0 male female 30
  • 39. Table 2 DISTRIBUTION OF RESPONDENTS BASED ON THEIR AGE S No Particulars Respondents Percent 1 Below 20 57 23 2 21-35 131 52 3 36-45 47 19 4 46-65 15 6 5 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 2 shows that distribution of respondents based on the age wise classification From the above table 23% belong to the below20years, 52%belong to the21-35 years,19% belong to the 36-45years, 6% belong to the 46-65years. Chart 2 DISTRIBUTION OF RESPONDENTS BASED ON THEIR AGE Frequency 140 120 100 80 Frequency 60 40 20 0 below20 21-35 36-45 46-65 31
  • 40. Table 3 DISTRIBUTION OF RESPONDENTS BASED ON THEIR SOFTWARE USAGE S No Particulars Respondents Percent 1 SAP 214 85 2 TALLY 29 12 5 3 FOXPRO 2 4 MANUALLY 2 1 5 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 3 shows that distribution of respondents based the SOFTWARE USAGE From the above Table 85% belong to the SAP 12%belong to the tally, 2% belong to the FoxPro, 1% belong to the manually. Chart 3 DISTRIBUTION OF RESPONDENTS BASED ON THEIR SOFTWARE USAGE Frequency MANUALLY FOXPRO Frequency TALLY SAP 0 100 200 300 32
  • 41. Table 4 DISTRIBUTION OF RESPONDENTS BASED ON THEIR EXPERIENCE S No Particulars Respondents Percent 1 Below 1Yr 94 38 2 1-2 Years 111 44 3 2-4 Years 24 10 4 > 4 Years 21 8 5 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 4 shows that distribution of respondents based on their experience. From the above table 38% belong to the below one year, 44% belong to the 1-2years, 10% belong to the 2-4 years, 8% belong to the more than 4 years. Chart 4 DISTRIBUTION OF RESPONDENTS BASED ON THEIR EXPERIENCE Frequency MORETHAN 4 YEARS 2-4YEAR Frequency 1-2YEAR BELOW 1YEAR 0 50 100 150 33
  • 42. Table 5 DISTRIBUTION OF RESPONDENTS BASED ON THEIR REQURIMENTS FULLFILLD S.No Particulars Respondents Percent 1 EXCELLENT 44 17 2 GOOD 139 55 3 O.K 64 26 4 NOT GOOD 3 2 5 TOTAL 250 100 Sources: Data collected from respondents INTERPRETATION: Table 5 shows that distribution of respondents based the requirement fulfilled. From the above chart 17% belong to the Excellent, 55% belong to the Good, 26% belong to the O.K, 2% belong to the Not good. Chart 5 DISTRIBUTION OF RESPONDENTS BASED ON THEIR REQURIMENTS FULLFILLD Frequency EXCELLENT GOOD O.K NOT GOOD 34
  • 43. Table 6 DISTRIBUTION OF RESPONDENTS BASED ON THE TIME EFFICIENT S.No Particulars Respondents Percent 1 FASTER 86 34 2 MODERATE 27 51 3 SLOW 37 15 4 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 6 shows that distribution of respondents based on the Time efficient. From the above table 34% belong to the Faster, 51% belong to the Moderate, 15% belong to the Slow. Chart 6 DISTRIBUTION OF RESPONDENTS BASED ON THE TIME EFFICIENT EFFICIENT Frequency 140 120 100 80 60 40 20 0 FASTER MODERATE SLOW Frequency 86 127 37 35
  • 44. Table 7 DISTRIBUTION OF RESPONDENTS BASED ON THE COST OF SAP S.No Particulars Respondents Percent 1 HIGH COSTLY 120 48 2 AFFORDABLE 78 31 3 ECONOMICAL 52 21 4 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 7 shows that distribution of respondents based on the Cost factor. From the above table 48% belong to the High costly,31% belong to the Affordable, 21% belong to the Economical, Chart 7 DISTRIBUTION OF RESPONDENTS BASED ON THE COST OF SAP 36
  • 45. Frequency AL IC M O N O Frequency EC LE AB D R FO AF LY ST O C 0% 50% 100% H IG H Table 8 DISTRIBUTION OF RESPONDENTS BASED ON THE CONFIDENTIALITY S.No Particulars Respondents Percent 1 EXCELLENT 53 21 2 GOOD 153 61 3 O.K 40 16 4 NOT FAVOUR 4 2 5 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 8 shows that distribution of respondents based on confidentiality. From the above chart 21% belong to the Excellent, 61% belong to Good, 16% belong to the ok, 2% belong to the Not favour. Chart 8 DISTRIBUTION OF RESPONDENTS BASED ON THE CONFIDENTIALITY 37
  • 46. Frequency EXCELLENT GOOD O.K NOT FAVOUR Table 9 DISTRIBUTION OF RESPONDENTS BASED ON THE QUALITY OF SERVICE S.No Particulars Respondents Percent 1 EXCELLENT 54 22 2 GOOD 148 59 3 O.K 48 19 4 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 9 shows that distribution of respondents based on the Quality service. From the above table 22% belong to the Excellent, 59%belong to the Good, 19% belong to the OK. Chart 9 DISTRIBUTION OF RESPONDENTS BASED ON THE QUALITY OF SERVICE 38
  • 47. Frequency 150 100 50 Frequency 0 Frequency EXCELLENT GOOD O.K Table 10 DISTRIBUTION OF RESPONDENTS BASED ON THE DATA LOSSAGE S.No Particulars Respondents Percent 1 YES 67 27 2 NO 128 51 IN SOME OCCASION 3 55 22 ONLY Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 10 shows that distribution of respondents based on the Data lossage. From the above table 27% belong to the Yes, 51% belong to the No, 22% belong to the some occasion only. 39
  • 48. Chart 10 DISTRIBUTION OF RESPONDENTS BASED ON THE DATA LOSSAGE Frequency 140 120 100 80 60 40 20 Frequency 0 Frequency YES NO OCCASION IN SOME ONLY Table 11 DISTRIBUTION OF RESPONDENTS BASED ON THEIR TRAINING S.No Particulars Respondents Percent 1 YES 131 53 2 NO 119 47 3 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 11 shows that distribution of respondents based on the training from the above table 53% belong to the Yes, 47% belong to the No. 40
  • 49. Chart 11 DISTRIBUTION OF RESPONDENTS BASED ON THEIR TRAINING Frequency 132 130 128 126 124 122 Frequency 120 118 116 114 112 YES NO Table 12 DISTRIBUTION OF RESPONDENTS BASED ON THE DURATION OF TRAINING S.No Particulars Respondents Percent 1 YES 82 33 2 NO 168 67 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 12 shows that distribution of respondents based on training. From the above table 33% belong to the Yes and 67% belong to the No. Chart 12 DISTRIBUTION OF RESPONDENTS BASED ON THE DURATION OF TRAINING 41
  • 50. Frequency NO Frequency YES 0 50 100 150 200 Table 13 DISTRIBUTION OF RESPONDENTS BASED ON THE TRAINING EXPECTATION S.No Respondents Percent Particulars 1 1MONTH 67 27 2 2-3MONTH 151 60 3 3-4MONTH 32 13 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 13 shows that distribution of respondents based on the training expectation. From the above table 27% belong to the one month, 60% belong to the 2-3 month, 13% belong to the 3-4 month. 42
  • 51. Chart 13 DISTRIBUTION OF RESPONDENTS BASED ON THE TRAINING EXPECTATION Frequency 160 140 120 100 80 Frequency 60 40 20 0 1MONTH 2-3MONTH 3-4MONTH Table 14 DISTRIBUTION OF RESPONDENTS BASED ON THE ADDITIONAL TRAINING S.No Particulars Respondents Percent 1 YES 150 60 2 NO 100 40 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 14 shows that distribution of respondents based on additional training. From the above table 60% belong to the Yes and 40% belong to the No. 43
  • 52. Chart 14 DISTRIBUTION OF RESPONDENTS BASED ON THE ADDITIONAL TRAINING Frequency NO YES Table 15 DISTRIBUTION OF RESPONDENTS BASED ON THE EMERGING TECHNOLOGY S.No Particulars Respondents Percent 1 YES 163 65 2 NO 87 35 3 Total 250 100 Sources: Data collected from respondents INTERPRETATION: 44
  • 53. Table 15 shows that distribution of respondents based on emerging technology. From the above table 65% belong to the Yes and 35% belong to the No. Chart 15 DISTRIBUTION OF RESPONDENTS BASED ON THE EMERGING TECHNOLOGY Frequency NO 87 163 YES 0 50 100 150 200 Frequency Table 16 DISTRIBUTION OF RESPONDENTS BASED ON THE CO-ORDINATION S.No Particulars Respondents Percent 1 YES 177 70 2 NO 73 30 3 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 16 shows that distribution of respondents based on the co-ordination. From the above table 70% belong to the Yes and 30% belong to the No. 45
  • 54. Chart 16 DISTRIBUTION OF RESPONDENTS BASED ON THE CO-ORDINATION S.No Particulars Respondents Percent 1 YES 177 60 2 NO 73 40 3 Total 250 100 Frequency 180 160 140 120 100 Frequency 80 60 40 20 0 YES NO Table 17 DISTRIBUTION OF RESPONDENTS BASED ON THE TECHNOLOGY DRIVEN Sources: Data collected from respondents INTERPRETATION: Table 17 shows that distribution of respondents based on technology driven. From the above chart 60% belong to the Yes, and 40% belong to the No. 46
  • 55. Chart 17 DISTRIBUTION OF RESPONDENTS BASED ON THE TECHNOLOGY DRIVEN Frequency 200 180 160 140 120 100 Frequency 80 60 40 20 0 YES NO Table 18 DISTRIBUTION OF RESPONDENTS BASED ON THE COMPLETE PACKAGE S.No Particulars Respondents Percent 1 YES 176 70 2 NO 74 30 Total 250 100 3 Sources: Data collected from respondents INTERPRETATION: Table 18 shows that distribution of respondents based on the complete package. From the above table 70% belong to the Yes, and 30% belong to the No. 47
  • 56. Chart 18 DISTRIBUTION OF RESPONDENTS BASED ON THE COMPLETE PACKAGE 180 160 140 120 100 Frequency 80 60 40 20 0 YES NO Table 19 DISTRIBUTION OF RESPONDENTS BASED ON THE SATISFICATION LEVEL S.No Particulars Respondents Percent 1 YES 156 62 2 NO 94 38 3 Total 250 100 Sources: Data collected from respondents INTERPRETATION: Table 19 shows that distribution of respondents based on satisfaction level. From the above table 62% belong to the Yes and 38% belong to the No. 48
  • 57. Chart 19 DISTRIBUTION OF RESPONDENTS BASED ON THE SATISFICATION LEVEL Frequency NO YES Table 20 DISTRIBUTION OF RESPONDENTS BASED ON THE USAGE OF SAP S.No Particulars Respondents Percent 1 EXHAUSTIVELY 74 29 2 MODERATE 155 61 3 MINIMUM 19 10 4 Total 248 100 Sources: Data collected from respondents INTERPRETATION: Table 20 shows that distribution of respondents based on usage of sap. From the above table 29% belong to the Exhaustively, 61% belong to the Moderate, 10% belong to the Minimum. 49
  • 58. Chart 20 DISTRIBUTION OF RESPONDENTS BASED ON THE USAGE OF SAP Frequency MINIMUM MODERATE Frequency EXHAUSTIVELY 0 50 100 150 200 3.2 STATISTICAL TOOLS FOR ANALYSIS CORRELATIONS Ho: There is no significant difference between the time efficient and implementation cost. H1: There is significant difference between the time efficient and implementation cost... 50
  • 59. Correlations IMPLEMENTATION TIME EFFICIENT COST Pearson 1.000 .384** Correlation TIME EFFICIENT Sig. (2-tailed) .000 N 250.000 250 Pearson .384** 1.000 IMPLEMENTATION Correlation COST Sig. (2-tailed) .000 N 250 250.000 *** Correlation is significant at the 0.01 level (2-tailed) RESULT: Ho is accepted. Significant level is (.000). CHI-SQUARE TEST Ho: There is no significant difference between the confidentiality and quality. H1: There is significant difference between the time confidentiality and quality. Frequencies 51
  • 60. Confidentiality Observed N Expected N Residual EXCELLENT 53 62.5 -9.5 GOOD 153 62.5 90.5 O.K 40 62.5 -22.5 NOT FAVOUR 4 62.5 -58.5 Total 250 Quality Observed N Expected N Residual EXCELLENT 54 83.3 -29.3 GOOD 148 83.3 64.7 O.K 48 83.3 -35.3 Total 250 52
  • 61. Test Statistics Confidentiality Quality 195.344a 75.488b Chi-Square 3 2 df .000 .000 Asymp. Sig. A) 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 62.5. B). 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 83.3. RESULT: Ho is accepted. Significant level is (.000). SAMPLE KOLMOGOROV-SMIRNOV TEST 53
  • 62. Ho: There is no significant difference between the sap usage and fulfilled. H1: There is significant difference between the sap usage and fulfilled. One-Sample Kolmogorov-Smirnov Test SAPUSAGE FULLFILLED N 250 250 Normal Parameters Mean 1.8880 2.1040 Std. .89367 .68634 Deviation Most Extreme Differences Absolute .270 .292 Positive .270 .292 Negative -.174 -.264 Kolmogorov-Smirnov Z 4.271 4.620 Asymp. Sig. (2-tailed) .000 .000 a. Test distribution is Normal. RESULT Ho is accepted. Significant level is (.000). ONE-WAY Ho: There is no significant difference between the sap usage and fulfilled. 54
  • 63. H1: There is significant difference between the sap usage and fulfilled. ANOVA TECHNOLOGY DRIVEN Sum of Squares df Mean Square F Sig. Between Groups 1.141 3 .380 1.537 .206 Within Groups 60.895 246 .248 Total 62.036 249 RESULT Ho is not accepted. Significant level is (.206). PAIRED SAMPLES STATISTICS Ho: There is no significant difference between the coordination and emerging technology. 55
  • 64. H1: There is significant difference between the coordination and emerging technology. Paired Samples Statistics Mean N Std. Deviation Std. Error Mean Pair 1 COORDINATION 1.2920 250 .45559 .02881 EMERGING 1.4320 250 1.06297 .06723 TECHNOLOGY Paired Samples Correlations N Correlation Sig. COORDINATION & EMERGING Pair 1 250 -.029 .644 TECHNOLOGY 56
  • 65. Paired Samples Test Paired Differences 95% Confidence Std. Std. Error Interval of the Sig. (2- Mean t df Deviation Mean Difference tailed) Lower Upper P a COORDINATIO i -1.894 N - EMERGING -.14000 1.16870 .07392 -.28558 .00558 249 .059 r E0 TECHNOLOGY 1 RESULT: 95% Confidence interval of the difference (lower -.285) & (upper .005) Ho is accepted. 57
  • 66. CHAPTER IV FINDINGS & CONCLUSION 58
  • 67. 4.1 FINDINGS The Findings of the study are  From the data analysis it is inferred that 70% belong to the male category, 30% of the respondents belong to the female category.  From the data analysis it is inferred that 23% belong to the below 20years category, 52% of the respondents belong to the 21-35 category, 19% belong to the 36-45 category, 6% belong to the 46-65 category.  From the data analysis it is inferred that 85% belong to the Sap category, 12% of the respondents belong to the tally category and 2% belong to the manually.  From the data analysis it is inferred that 37% belong to the below one year, 44% belong to the 1-2 years, 10% belong to the 2-4 years 9% belong to the more than 4 years.  From the data analysis it is inferred that 17% belong to the excellent category, 55% belong to the good, 26% belong to the o.k., 2% belong to the not good.  From the data analysis it is inferred that 34% belong to the faster category, 51% belong to the moderate, and 15% belong to the slow.  From the data analysis it is inferred that 48% belong to the high costly category, 31% belong to the affordable, and 21% belong to the economical.  From the data analysis it is inferred that 21% belong to the excellent category, 31% belong to the good, 16% belong to the o.k., 2% belong to the nof favour  From the data analysis it is inferred that 22% belong to the excellent category, 59% belong to the good, and 19% belong to the o.k.  From the data analysis it is inferred that 27% belong to the yes category, 59% belong to the no, and 22% belong to the some occasion only.  From the data analysis it is inferred that 52% belong to the yes category, 48% belong to the no.  From the data analysis it is inferred that 33% belong to the yes category, 67% belong to the no, and 22% belong to the some occasion only. 59
  • 68.  From the data analysis it is inferred that 27% belong to the one year category, 60% belong to the 2-3, and 13% belong to the 3-4.  From the data analysis it is inferred that 60% belong to the yes category, 40% belong to the no.  From the data analysis it is inferred that 65% belong to the yes category, 35% belong to the no  From the data analysis it is inferred that 70% belong to the yes category, 30% belong to the no  From the data analysis it is inferred that 70% belong to the yes category, 30% belong to the no  From the data analysis it is inferred that 70% belong to the yes category, 30% belong to the no  From the data analysis it is inferred that 70% belong to the yes category, 30% belong to the no  From the data analysis it is inferred that 62% belong to the yes category, 38% belong to the no  From the data analysis it is inferred that 29% belong to the exhaustively category, 29% belong to the moderate category, 8% belong to the minimum category. 60
  • 69. 4.2 SUGGESTIONS: Suggestions based on the study are:  The organization can take some measures to improve the career development of the employees in using the SAP applications more effectively in the organization.  Company should provide additional training program in SAP applications to improve the organization standards.  The quality of SAP service provider and day to day operation should improve.  The company must give the additional training on any changes, updation, upgradation with regards to SAP  The company should reduce the cost for implementation of SAP to lower level.  The company should provide awareness of SAP for all employees.  The company must adopt new technologies to increase the Knowledge there by it can increase the effectiveness of the employees. 61
  • 70. 4.3 CONCLUSION In SIC all the departments are using SAP. But implementation and testing works are made by Germany. By using SAP in SIC all employees are satisfied .From the study it is known that employees at SIC are happy with implementation of sap and they are working efficiently and effectively by saving. Thus implementation of sap has improved the satisfaction level of employees. 62
  • 71. BIBLIOGRAPHY Joghnson CM. Implementation of SAP, 2nd Edn. Oxford University Publication: London, pp 45–52. Singaravelu CVK. Probability and Statistics, 3rd Edn. Amudham Publications: Chennai, India, p. 228. Kothari CR. Research Methodology, 2nd Edn. Newage Publication: New York, pp 128– 182. Williams LK. Basic Concepts of SAP, 3rd Edn. Emerald Group Publication Limited: Paris, France, p. 248. Pannierselvam KV. Enterprise Resources Planning, 3rd Edn. Himalaya Publications: New Delhi, India, pp 248–250. Savkin AV, Petersen IR. Management Concepts and Statistical Analysis (USA) 1999; 44: 1037–1041 Rafaely B. Advanced concepts of Enterprise Resource Planning. PhD thesis, University of Southampton, UK, 1997. http://adsabs.harvard.edu/abs/1997PhDT.......115R Premount A. Vibration Control of Project Report. 2nd edn. Springer Verlag, 2002 Pal B, Chaudhuri B. Robust Systems Application Products in Data Processing. Springer Verlag, 2005 Isidori A, Byrnes CI. Global Industrial Database and Control 1990; 25: 131–140 Marconi L, Praly L, Isidori A. Mathematics for Management Studies. SIAM J Control Optim (USA) 2007; 45: 2277–2298 63
  • 72. Annexure I THE EFFECTIVENESS OF SAP IMPLEMENTATION IN FINANCE DEPARTMENT WITH REFERENCE TO SOUTH INDIAN CORPORATION 1) NAME: __________________ 2) Designations : __________________ 3) AGE: ___________________ 4) GENDER: Male Female 5) Which Software package tool you are using in your finance department? a) SAP b) Tally c) FoxPro d) Manually 6) Since how long you are using SAP? a) Below 1year b) 1-2 years c) 2-4 years d) More than 4 years 7) Has SAP fulfilled your requirements with regard to formats of Accounts Receivables, Payables & other General ledgers? a) Excellent b) Good c) O.K d) Not good 8) How Time efficient is SAP? a) Faster b) Moderate c) Slow 9) Your opinion on implementation cost of SAP? a) High costly b) Affordable c) Economical 10) SAP contribution in maintain confidentiality in finance department? a) Excellent b) Good c) Ok d) Not favour 11) How do you rate the quality of service by your SAP service provider? a) Excellent b) Good c) Ok d) Poor 12) Have you come across any data loss after the SAP being installed? a) Yes b) No C) In some Occasions only? 13) Does Company provide initial training on SAP to employees? a) Yes b) No 64
  • 73. 14) If yes, is the duration of training is sufficient? a) Yes b) No 15) If no, how many month do you expecting for such training? a) 1 months b) 2-3 month c) 3-4 month d) more than4 16) Does the company is giving additional training on any changes, updation, Upgradation with regard to SAP? a) Yes b) No 17) Will SAP hold well in the emerging technology? a) Yes b) No 18) In your Opinion, Is there proper co-ordination between finance department and other departments with regard to data processing? a) Yes b) No 19) Is SAP Technology driven? a) Yes b) No 20) In your Opinion, Is SAP a Complete Package? a) Yes b) No 21) Are you satisfied with SAP in your department? a) Yes b) No 22) To what extent you are using SAP? a) Exhaustively b) Moderate c) Minimum I SINCERELY THANK YOU FOR YOUR CO-OPERATION T. Dinesh Babu, B.E., M.B.A., 65