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CHAPTER 4 – DATA PRESENTATION AND ANALYSIS

4.1 General

This chapter discusses the data analysis of the research. Quantitative data has been

gathered from primary and secondary data sources have been analyzed in this

section. Primary data has been gathered from focus groups through the survey.

Initially the demographic data are presented, related to the respondents who

participated for the survey. Software known as SPSS version 16.0 and Microsoft

excel has been used to analyze the collected data. Statistical calculations such as

mean, standard deviation and median values have been calculated using SPSS and

Microsoft excel where appropriate.

4.2 Characteristics of Responses

This section summarizes the characteristics of the respondents of the research.

Table 4.1: Industry wise Distribution of Respondents

Frequency Percent Valid

Percent Cumulative

Percent

Valid Manufacturing 45 49.5 49.5 49.5

Service 32 35.2 35.2 84.6

Retail 12 13.2 13.2 97.8

Other 2 2.2 2.2 100.0

Total 91 100.0 100.0

Organizations in different industry sectors such as manufacturing, service, retail and

other sectors were studied under the research. Majority of respondents have received

from manufacturing sector with 49.5%. Service sector and retail sectors have become

the second and third respectively in the industry wise distribution of respondents in

the sample.

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Table 4.2: Educational level Distribution of the Sample.

Frequency Percent

Valid Percent

Cumulative Percent

Valid Postgraduate Degree 17 18.7 18.7 18.7

Bachelors Degree 29 31.9 31.9 50.5

Diploma 20 22.0 22.0 72.5

Certificate 17 18.7 18.7 91.2

Other 8 8.8 8.8 100.0

Total 91 100.0 100.0 The distribution of level of education of respondents is as shown in Table 4.2.

Majority of the respondents are graduates who are 50.5% of total respondents. 22%

of participant’s posses a Diploma and 18.7% participant are having at least a

certificate level qualification. 91 total numbers of responses were considered in the

research.

Table 4.3: Total ERP Experience Distribution of the Sample

Frequency Percent

Valid Percent

Cumulative Percent

Valid

Years

2 ≥ E ≥0 36 39.56 39.56 39.56

5 ≥ E >2 45 49.45 49.45 89.01

10≥ E >5 9 9.89 9.89 98.90

15 ≥ E >10 1 1.10 1.10 100.00

Total 91 100.0 100.0

The distribution of level of experience of respondents is as shown in Table 4.3. 49%

of respondents are having the experience between 2 to 5 years and 40% are having 0

to 2 years experience.

Summarizes the experience level of the respondents the results says average 3.6 years

total ERP experience with standard deviation of 2 years experience of the

respondents.

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Table 4.4 summarizes the ERP package characteristics.

Table 4.4: ERP Package Characteristics

Frequency Percent

Valid Percent

Cumulative Percent

Valid Standard package 16 17.6 17.6 17.6

Standard package with customization

73 80.2 80.2 97.8

Non standard package (Developed on company requirement)

2 2.2 2.2 100.0

Total 91 100.0 100.0

According to the Table 4.4, 80.2 % of respondents, the majority use standard

packages with customization. Non standard packages developed on company

requirement reported minimum of 2.2% of total responses.

Table 4.5: ERP Vendor Distribution

Frequency Percent

Valid Percent

Cumulative Percent

Valid SAP 26 28.6 28.6 28.6

Microsoft Dynamics

23 25.3 25.3 53.8

IFS 12 13.2 13.2 67.0

Oracle 10 11.0 11.0 78.0

Sage Accpac 11 12.1 12.1 90.1

Web ERP 6 6.6 6.6 96.7

Other 3 3.3 3.3 100.0

Total 91 100.0 100.0

ERP vendor wise distribution as per the respondent feedback is shown in Table 4.5.

SAP and Microsoft Dynamics ERP packages has recorded as most commonly used

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ERP packages in the sample.IFS, Sage Accpacc and Oracle, Web ERP and Other

ERP packages records higher usage other than to SAP and Microsoft Dynamics in

the sample.ERP vendor penetration of the sample is shown in Figure 4.1

Figure 4.1: ERP Vendor Penetration of the Sample

Table 4.6: ERP Modular Distribution-Finance

Frequency Percent

Valid Percent

Cumulative Percent

Valid 0 2 2.2 2.2 2.2

Finance Module

89 97.8 97.8 100.0

Table 4.6 shows almost 97.8% use Finance module in their ERP packages.

According to the data it can be conclude most of the companies use their ERP

package especially for their financial activities. 71.4% respondents indicated that

SCM (Supply chain module) is in operation in their companies. Table 4.7 shows the

SCM modular distribution of the sample.

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Table 4.7: ERP Modular Distribution-SCM

Frequency Percent

Valid Percent

Cumulative Percent

Valid 0 26 28.6 28.6 28.6

SCM (Supply Chain Management)

65 71.4 71.4 100.0

Total 91 100.0 100.0

Table 4.8: ERP Modules Implemented

Frequency Percent Valid Percent

Cumulative Percent

1-2 Modules 11 12.09 12.09 12.09 3-4 Modules 42 46.15 46.15 58.24 5-6 Modules 34 37.36 37.36 95.60 7-9 Modules 4 4.40 4.40 100.00 Total 91 100.00 100.00

The distribution of the number of ERP modules implemented their organizations is

shown in Table 4.8. 83.5% majority of responses in cooperated with 3 to 6 no of

modules with their ERP system.

Table 4.9: Summary of ERP Modules Implemented

N Valid 91

Missing 0 Mean 4.22 Median 4.00 Mode 4 Std. Deviation 1.611

Table 4.9 Summarizes that the ERP modules implemented with mean value of 4

Components with standard deviation of 1.6 of total responses.

Table 4.10 shows the average people involvement with the ERP system for identified

business activities.

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Table 4.10: Average People Involvement with the ERP System

Name of the ERP

Average people involvement with the ERP Raise

Purchase order (PO) to Good receipt

(GR)

Receive an invoice to payment

completion to the vendor

On a complete

sale

Good receipt (GR)

to issuance

IFS 3 3 4 3 Microsoft Dynamics 3 3 4 2 Oracle 4 4 4 3 Other 6 6 4 6 Sage Accpac 6 3 5 4 SAP 5 5 5 4 Web ERP 2 3 4 4

Results shows SAP , Sage Accpac and other ERP’s records the higher average people

involvement including approval levels compared to ERP’s in the purchase order to

good receipt process. On a complete sale it says the average number of people

involvement with the system are same.SAP, Oracle, and other ERP’s shows higher

number of people involved in receive an invoice to payment completion to the

vendor.

4.3 Statistical Analysis of Parameters

According to the identified high level parameters, descriptive statistics such as mean

and standard deviation of complexities of ERP has been calculated. Table 4.11 in

Appendix-B summarizes statistical parameters for the complexity of ERP based on

product dimension. Rating scale has considered as complexity of ERP varies from

highest complexity to lowest complexity when Likert scale varies from 1 to 5.

Statistical data shows that SAP ERP is most complex and Microsoft Dynamics is

least complexity, according to the feedback received for the product dimension

parameters.

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ERP Complexity based on People factor dimension is shown in Appendix-C, Table

4.12.

Analysis shows SAP records highest complexity in terms of people point of view.

Web based ERP. Oracle ,Sage Accpac, others ERP’s such as Epicor,IFS,Web based

ERP and Microsoft Dynamics shows from highest complexity to lowest complexity.

Mean value and standard deviation of complexity of ERP derived from Project

dimension parameters are shown in Appendix-D in Table 4.13.

It indicates that Oracle ERP is most complicated in Project dimension point of view

and Web based ERP is least complexity.

In Appendix–E, Table 4.14 shows the measurements of complexity measurement

with the company business processess.It shows how ERP alignment with the

business processes according to the feedback given. Analysis says SAP is less

aligned with companies’ business processes in the target group of and Microsoft

Dynamics is more aligned with business Processes. It can be seen that IFS ERP

system also more aligned with the business processors according to the feedbacks.

Based on the results Vendor wise ERP complexity index has been established. It’s

shown in Table.4.15.

Note: If Mean value closer to 0 it denotes higher complexity and if mean value closer

to 5 it denotes lesser complexity.i.e. ERP varies from highest complexity to lowest

complexity when Likert scale varies from 1 to 5.

Table 4.15: Vendor wise ERP Complexity Index

Name of the ERP Mean Std. Deviation ERP Complexity Index

SAP 3.28 0.32 7 Oracle 3.29 0.15 6 Other 3.34 0.30 5 Sage Accpac 3.35 0.31 4 IFS 3.51 0.20 3 Web ERP 3.76 0.23 2 Microsoft Dynamics 4.01 0.23 1 Graphical representation of complexity index calculated from the survey results is

shown in Figure 4.2.

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Figure 4.2: Graphical Representation of Vendor based Complexity Index

ERP complexity index indicates that Microsoft Dynamics is least complexity and

SAP records highest complexity according to the survey feedback. Also It indicates

that Web ERP, IFS, Sage Accpac Oracle varies from lower complexity to higher

complex. It provides a general estimation and an idea in ERP systems selection

decision for medium scaled companies in Sri Lanka.

Table 4.16: Correlation among Independent Variables

ProductD PeopleF ProjectD BusinessP

ProductD Pearson Correlation 1 .574** .553** .385**

Sig. (2-tailed) 0.000 0.000 0.000 N 91 91 91 91

PeopleF Pearson Correlation .574** 1 .587** .516**

Sig. (2-tailed) 0.000 0.000 0.000 N 91 91 91 91

ProjectD Pearson Correlation .553** .587** 1 .360**

Sig. (2-tailed) 0.000 0.000 0.000 N 91 91 91 91

BusinessP Pearson Correlation .385** .516** .360** 1

Sig. (2-tailed) 0.000 0.000 0.000 N 91 91 91 91 **. Correlation is significant at the 0.01 level (2-tailed).

In the complexity analysis it can be seen that there is a significantly positive co-

relation among identified high level independent variables. Table 4.16 provides the

3.28

3.29

3.34

3.35

3.51

3.76

4.01

SAP

Oracle

Other

Sage Accpac

IFS

Web ERP

Microsoft Dynamics

ERP Complexity Index

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correlation coefficients among independent variables. It says that that there is a

positive interrelationship among the Product dimension, People Factor, Project

dimension and Business processes in the complexity analysis.

To improve the clarity of the research in addition to the primary survey it has

been considered some secondary data available. Functionality, ease of use

(Less complexity), total cost of ownership were clearly the top three selection

criteria’s in ERP software decisions. (Abrdeen Group, 2007). According to

the literature survey, total cost of ownership important criteria for ERP

software decisions. Especially this is more important to small and medium

scaled business. Therefore average ERP per user cost has been analyzed as a

secondary data. Information gathered for secondary data sources are mainly

obtained from internet sites that published for Midmarket Enterprise ERP solution

guides and some data obtained from researches done for information systems

application for Medium scaled business in Sri Lanka. First it has been considered per

user cost of ERP for the measurement.

Table 4.17: ERP Average Cost per User

ERP Vendor

Average Software

Cost (Per user)

Source

Infor $5,206 Aberdeen Group, July 2007 Lawson $5,261 Aberdeen Group, July 2007 QAD $5,271 Aberdeen Group, July 2007 Epicor $5,366 Aberdeen Group, July 2007 SAP $6,111 Aberdeen Group, July 2007 Oracle $7,361 Aberdeen Group, July 2007 Dynamics AX $6,150 www.180systems.com/files/ERP-Comparison2008.xls Dynamics NAV $5,350 www.180systems.com/files/ERP-Comparison2008.xls Dynamics GP $3,025 www.180systems.com/files/ERP-Comparison2008.xls Dynamics SL $5,350 www.180systems.com/files/ERP-Comparison2008.xls Epicor Enterprise $3,000 www.180systems.com/files/ERP-Comparison2008.xls

IFS Applications $2,500 www.180systems.com/files/ERP-Comparison2008.xls

Sage Accpac 500 ERP $2,300 www.180systems.com/files/ERP-Comparison2008.xls

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Table 4.17 shows the ERP per user cost and its graphical representation shows in Figure 4.3.

Figure 4.3: ERP Average Cost per User

According to the data Oracle ERP records highest per user cost. Further researcher has taken in to consideration some Sri Lankan experiences. According to the research done by Munasinghe and Jayawardana - The Success of Information Systems implemented in medium scaled industries-Sri Lankan experience also considered for the analysis as a secondary data.

Table 4.18: Over all Success (%) of MIS in SME in Sri Lanka

Functional Area Over all Success (%) of MIS in SME in Sri Lanka

Production Planning and Control 14 Inventory Control 32 Sales & Marketing 27 Financial Accounting 75 Cost and Management Accounting 38 Payroll Preparation 98 Strategic Planning 7

Source: (Munasinghe & Jayawardana, 2001)

$0 $2,000 $4,000 $6,000 $8,000

Infor Lawson

QADEpicor

SAPOracle

Dymanics AXDynamics NAV

Dynamics GPDynamics SL

Epicor EnterpriseIFS Applications

Sage Accpac 500 ERP

Average software cost per user

Average software cost per user

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Figure 4.4: Success Rate of MIS in SME's in Sri Lanka

Source: (Munasinghe & Jayawardana, 2001)

In Sri Lankan context, in SME’s found there is sound adoption in Payroll and financial accounting key areas as indicated above Figure 4.4 in medium sized business .Though strategic planning, production planning and control are important key areas of any business it can be seen that information systems adoption in those areas are unsatisfactory.

4.4 Chapter Summary

This chapter covered the data presentation and analysis of the research. First it

analyzed the characteristics of the respondents of the research. Next sub section it

summarized the statistical analysis of parameters. In the statistical analysis of

parameters first it analyzed the primary data gathered through questionnaire. Finally

this chapter analyzed some secondary data gathered from trusted internet sources and

from previous researches carried out for information systems application in Sri

Lanka.

0 50 100 150

Production Planning and Control

Inventory Control

Sales & Marketing

Finacial Accounting

Cost and Management Accounting

Payroll Preperation

Strategic Planning

Success (%) of MIS SME's in Sri Lanka