Chapter 4

CHAPTER 4.0

RESULTS AND DISCUSSIONS

4.1. Defect Causal Analysis

The endeavor is to expose and analyze the key areas of the implementation process

and procedure for various kinds of problems and other human factors which

contributes to the end result of an unsuccessful implementation.

Hence a Defect Causal Analysis was carried out which highlighted the root causes

which had a major contribution in the problems that both the client as well as the

vendor faced during the course of the ERP implementation procedure. Defects are

analyzed to determine the cause of an error .The major root causes were classified

into four sub-headings namely, the ERP Package itself, its application, the top

management and finally the data collection. The main effect was the challenge faced

in the implementation of the ERP system.

The quality issues were segregated on the basis of the module in which they

originated and the frequency with which they occurred in these modules (Refer

Annexure 1). The complete issue list was then considered for further analysis by

means of a Pareto Chart using tools. The major benefit of using this type of an

analysis was to get the client to concentrate on just the vital few problems from the

complete issue list that was recorded. This enabled a deep and thorough analysis of

problems encountered in implementation so that a concentrated study might be

carried out.

Table 4.1: Number of issues in each module

Bin No of Error Cumulative %

SD 53 40.45802

FI-CO 35 67.17557

MM 25 86.25954

HR 10 93.89313

PP 4 96.94656

BASIS 4 100

Pricing, 22

Improper definitions ,

18

Account assignment,

11

Fig. 4.1: Pareto chart- Implementation issues in each module

From the analysis by means of the Pareto Chart, it was found that the functional

modules of Sales & Distribution and Financial-Control posed majority of the

problems. Hence, these problems needed to be addressed through a more precise tool

which will bring out the exact areas of shortcomings in the whole system. This was

achieved through a Cause & Effect Diagram assessing the main effect that was the

major bottlenecks at the company.

I. Sales and Distribution Module

Table 4.2: Sales and Distribution frequency table

Sl. No Causes of problems Frequency

1 Pricing 22

2 Improper definitions 18

3 Account assignment 11

Fig. 4.2: Pie-chart for Sales and Distribution Module

53

35 25

10 4 4

0

50

100

0

20

40

SD FI-CO MM HR PP BASISEr

ror

Fre

qu

en

cy

Modules

Pareto Analysis

Frequency Cumulative %

II. Why-why analysis for the Major bottle neck

Major problem areas observed by Pareto Chart are Sales and Distribution Module

contributing 41% and the Financial Accounting and controlling module contributes

27% summing together becomes 68% of the total problems facing in ERP transaction.

1. Sales and Distribution Module - In this module we observed 53 defects out of

131, defects were such as Error in Delivery Challan, No accounting document

creating, Credit limit verification and so on, these defects causing errors in

functioning of ERP systems. The defects were present in the module due to below

identified reasons

Pricing - It was observed that there was no standardized pricing procedure

which resulted in incorrect pricing.

Improper definition - It was noticed that there was incomplete sales areas

definition in turn yielded in loss of controls.

Account Assignment - It was observed in effective account assignment due to

improper accounting system which has root to wrong financial posting.

II. Financial Accounting and controlling module

Table 4.3: Financial Accounting & Control frequency table

Sl. No Causes of problems Frequency

1 Masters 12

2 Tax schema 10

3 Asset management 8

4 Improper definitions 5

Masters 34%

Tax schema 29%

Asset management

23%

Improper definitions

14%

Fig. 4.3: Pie-chart for Financial Accounting and controlling Module

Why-why analysis for the Major bottle neck

2. Financial Accounting and controlling module - In this module we observed 35

defects out of 131, defects were such as Tax payment errors, sales promotion

exception posting, changing reconciliation account and etc, these defects impacted

functioning of Financial Accounting and controlling module . The defects are

confronted due to following reasons.

Masters - It was observed that there was a mismatch between balance sheet

and trial balance, accounts codes were not matching resulted in improper

maintenance of master data base.

Tax schema - In the Taxing system there is lot of variations due to taxing

policies followed by different states as well as countries such as variations in

Value Added tax (VAT), sales tax and other commercial taxes resulted in

wrong tax calculation and wrong ledger posting.

Asset management - It was observed that there was improper asset register

and depreciation calculation resulted in incomplete asset classification and

finally resulted in improper asset management.

Improper definition - It also noticed that there was no standardized financial

control and procedure followed.

Table 4.4: Why-why analysis for SD & Fi-CO

Sl

No.

Problem Cause Root cause Solution

1 Major

bottle neck

SD 1. Pricing

2. Improper

definition

3. Account

Assignment

Standardize pricing procedure.

Redefine sales areas.

Formulate standard accounting

system.

FI-CO 1. Masters

2. Tax schema

3. Asset

management

4. Improper

definition

Review software architecture.

Regularize ledger posting.

Standardize asset classification.

Standardize Financial controls

and procedure.

Fig 4.4: Ishikawa diagram to identify the bottleneck

Finance and

control

Sales and Distribution

P1-Pricing

Correct pricing

procedure

Wrong pricing

Wrong sales area

Definitions

Loss of controls

P3-Account Assignment

Improper account

Wrong FI Postings

P1-Masters

Account codes Wrong Balance Sheet

Trial Balance

P3-Asset management

Incomplete Asset

Classification

Improper asset

Register and Depreciation

calculation

P2-Tax Schema

P4-Improper definition

Wrong tax calculation &

FI Postings

P2-Improper definition

Major

bottlenecks

4.2. Grounded Theory: Factors identified.

Grounded Theory “A theory is inductively derived from the study of the phenomenon

it represents. That is, it is discovered, developed, and provisionally verified through

systematic data collection, analysis, and theory stand in reciprocal relationship with

each other. One does not begin with a theory, and then prove it. Rather, one begins

with an area of study and what is relevant to that area is allowed to emerge”. GT

differs from other qualitative approaches. Traditional qualitative approaches collect

the data first before commencing the analysis and long after they have left the

research site. In contrast, grounded theorists use their emerging theoretical categories

to shape the data collection while doing the fieldwork. The data analysis followed

three types of coding; open coding, (b) axial coding, and (c) selective coding

(a) Open coding : From the literature, readings on theory, research, and supporting

evidence the theoretical sensitivity can be broadly classified into four categories

namely organizational critical success factor, Tactical critical success factor,

Technological critical success factor and the Strategic critical success factor. The

relationship between the category, Properties and Dimensions are identified.

(b) Axial coding: here we established the relationship between the categories obtained

during open coding.

(c) Selective coding: here the central category and the linking category are decided, in

our study, the central category will be Successful ERP Implementation, other

categories that were considered to influence the central category is integrated as the

intervening factors. The result of the tasks is the theoretical scheme, which is

subjected to further analysis

Fig. 4.5: Factors affecting ERP implementation

4.3. Analytical Hierarchy Process (AHP): Prioritized the factors

4.3.1. Structure of AHP model for ranking and comparison

The reason for choosing this model is the fact it consists of a great number of criteria,

not all of which of the same importance. In addition to this, a high quality computer

system/software Super Decision has been developed. It is used in assisting the

development of the model and enables a detailed sensitivity analysis of the final

ranking list on the change of the values which are assessed subjectively.

In order to use this model for ranking, we need to determine the weights of the main

criteria and sub-criteria, and then for each.Criteria at the bottom level of the hierarchy

structure to define the intensities for the evaluation of the relevance. The weights of

criteria and sub-criteria are calculated by the help of Super Decision software on the

basis of the pair wise comparison of relative criteria and sub-criteria importance. For

quantity criteria, the intensities are defined on the basis of the five-level scale of

intensities (excellent, very good, good, satisfactory, weak), which have been derived

on the basis of the range in which their values have fluctuated.

ERP

Implementation

Consequences

Organizational

CSFs

Tactical

CSFs

Strategic

CSFs

Consequences

Never run

Parallel

sysytem

Adequate and

Correct Data

Stakeholders

Identification

Training and

Testing Conference Room

Pilot

Customization

Clarity In mngt

objective

Employee Retention

Technologic

al CSFs

Step 1 - Determination of the relative importance of the attributes

Fig. 4.6: Screen shot: Determining important attributes

Step 2 - Determination of the relative importance of each of the alternatives with

respect to each attribute. Determine the overall priority weight of each of these

alternatives.

Fig. 4.7: Screen shot: Relative importance of attributes

Step 3 - The next step is to evaluate all the choices on each objective.

Fig. 4.8: Screen shot: Evaluate attribute choices

Step 4 - The priority value is now calculated with the help of relative scores tables

and the weights of the objectives.

Fig. 4.9: Screen shot: Priorities attributes

The following are the response obtained from The Questionnaires were asked to

Consultants and user which gave both quantitative issues encountered in

implementation of the ERP system the response is follows.

Table 4.5: Response prioritization matrix

Factors Response

1 2 3 4 5 6 7 8 9 10

Adequate and

Correct Data 0.292 0.301 0.290 0.302 0.294 0.311 0.296 0.313 0.326 0.323

Training and

Testing 0.136 0.146 0.139 0.140 0.140 0.143 0.134 0.139 0.130 0.127

Never run

Parallel system 0.160 0.150 0.160 0.158 0.156 0.151 0.157 0.153 0.154 0.157

Conference

Room Pilot 0.087 0.080 0.082 0.081 0.085 0.083 0.084 0.087 0.086 0.085

Employee

Retention 0.089 0.083 0.086 0.084 0.086 0.081 0.084 0.085 0.087 0.085

Customosation 0.084 0.084 0.084 0.084 0.082 0.081 0.086 0.083 0.083 0.082

Clearity In

management

objective

0.107 0.112 0.115 0.106 0.112 0.103 0.114 0.095 0.091 0.138

Stakeholders

Identification 0.044 0.044 0.045 0.044 0.044 0.047 0.045 0.047 0.044 0.005

4.4. Hypothesis testing: Accepting or rejecting the null hypothesis.

Since the sample size is small and the population variance is unknown‘t’ test is

performed on the hypothesis.

0.28 0.29 0.30 0.31 0.32 0.33

ADEQUATEAND

0

1

2

3

4

Co

un

tI. Null: there is no significant difference between the sample mean and the population

mean.

II. Alternate: there is significant difference between the sample mean and the

population mean.

For Adequate correct data to the consultant factor the mean computed to be x bar =

0.304 The Null Hypothesis Ho: µ=0.304. And alternate hypothesis Ha: µo ≠ 0.304.

The test statistics using the data for the first value tComputed = x -0.340/(SD/SQRT(n))

Where x is the mean SD is the standard deviation.

n is the sample size.

Since there are 10 data points sample size is 10.

Degree of Freedom (DOF) =n-1=10-1=9.

Level of significance assumed is 5%.

Sine it is two tailed test we use α/2=0.025.

tCalculated =0.137

The critical value to compare this value against is ttabulated = t10-1,0.025 =2.26, since

tcalculated is within the interval (-2.26,2.26).the hypothesis cannot be rejected. The

corresponding p-value p(xbar>0.137)= 0.894 for us to reject the hypotheis the p-value

should be less than 0.05. Similarly the 95% CI t vaule p value are calculated using

SYSSTAT software and the results are as follows.

1

Likewise we have tested the hypothesis for other factors also and the resultsa are

tabulated as follows.

One-sample t test of ADEQUATEAND with 10 cases;

Ho: Mean = 0.304

Mean = 0.305 95.00%

CI = 0.295 to 0.314

SD = 0.013

t = 0.137

df = 9 Prob = 0.894

Fig. 4.10: Box plot: Adequate and correct data to consultant

One-sample t test of TRAININGAND with 10 cases;

Ho: Mean = 0.137

Mean = 0.137 95.00%

CI = 0.133 to 0.142

SD = 0.006

t = 0.141

df = 9 Prob = 0.891

Fig. 4.11: Box plot: Training

One-sample t test of NEVERRUNPA with 10 cases;

Ho: Mean = 0.155

Mean = 0.156 95.00%

CI = 0.153 to 0.158

SD = 0.004

t = 0.509

df = 9 Prob = 0.623

Fig. 4.12: Box plot: Parallel system

One-sample t test of CRP with 10 cases;

Ho: Mean = 0.084

Mean = 0.084 95.00%

CI = 0.082 to 0.086

SD = 0.002

t = -0.011

df = 9 Prob = 0.991

Fig. 4.13: Box plot: Conference Room Pilot

0.150 0.152 0.154 0.156 0.158 0.160 0.162

NEVERRUNPA

0

1

2

3

4

Co

un

t

0.12 0.13 0.14 0.15

TRAININGAND

0

1

2

3

4

5

6C

ou

nt

0.079

0.080

0.081

0.082

0.083

0.084

0.085

0.086

0.087

0.088

CRP

0

1

2

3

Co

un

t

0.081

0.082

0.083

0.084

0.085

0.086

0.087

0.088

0.089

EMPLOYEERET

0

1

2

3

4

Co

un

t

0.081 0.082 0.083 0.084 0.085 0.086

CUSTOMOSATIO

0

1

2

3

4

Co

un

t

One sample t test of EMPLOYEERET with 10 cases;

Ho: Mean = 0.085

Mean = 0.085 95.00%

CI = 0.084 to 0.086

SD = 0.002

t = -0.054

df = 9 Prob = 0.958

Fig. 4.14: Box plot: Employee retention

One-sample t test of CUSTOMOSATIO with 10

cases; Ho: Mean = 0.083

Mean = 0.083 95.00%

CI = 0.082 to 0.084

SD = 0.001

t = 0.238

df = 9 Prob = 0.817

Fig. 4.15: Box plot: Customisation

One-sample t test of CLEARITYIN with 10

cases; Ho: Mean = 0.109

Mean = 0.109 95.00%

CI = 0.100 to 0.119

SD = 0.013

t = 0.118

df = 9 Prob = 0.908

Fig. 4.16: Box plot: Clarity

0.09 0.10 0.11 0.12 0.13 0.14

CLEARITYIN

0

1

2

3

4

5

6

Co

un

t

0.00 0.01 0.02 0.03 0.04 0.05

STAKEHOLDERS

0

2

4

6

8

10

12

Co

un

t

One-sample t test of STAKEHOLDERS with

10 cases; Ho: Mean = 0.046

Mean = 0.041 95.00%

CI = 0.032 to 0.050

SD = 0.013

t = 0.019

df = 9 Prob = 0.985

Fig. 4.17: Box plot: Stake holder

Table 4.6: Hypothesis Test summary

Sl.

No

Factors Null

Hypothesis

Alternative

Hypothesis

95.00%

CI

t Prob Result Null

Hypothesis

1. Adequate and

Correct Data to

consultant

μ0=0.304

μa≠0.304

0.295 to

0.314

0.137 0.894 Donot

Rejected.

2. Training and

Testing

μ0=0.137 μa≠0.137 0.133 to

0.142

0.141 0.891 Donot

Rejected.

3. Never run

Parallel

sysytem

μ0=0.155 μ0≠0.155 0.153 to

0.158

0.509 0.623 Donot

Rejected.

4. Conference

Room Pilot

μ0=0.084 μ0≠0.084 0.082 to

0.086

-.011 0.991 Donot

Rejected.

5. Employee

Retention

μ0=0.085 μ0≠0.085 0.084 to

0.086

-0.05 0.958 Donot

Rejected.

6. Customosation μ0=0.083 μ0≠0.083 0.082 to

0.084

0.238 0.817 Null

Hypothesis

Donot

Rejected .

7. Clearity In

mngt objective

μ0=0.109 μ0≠0.109 0.100 to

0.119

0.118 0.908 Donot

Rejected .

8. stakeholders

Identification

μ0=0.046 μ0≠0.046 0.032 to

0.050

0.019 0.985 Donot

Rejected .

Table 4.7: Rank allocation for influencing factors

Factors Priority

value Percentage %

Priority

/Rank

Adequate and Correct Data to consultant 0.304 30.4 1

Training and Testing 0.137 13.7 3

Never run Parallel system 0.155 15.5 2

Conference Room Pilot 0.084 8.4 6

Employee Retention 0.085 8.5 5

Customosation 0.083 8.3 7

Clearity In mngt objective 0.109 10.9 4

stakeholders Identification 0.046 4.6 8

Fig. 4.18: Force Field diagram for successful ERP implementation

4.5 Force Field Analysis: Explored restraining forces.

From the force field analysis it was found that the role of consultants and the

customer dominates, 38.7% and around 30% respectively.

These major restraining force was further considered for analysis to improve ERP

implementation successfully.

4.6. Gap with respect to CMMI.

The final gaps are sorted into categories and listed as shown below:

Presen

t State

Desired

State

Consultant – 30.4 %

Training & Testing -13.7%

Parallel System – 15.5 %

Conference Room Pilot -8.4

%

Employee Attrition – 8.5 %

Customization – 8.3 %

Organization Culture – 10.9 %

Employees Exclusiveness -4.6 %

Customer Demand

Order acceptance

Increase Productivity

Trust in Team leader

Driving Forces

Positive forces for change

Restraining Forces

Obstacles for change

Fig. 4.19: Integrated Project Management

Fig. 4.20: Measurement and Analysis

Fig. 4.21: Organizational process definition

SG 1 SG 2 SG 3

CMMi 6 3 5

NGDM 2 2 2

0

1

2

3

4

5

6

7

Spe

cifi

c P

ract

ice

by

Go

als

SG1 SG2 SG3

CMMI 3 3 2

NDGM 2.5 3 2.5

0

0.5

1

1.5

2

2.5

3

3.5

Spe

cifi

c P

ract

ice

by

Go

als

SG 1 SG 2 SG 3

CMMi 6 3 5

NGDM 2 2 2

0

1

2

3

4

5

6

7

Spe

cifi

cPra

ctic

e b

y G

oal

s

Fig. 4.22: Organizational process focus

Fig. 4.23: Organizational Training

Fig. 4.24: Product Integration

SG 1 SG 2 SG 3

CMMi 6 3 5

NGDM 2 2 2

0

1

2

3

4

5

6

7

Spe

cifi

c P

ract

ice

by

Go

al

SG1 SG2

CMMI 4 3

NGDM 3 3

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Spe

cifi

c P

ract

ice

by

Go

al

SG1 SG2 SG3

CMMI 3 2 4

NGDM 2 2 3

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Sp

eci

fic

Pra

ctic

e b

y G

oal

Fig. 4.25: Project Monitoring and control

Fig. 4.26: Project planning

Fig. 4.27: Process and product quality assurance

SG1 SG2

CMMI 7 3

NGDM 6 2

0

1

2

3

4

5

6

7

8

Spe

cifi

c P

ract

ice

by

Go

als

SG1 SG2 SG3

CMMI 4 7 3

NGDM 4 6 3

0

1

2

3

4

5

6

7

8

Spe

cifi

c P

ract

ce b

y G

oal

s

SP1 SP2

CMMI 2 2

NGDM 2 1

0

0.5

1

1.5

2

2.5

Spe

cifi

c P

ract

ice

by

Go

als

Fig. 4.28: Requirement development

Fig. 4.29: Risk Management

Fig. 4.30: Supplier Agreement Management

SP1 SP2 SP3

CMMI 2 3 5

NGDM 2 2 6

0

1

2

3

4

5

6

7

Sp

ecif

ic P

ract

ice

by

G

oa

ls

SG1 SG2 SG3

CMMI 3 2 2

NGDM 1 1 1

0

0.5

1

1.5

2

2.5

3

3.5

Spe

cifi

c P

ract

ice

by

Go

als

SP1.1 SP1.2 SP1.3 SP2.1 SP2.2 SP3.1 SP3.2

CMMI 33 33 33 50 50 50 50

NGDM 5 8 5 5 5 5 5

0

10

20

30

40

50

60

Spe

cifi

c P

ract

ice

by

Go

als

Fig. 4.31: Technical solution

Fig. 4.32: Validation

Fig. 4.33: Verification

CMMI0

1

2

3

4

SG1SG2

SG3

Spe

cifi

c p

ract

ice

by

Go

als

CMMI

NGDM

0

1

2

3

4

SG1SG2

SG3

Spe

cifi

c p

ract

ice

by

Go

als

SG1 SG2 SG3

CMMI 2 4 2

NGDM 2 3 2

SG1 SG2 SG3

CMMI 2 4 2

NGDM 2 3 2

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Spe

cifi

c p

ract

ice

by

Go

als

Table 4.8: Review of process area gap analysis

Sl. No Process areas Specific goals TOTAL No. of gaps

1. REQM 1.5 5 1

2. PP 1.4,2.7,3.3 14 5

3. PMC 1.7,2.3 10 2

4. CM 1.3,2.2,3.2 7 4

5. PPQA 1.2,2.2 4 1

6. MA 1.4,2.4 8 2

7. RD 1.2,2.3,3.5 10 2

8. TS/SAM 1.3,2.5 8 0

9. PI 1.3,2.2,3.3,3.4 12 3

10. VAL 1.3,2.2 5 2

11. VER 1.3,2.3,3.2 8 3

12. IPM 1,6,2.3,3.5 14 5

13. RSKM 1.3,2.2,3.2 7 5

14. OPF 1.3,2.2,3.4 9 0

15. OPD 1.5,2.3 8 0

16. OT 1.4,2.3 7 0

17. DAR 1.6 6 5

TOTAL 142 40

Gaps analysis based on the Total Number of gaps in the various process areas. The

weightage factor is used to correct disproportional sample sizes and adjust the

collected data to represent the population from which the sample was drawn the

average factor is the rounded off to

Table 4.9: Weightage factor allocation for process area

Sl.No Process Areas No. of gaps Weight age

Factor

Average gaps in

each areas

1. REQM 1 0.25 0

2. PP 5 0.25 1

3. PMC 2 0.03 0.2

4. CM 4 0.06 0.12

5. PPQA 1 0.03 0.01

6. MA 2 0.03 0.04

7. RD 2 0 0.06

8. TS/SAM 0 0 0

9. PI 3 0.15 0.03

10. VAL 2 0.02 0.06

11. VER 3 0.02 0.06

12. IPM 5 0.15 1

13. RSKM 5 0.01 0.75

14. OPF 0 0 0

15. OPD 0 0 0

16. OT 0 0 0

17. DAR 5 0.25 1

40

To determine the percentage of gap in each processing areas:

Table 4.10: Gap analysis in percentage for process areas

Sl.No Processs Areas No. of gaps Percentage

1 Risk Management-RSKM 5 12.5

2 Project Planning -PP 5 12.5

3 Integrated Project Management -IPM 5 12.5

4 Decision Analysis and Resolution-DAR 5 12.5

5 Configuration Management-CM 4 10

6 Verification-VER 3 7.5

7 Product Integration-PI 3 7.5

8 Validation-VAL 2 5

9 Measurement and Analysis -MA 2 5

10 Requirements Development-RD 2 5

11 Project Monitoring and Control -PMC 2 5

12 Requirements Management-REQM 1 2.5

13 Process and Product Quality Assurance -PPAQ 1 2.5

Fig. 4.34: Process area gap in percentage

Risk Management-RSKM

1%

Project Planning -PP 3%

Integrated Project

Management -IPM 4%

Decision Analysis and Resolution-DAR

6%

Configuration Management-CM

7%

Verification-VER 8%

Product Integration-PI 9% Validation-

VAL 9%

Measurement and Analysis -MA

10%

Requirements Development-RD

10%

Project Monitoring and Control -PMC

11%

Requirements Management-REQM

11%

Process and Product Quality Assurance -

PPAQ 11%

Table 4.11: Pareto analysis table

Sl.

No

Process Area of CMMI No. of

gaps

Percentage Cumulative

%

1 Risk Management-RSKM 5 12.5 12.5

2 Project Planning -PP 5 12.5 25

3 Integrated Project Management -IPM 5 12.5 37.5

4 Decision Analysis and Resolution-DAR 5 12.5 50

5 Configuration Management-CM 4 10 60

6 Verification-VER 3 7.5 67.5

7 Product Integration-PI 3 7.5 75

8 Validation-VAL 2 5 80

9 Measurement and Analysis -MA 2 5 85

10 Requirements Development-RD 2 5 90

11 Project Monitoring and Control -PMC 2 5 95

12 Requirements Management-REQM 1 2.5 97.5

13 Process and Product Quality Assurance -

PPAQ

1 2.5 100

Fig. 4.35: Pareto chart for identifying critical process area

Based on the weighted, Percentage of Gap and the pareto Analysis the major gap

found in the Risk Management, Project Planning ,Integrated Project Management and

Decision Analysis and Resolution and the corrective action is taken up.

0

20

40

60

80

100

120

Percentage

CUMULATIVE %

4.7. Closer of the gaps: Bridging the gap between NDGM and CMMI.

The gaps in the process areas of NGDM are identified and the major gaps found in the

risk management, project planning, integrated project management decision analysis

and resolution process areas

4.7.1. Risk Management-RSKM

Risk analysis was not done,Risk is what happens unexpectedly and affects the flow of

operations while they are going on. So, to minimize the effects of risk, they are pre

determined or expected and safety measures will be taken.

In this project risk analysis was not done. There was one risk of hierarchy changing

many times. The hierarchical structure of DM changed for 15 times. As hierarchy has

very intense effect on DM, it could had been analyzed before only and safety

measures like specifying the customer the exact number of hierarchical changes

possible and could have told that any further changes would be treated as customer

request and would have got compensation. There were hierarchical changes in

prototype 1 and even in prototype 2 also.

The Spiral SDLC, which NGDM advocates emphasizes on risk analysis during each

spiral. The project team has started to document the risks at each spiral/milestone and

having a formal risk response plan associated with it. By repeatedly following a

rigorous risk analysis the preparedness to solve problems will be considerably

increased.

Prototype 2 typically consists of following activities:

Get feedback from prototype 1

Modify Data model design based on feedback

Integration design

Design of Non-out of the box workflows

Design Job Scheduler

Design test specifications for production data set

Data model creation as per design

Integration development

Configure, build and test various functionalities in the solution

Development of Non-out of the box workflows

Develop job scheduler

Prepare and Build test cases with production data set

Periodic Build and Test cycles with production data set

Reviews with customer

The risk template filled for February is as follows

Table 4.12: Risk template

Project Code :

Sl.

No.

Category Risk Consequences Date

Identified

Impact Impact of

Risk Value

Risk

Response

Type

1 Customer Risks Resistance to

change/acceptance of new

ways of working

Company product will not be

completely installed at customers

place. So, the efforts of developing

the product would be waste

25-Feb-2*** Medium Low Mitigation

2 Customer Risks Buy-in of ST organization

for the Roll-Out – project

is focused on Phase 1

scope only, including

makeup of Project Board

Only few advantages of the product

are gained. Product is not fully

utilized at the customer place and

almost same consequences of the

previous risk.

25-Feb-2*** Low Medium Mitigation

3 Resource Risks Availability of project

resources – ST resources

are not assigned full time

on the project and have

other project/operational

roles

Consultants who are multiplexed

would find lesser time in any one of

projects due to over time in one of

the projects. So he may not be

available for work. And this will

cause delay in current project

because there may be some

operations which would only

proceed after his work.

27-Feb-2*** Medium Medium Mitigation

4 Implementation

Risks

Integration with

downstream systems –

changes may be required

to MFS/DMT, E2

scheduling,

BM/DRP/SGA06

Integration time will be delayed,

overall project will not be completed

in time.

28-Feb-2*** Medium Low Mitigation

Statement Of Work(SOW) which is the basic thing that is very necessary for every

project and this statement specifies about the work to be done in the project. The

project manager after properly analyzing the work to be done will prepare the

statement and there will be an official sign off by the customer which is the indication

of proceeding with work. Sometimes there can be even negotiations after sign off

also.

Because of not doing risk analysis in SOW it can be at least stated that there could be

probability of occurrence of risk and time could had been taken for that.

Table 4.13: Statement of work

Response Priority Risk

Score

Risk

Owner

Have a formal training plan and train the customer

about the product and making customers realize the

advantages and ease of using the new product.

Medium 0.2 Project

manager

Have an adequate training and workshop sessions.

Training should make sure that everyone in the

company will be ready to accept the product.

Training should be done in more sessions and this

will reduce the risk.

Medium 0.3 Project

manager

Consultants working for the project should be out of

other projects and if the employee is multiplexed his

other job should not affect the current project.

Medium 0.6 Project

manager

We should ask customer to explain their system so

that we can plan according to it.

Medium 0.2 Project

manager

In the same way the risk template was filled March and April also. By taking action

according to response, the risks were minimized. There was one more risk added in

the March template which is the drastic changes in the hierarchy. Its priority was high

and even it was resolved to medium. One of the above four risks which is the risk of

available resources couldn’t be resolved till May; its priority was left out at medium

only.

4.7.2. Project Planning –PP

From the estimation you can just think about how many days each activity would

take, where as in base lining we will finally fix the number of days the activity should

take and base lining basically means setting up the dead line of those activities by

when they should be finished.

The schedule variance metrics is got from the MS project:

The screen shot MS project is as shown below, Project focused on processes rather

than functionality:,The focus of project members was mainly on how the forecasting

processes are to be handled rather than going into the technical part of building the

functionalities for the project as well. If there was focus on functionality and the

technical aspects the project could have got many reusable components in the DM

when the hierarchies are changed and this would have saved the precious time of the

team. This would have reduced some burden on the employees. DM projects are

Integration intensive and hence postponing the integrations to a later stage affected it

severely.

Fig. 4.36: Screen shot: Project planning

The the above Project plan it is found that the schedule variance is 2 weeks delay. For

some security reason the company didn’t let us put the network diagram.

Effort variane = -9%

Schedule variance = 2 weeks delay

when you look at schedule variance it is 2 weeks delay which is a very bad negative

effect and which adds for cost of the project for the company.

If the team had followed template and had done risk analysis at the right time, they

could have saved lot of time and even if there was any possibilities of delay, they

could have been shown it to the customer.

I. Time sheets data and project metrics: Use Time sheets data and Project plan in

MS project for making the project metrics.

By the timesheets data we will know in detail about each person working in the

project, about the no. of hours he has worked in the project and the time expend type,

that is, what kind of activity he or she was involved while doing the project. By this

we will calculate the total full time efforts (FTEs) put by the team members in the

project. Full time is 8 hours per day.

For 121 days in our project, 121*8= 1 full time effort for 121 days.

121 days are from the start date 26-Nov-08 to date of review 15-May-08.

Effort variance is calculated by formula:

Effort variance = (Estimated effort-actual effort)/ Estimated effort*100

The Effort variance metrics is as shown below:

Table 4.14: Effort variance matrix

Sl

No.

Persons Days on project Ratio

against total

days (a)

Hours as

per time

sheets

1 PB 65 0.53719 466

2 VP 121 1 848

3 BK 95 0.78512 466

3 AJ 116 0.95868 796

4 EG 77 0.63636 675

5 RL 116 0.95868 881

6 RP 52 0.42975 392

7 NG 111 0.91736 818

8 SP 111 0.91736 874

9 CT 110 0.90909 464

10 Rly 5.5 0.04545 44

11 RJ 98 0.80992 796

12 Others 41.25 0.34091 330

Total 7850

FTEs= ∑ (a) 9.24587 Misc hrs 253

Grand total 8103

Estimated effort for 121 days work

with 9.24FTEs

8944 Actual effort on

project

8103

Effort variance = (Estimated effort-

actual effort)/

Estimated effort*100

-9%

It is good to have negative effort variance which is positive indication that the team

has put less effort.

4.7.3. Integrated Project Management -IPM

Activity tracker: This is a tool which is actually used to know the flow of activities in

the project. This can also be used to check whether the project is going according to

schedule or not. This is a tool with single window for all to view. This means that

everyone who accesses it has equal privileges to view and access. Everyone in the

project has to should describe their modification or creation of new file in the product

and upload it into activity tracker. It even has automated mailing system which sends

mail to everyone in the project about any file upload

Screen shots of activity tracker:

Fig. 4.37: Screen shot: Integrated project management

Fig. 4.38: Screen shot: Creating new project plan

Fig. 4.39: Screen shot: Modifying the project plan

4.7.4. Decision Analysis and Resolution-DAR

There was cost of quality metrics done,The cost of qulity is what you spend on for

prevention of quality losses, assuring good quality and even for internal and external

failures.The cost of quality metrics is as shown below:

Table 4.15: Quality cost matrix

Sl

No.

Persons No. of

hours

Cost Type of

costs

1 PM + Project Lead for PM

activities

1056 26400 Prevention

2 QA personnel 952 23800 Appraisal

3 Testing personnel 24 600 Failure

4 Project member 36 900 Failure

Total Cost 51700

In the above metrics, prevention cost is what is spent on prevention of failures in the

planning time, the costs involved in planning the activities according to standards,

planning for following coding guidelines in software development, planning to use

good tools like version control tools. Appraisal cost is what is spent for quality

assurance, making audits reviews etc. There are two failures. The first one is internal

failure and the second one is external failure. Internal failures are the losses which

you get when you are developing your product and external failure are the losses you

get when your product is released and defects are found by customer side, so project

member has to spend his time to correct those.

If a company invests more on prevention and appraisal costs, there will be minimal

failure costs and if it doesn’t spend on these things properly, there will be more failure

costs and it will definitely cost more than what you spend for prevention and

appraisal.

The QMG of company has put the DAR guidelines in the company QMS site and

made employees easy to think about how to follow DAR and it is taking step to

educate PMs about it and to do DAR.

The screen shot shown below is the website of company that has DAR guidelines:

Fig 4.40: Screen shot: Standards and guidelines

After implementing CMMI methodology the benefits are tracked. the following are the results

CMMI methodology reduced the effort over run from 48 to 50 %before CMMI

implementation to 38 to 42 % after CMMI implementation.

Over 90% of the deliverables now made within stipulated time.

Around 10 to 12 %results in saving in the cost poor quality

4.8. Six Sigma: Improved Process sigma.

Measure phase is to examine the current state of the process, it precisely pinpoints the

area causing problems to use it as a basis of the problem-solving. Fault or defect of

the project, unit and opportunity must be clearly and precisely defined and all possible

and potential causes for such problems must be identified in this step. Subsequently

such problems are analyzed statistically, direction of the project and precise standard

of the projects subjected to the analysis must be determined.

There are mainly two jobs in measure phase. The first one is to assist define phase for

Improvement in the project selection. Before the improvement project is defined,

several Characteristics or processes shall be measured. Most of Six Sigma companies

apply the mental model (i.e. Y is a function of X). Y is selected from variation results

through Six Sigma measurement system, while X factors which influence Y need to

be identified for each Ys. The relationship is demonstrated.

The other job of the measure phase is to collect the data for the selected Ys and Xs.

Before the selection decision is made, related data such as types, sizes, measurement

intervals, and how to record the data are needed. Be different with the measurement of

process performance, measurement of Ys and Xs are more detailed and project

related.

The main activities in this phase are: identify what to measure, evaluate the

measurement system, data collection, sources of variation, and sigma level

calculation. In first activity, the current inputs, the process, and the outputs are

documented. This activity helps to measure the problem in quantitative terms.

The second activity is to evaluate the measurement system. The measurement system

is evaluated by looking at the following issues. The plan has to show works that have

to be done, added or removed tasks which are handled as the project progress, and

changes in project requirements.

The next activity is data collection in which the required data is collected. Once we

have the data, we can display it graphically. The graphical display of data helps to

find the sources of variation in the process.

The last activity of measure phase is the calculation of the sigma level.

In this phase main task is to measure the chosen process. Firstly we should make sure

what needs to be measured. Then answer the question – is our measurement system

good enough? If not, then it needs to be improved first. After that, the measurement is

started. The aim of measurement is to identify the sources of variations. At last, the

sigma level of chosen process is calculated.

The categories for the assessment criteria are Graphical User Interface, Data

Exchange, Data Processing, Data Entry, Data Interpretation, Support by Supplier,

Integration by other Methods, Utilisation, Individual Adaptability, Support For

Introduction of Software Update, Notification, Database.

The measures taken would depend on the problem at hand, and aimed at providing

indicators of how well a process delivered according to the CTQs.

Since in the define stage the problem statement was clearly defined in the measure

phase the first step is to gather data therefore, we look up the purpose of data

collection through which we can gain transparency between the customer and the ERP

software. In this stage we have to go through the software in detail and all the main

portions of the ERP software so as to reach to the conclusion of what type of data is to

be collected in order to find the purpose. To achieve the above step we take up a study

in which we ask a series of questions and doubts from an expert who is involved in

the all the major and minor processes of the ERP software. We noted down all the

details provided by the expert who explained all the modules of the ERP software and

measured the emphasis of each answer and points, which would help us to frame the

generalized questions.

The list of generalized questions which were picked up from the above session were

looked through and analyzed so as to come to a conclusion to a set of 15 questions

which would provide with the important problems that the customers are facing and

experiencing while using the software. Using the picked up the questions from the

generalized list of questions, we prepare the questionnaire of a set of quantitative as

well as qualitative questions. The quantitative questions were given a rating of a scale

from 1 to 5.Where 1 signifies the minimum satisfaction and 5 signifies the maximum

satisfaction.

The next step after the forms are received from the different department the

segregation of questionnaire is to take place. The segregation of questionnaire is done

by visual inspection and analysis. The questionnaires, which are filled by the various

customers who are the infrequent users of the ERP software, were sorted out and

separated from the customers who are the active and the frequent users of the ERP

software. The number of questionnaires collected after the segregation of the data

filled questionnaires is 158.

The rating given by the various customers to the quantitative questions which were of

the scale of 1 to 5, each of the 14 quantitative questions of each of the questionnaire

are averaged out. From the above calculation we can find the average rating of each

question and the overall rating. The overall rating that is obtained from the

questionnaire helps us figure out and structure the problem the customers are facing

while using the ERP software.

Now, the defects are to be found out. To find out the defects the sigma level technique

is used on the quantitative questions. Here the average rating of each customer was

calculated and a rating of 2 or below was assigned a defect. This is considered a

highly unsatisfactory part of the ERP software through the customer’s point of view

and is considered a defect. The quantitative question which are given a rating of 3 and

above are assigned by the customers, are considered a satisfactory part of the ERP

software through the customer’s point of view and is considered a non defect.

Fig. 4.41: Defects in each category

As the number of defects and number of non-defects or accepted questions are

calculated by going through the questionnaires, using the formula defects per million

is calculated. Defects per million is calculated as it is required and is also an important

parameter in the sigma level technique of solving problems. Defects per million is

calculated using the formula which has many factors and depends from situation to

situation. The formula is provided in the annexure.

0

20

40

60

Fig. 4.42: Six sigma calculator

The sigma level calculator is the method through which the sigma level is calculated

in this problem. In the sigma level calculator many parameters are to be filled in. the

parameters are Number of opportunities, number of CTQ’s, total number of

opportunities. After all these parameters are entered the sigma level calculator uses

these parameters and set of standard formulas to calculate the sigma level. To reach to

the final sigma level of the ERP software there are number of parameters the sigma

level calculator calculates which are, DPMO, defect percentage, yield percentage.

Now the sigma level is calculated and the value is 3.138748.

Table 4.16: Process sigma level before improvement

Number of Opportunities 158

Number of CTQs 1

Total Number of Opportunities (#Opportunities * #CTQs) 158

Number of Defects 8

DPMO 50632.91

Defect Percentage 5.063291

Yield (%) 94.93671

Process Sigma 3.238748

The weight age for each of these categories were provided by the following means:

Expert opinion

Equal weight age

Random weight age

The expert opinion weight age was given to us by the expert users of the software

from the administrative Customer of the company.

Expert weight age rating:

Here, we have made use of the weight ages provided to us by expert opinion.

Graphical User Interface – 0.08

Data Exchange – 0.08

Data Processing – 0.09

Data Entry – 0.09

Data Interpretation – 0.09

Support By Supplier – 0.09

Integration By Other Methods – 0.09

Utilisation – 0.06

Individual Adaptability – 0.06

Support For Introduction Of Software Update – 0.09

Notification – 0.09

Database – 0.09

Fig. 4.43: Weightage given by export

These weight ages given above are first multiplied by the actual ratings given by the

customers in each category to obtain the actual rating index.

Similarly, these weight ages are multiplied by the ideal rating, which is taken to be 5,

in each category to obtain the ideal rating index.

9%

8%

8%

9%

8%

11% 7%

8%

7%

10%

7%

8%

   Graphical User Interface

Data Exchange

Data Processing

Data Entry

Data Interpretation

Support By Supplier

Integration By Other Methods

Utilisation

Individual Adaptability

Support For Introduction Of SoftwareUpdateNotification

  Database

The actual and the ideal rating indexes are added up to obtain the satisfaction index

for actual ratings and ideal ratings. These two indexes are compared to get a fair idea

of the level of satisfaction of the customers who’re using the software.

The equal weight age was taken using the following formula:

Weight age for each category = 100 / no. of categories

= 100 / 12

= 8.83(%)

The random weight age were taken from a non-user of the software, hence random in

nature.

Equal weight age rating:

Here, we have used the equal weight age for each of the categories. The weight age

for each category is taken to be 0.083.

As done for the expert rating index calculations, each of the actual ratings in each

category are multiplied by the respective weight age in order to obtain the actual

rating index whose total sum gives the actual satisfaction index.

Similarly, the ideal ratings are multiplied by the respective weight age to find out the

ideal rating index whose total sum gives the ideal satisfaction index.

The actual and ideal satisfaction indexes are further compared to get a fair idea of the

level of satisfaction of the customers who’re using the software.

Random weight age rating:

Here, we have used the weight ages given to us by a non-user of the software such

that the weight ages are random in nature. The weight ages given to us are given

below:

Graphical User Interface – 0.09

Data Exchange – 0.08

Data Processing – 0.08

Data Entry – 0.09

Data Interpretation – 0.08

Support By Supplier – 0.10

Integration By Other Methods – 0.07

Utilisation – 0.08

Individual Adaptability – 0.06

Support For Introduction Of Software Update – 0.09

Notification – 0.09

Database – 0.09

Fig. 4.44: Random weightage

In this case too, to obtain the actual rating index, we multiply the actual ratings in

each category with the respective weight ages. The sum of the values of the actual

rating index gives us the actual satisfaction index.

The ideal rating index is obtained by multiplying the ideal rating with the respective

weight ages. The sum of this index gives us the ideal satisfaction index.

The actual and ideal satisfaction indexes help us get a fair idea of the level of

satisfaction of the end-users of the software.

Customer satisfaction index calculated:

Hence, using the weight age methods described above, we can obtain the customer

satisfaction for each of the ratings namely expert ratings, using equal weight age and

random weight age.

9%

8%

8%

9%

8%

11% 7%

8%

7%

10%

7%

8%

   Graphical User Interface

Data Exchange

Data Processing

Data Entry

Data Interpretation

Support By Supplier

Integration By Other Methods

Utilisation

Individual Adaptability

Support For Introduction Of Software Update

Notification

  Database

The conclusion of this calculation gives us the following data:

Expert Rating Customer Satisfaction Index = 2.96

Equal Weight age Customer Satisfaction Index = 2.98

Random Weight age Customer Satisfaction Index = 2.98

Note: Ideal Customer Satisfaction Index for each case is taken to be = 5.

We can note that the as a whole, the customer satisfaction index is nearly 60% of the

ideal. This tells us that 60% of the customers are satisfied with the usage of the

software. Also, in the measure stage, we had calculated the sigma level for the

software which is equal to 3.14. This too tells us that out of the entire Customer, about

60% of the users are satisfied with the usage of the software.

Thus we can say that the quantitative as well as the qualitative analysis of the

software are at par with each other and thus giving us a more reliable study end result.

Fig. 4.45: Average rating for categories

It is a step to improve a few key factors confirmed in the previous Analysis process

and pursue a method to improve realistic problems to be ultimately resolved. It is also

a phase to explore the solution how to change, fix and modify the process. A pilot test

00.5

11.5

22.5

33.5

4 3.61

2.76 3.27

2.31

3.44

2.785 2.84 2.81 2.53

3.16 2.78

3.11

Ave

rage

R

ati

ng

is to be made in the actual work for a month to test the improvement plans and an

analysis is to be made on the effect before and after applying the improvement plans

through statistical analysis as in the previous Analysis step. If the result is

unsatisfactory additional improvement plans must be carried out.

All of activities within improve phase are included. It starts from deciding if the

selected Y or Ys need to be improved. Then we need to identify and measure Xs

which associate with the decided Y or Ys. A group of statistical tools and experiments

are applied to find out the improvement opportunities. We can also identify the

special causes for variations among the Xs. If the result is that those variations can be

improved, then they should be removed or their impacts reduced. On the other hand,

if there are no special causes which are identified or those variations cannot be

improved, we shall reapply statistical tools and redesign experiments. If the results do

not change after several iterative, we shall consider that might be the design problems

of process or product. Then, the process or product is designed with the aim of

improvement.

Steps followed:

Gain Improvement Approval: The proposed improvement shall be approved

by everyone involved in Six Sigma project, includes all project team members,

Champion, top management, customer, related process operators. Make sure

everyone can review it.

Implement Solution: Once everything is ready, it is time to implement the

approved solution. A well-designed formal project plan will lead the whole

implementation. Make sure the defined delivers and milestones are reached on

time, and keep contact between affected groups frequently.

Gather customer feedback: If the project is customer involved, or the process

is directly affect customers, customer feedbacks shall be collected timely and

be used to modify project actions.

Assess improvement results: It does not matter that this step shall be done in

here or next phase. The improvement results will be compared with the

statement before improvement. That will show how much improvement the

project have done.

We approached few employees who had mentioned specific problems which they

were facing while using the ERP software. These problems were also found similar in

few other departments.

Since the back end process was not included in the scope of the project these

problems were analyzed and discussed with the people from the project office.

This is the last step of DMAIC cycle and as the name suggests it uses methods that

effectively help in an improvement process being deployed.

Owing to the short span of this project the control stage could not be worked on fully.

But based on the control measures certain suggestions and scope for the improvement

are given.

The objective of control module is to make sure that the problem either does

not occur or a problem that has occurred is rectified and deployed in the right

way.

Table 4.17: Problems occurred in SAP software.

Stock

Transfers

Requirement Remarks Alternative

Solution

Mfg Plant to

Depot

Stock Transfer of materials

from Mfg plant to respective

Depots:- Num ranges should

be defined for each Depot

exclusively i.e., the Num

ranges should be differnet for

each Depot, thereby resulting

in approx 30 Doc types for one

plant.

Not supported by Std

SAP, as defining

multiple doc types for a

single transaction, for

each plant is not

possible.

Depot to

Depot

For the Material moving from

Depot to Depot, the document

type should be different, so as

to differentiate the stock going

out on stock transfer between

the depots

Yes, a separate

document type shall be

defined for the stock

transfers, thereby

differentiation of the

stock transfers with the

depots and sales can be

achieved

NIL

Sales Office

[branches] to

Customers

Num Ranges for " INVOICE

" to be defined, Sales Office

Wise.

Not supported by Std

SAP.

This can be

achieved by the

help of

developing

USER EXIT

Programs.

A help file attached to the server module of the software would be of

immense help to new users and also help improve the satisfaction level of the

existing customers.

More regular surveys and feedback should be collected at scheduled intervals

of time to keep a check on the user satisfaction level.

Table 4.18: Non complying requirements in SAP software.

Issue

ID#

Module Issue Name Description Originator Status* Assigned to

Name

1 General Scope of Project Implementation of HR for Mystique

Apparels and Movers

Rao Closed Raghavan

2 SD Consignment sales material sent to Karnataka Agro-

Accounting issue to be cleared

Jayasheel /

Ramesh

Closed Kiran

3 SD Sales Pricing Structure Needs more clarity on Pricing / Discount

structure

Kiran Closed Jayasheel /

Ramesh

4 QM Core Team Member Core Team member has to be finalised. He

has to be responsible for standardising QM

process across the companies

Vinayak /

Naveen

Closed Tukaram

5 MM Material Valuation Material Valuation effects of change of

value when the value is changed in Moving

Average set up. ??

Ramesh Closed Shantaram /

Naveen

6 HR Time Management Scope of Time Management which has to

be included in the project to run Payroll

Ramesh Closed Murali to take

decision

7 MM Free Samples Inventory Valuation of the materials needs

to be zero

Ramesh Closed

8 MM Material Transfer Transfer of Valuated to non valuated

material

Ramesh Closed

9 HR Travel Management Travel management needs to be mapped

which involves the tracking of the vehicle

mileage and the spends of the employee

Vinayak /

Naveen

open Geetanjali

10 SD \

HR \ FI

Incentive Calculation Incentive calculation for the employees Vinayak /

Naveen

open Kiran /

Geetanjali

Vinayak

Issue

ID#

Module Issue Name Description Originator Status* Assigned to

Name

11 SD Invoice Numbering Stock Transfer of materials from Mfg plant

to respective Depots:- Num ranges should

be defined for each Depot exclusively i.e.,

the Num ranges should be differnet for

each Depot, thereby resulting in approx 30

Doc types for one plant.

Vinayak /

Naveen

open Kiran

12 ALL Retrospective Migration The migration is planned on a retrospective

date so that the yearly returns could be filed

properly

Vinayak /

Naveen

open Tukaram

13 SD Account Assignment issue for

Traded goods

Vinayak /

Naveen

open

14 FI Creation of asset is not possible. Narasimha open

15 FI Addition to the asset is not

possible.

Murali to take

decision

open

16 FI TDS configurations is not

complete.

Murali to take

decision

open

17 FI Service Tax provisions for GTA

(i.e. on Freight/Carriage

inward/Carriage

outward/Transportation

Charges) not configured.

Narasimha open

18 FI VAT provisions not

incorporated.

Narasimha open

19 FI Entry Tax provisions not

complied with.

Narasimha open

20 FI No financial reports are being

abstracted to our satisfaction.

Narasimha open

21 FI TDS quarterly return report in Narasimha open

Issue

ID#

Module Issue Name Description Originator Status* Assigned to

Name

the Form 26Q is not configured.

22 FI In the cash imprest account

before making entry, the system

should ask for the Company

Code. But unfortunately it will

take the previous code and

accepts the entry, which may

lead to wrong entries in the cash

book.

Narasimha open

23 FI Dunning process not explained. Narasimha open

24 FI Controlling module not

configured to our requirements.

Narasimha open

25 FI Depreciation schedule as per

Companies Act not configured.

Narasimha open

26 FI Balance sheet format under

Companies Act is not

configured.

Narasimha open

27 FI Voucher printing for various

transactions not possible.

Narasimha open

Online report generation and online integration would help access final

reports with ease and reduce time for movement of reports. Data entry-

0.690159,Data exchange-0.131803,Support-0.083428,Utilities-0.094610

Fig. 4.46: Screen Shot: User Authenticity

The software supports the variety of end user with the Authenticity.

Fig. 4.47: Screen Shot: Dynamic reporting

Dynamic report can be executed from the materials details.

Fig. 4.48: Screen Shot: Static reporting

Static report can be executed from the materials details.

Fig. 4.49: Screen Shot: Purchase order

The Purchase orders for a specific work order can be link directly into the out plant

processing feature. Purchase order is generated automatically for the selected vendor

when a work order is loaded across the shop floor for an item with an out plant

operation in its routing.

Fig. 4.50: Screen Shot: Sales order report

The sales order report can be delivery document number and delivery date from user

can be fetched form the table.

Fig. 4.51: Screen Shot: Out bound delivery

Orders can be directly transferred for outbound delivery.

Fig. 4.52: Screen Shot: Payment incoming

The details of cheque number, cheque amount, amount applied to invoice, and others

form the incoming payments can be displaced.

Fig. 4.53: Screen Shot: Billing

The billing document can generate accounting document.

Now the six sigma calculator is used to calculate the sigma level. The process

opportunities and the defects are entered into the six sigma calculator, the

characteristic to quality i.e. the unit is given as 1 because only customer satisfaction is

what we are concentrating on. The opportunities are given as 200 and the defects we

are mainly concentrating are 4 they are data entry, data exchange, support, utilities.

The sigma shift is given as 1.5

The calculated results are as follows:

The defects in percentage is equal to 2.00%

The yield in percentage is equal to 98.00%

And the process sigma is found to be 3.554.

The process sigma of the previous batch was found to be 3.15 and there 0.409

increase in the sigma level only for 4 defects. If the same is done for the other

categories of the defect then there will be an increase in the sigma level.

Table 4.19: Process sigma level after improvement

Number of opportunities 200

Number of CTQs 1

Total Number of Opportunities(#opportunities*#CTQs) 200

Number of Defects 4

DPMO 20000

Defect Percentage 2.00%

Yield 98.00%

Process Sigma 3.554

A help file attached to the server module of the software would be of immense help to

new users and also help improve the satisfaction level of the existing customers.

More regular surveys and feedback should be collected at scheduled intervals of time

to keep a check on the user satisfaction level. Creating a back-up so that manual entry

and data entry into the software need not be repeated.

Online report generation and online integration would help access final reports with

ease and reduce time for movement of reports.

Fig. 4.54 – Integrated frame work for Successful ERP Implementation

4.9 Integrated frame work for Successful ERP implementation

Integrated model aligns with the organizational operations management solution with the

business processes and information in ERP system. This model shows how the various

processes interchange information with each other as well as with the external environment.

Strategic planning activities includes provision of total quality management enabling

enterprise to implement their mission and vision by aligning policies, goals and other

stakeholders’ needs, supported by a continuously improving management of resources and

processes. The strategy is translated into plans, objectives and measurable targets. Planning

and strategy also reflects the organisation’s approach to implementing modernisation and

innovation.

Business planning activities supports enterprise in adopting new technology, follow up of

government regulations and company’s norms while the operational planning and execution

depict functionality relating to customer.

The important fact of our model is the database that should provide the integration of

information system that includes many units of measure, costing and pricing, Asset

management for materials should handle all necessary cost information like direct material

cost as well as kind of cost, form last in, weighted average or periodic value at its source.

Creation of cross system application starting from material reporting ,going all the way to

machine monitoring and control and post sales statistics, in between the critical areas

inventory issues , operational, dispatch and collection of money.

Various pricing scenarios should be provided to impact on measure the performance like

sales, profitability and customer satisfaction. For the execution of software it is necessary to

bring the notice of the end user rather than the top management. It should function like a

people driven rather than process driven. Project estimation techniques are essential to avoid

any cost or the time over run by the teams

Customer satisfaction is a closed loop that measures the satisfaction with the ERP software

they used. Potential respondents are screened prior to interviewing to guarantee inclusion of

customers of a wide range of business-to-consumer products and services, results from data

collection and analyses are released to the enterprise throughout end of each calendar year.