Six Sigma Project_Gaurav Singh

7/27/2019 Six Sigma Project_Gaurav Singh

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Project Report

Six Sigma- Green Belt Programme

SQC & OR Unit

Indian Statistical Institute, New Delhi

Gaurav Singh

Project Guide

Rina Chakraborty


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Executive Summary

This paper consists of a project on Accounting. The project is set in the backdrop of increased

demand for better customer (internal & external) service thorough timely release of online

system (Micros-Fedelio) after auditing.

The entire job focus was to check revenue losses that might have occurred during the

transactions.

The revenue generating departments viz laundry, spa, banquet, bar, restaurants, makes entries of

all the transaction in micros. This information is transmitted to Fidelio through an interface.

Relating with the job focus the whole concern was to filter all transactional information and pass

it on to the Accounts department for proper recording.

The job demanded the use of certain automated auditing process (indexing etc). During this

process of automated auditing the major concern was to keep all other users of (Micros-Fedelio)

the software logged off and not allowing any further entries or information flow. The system was

again provided back to the departments after successful completion of Auditing.

As a result front office had no information about the total bills of a guest who is checking out

during the auditing process.

This project focuses on the timely delivery of the system to all the concerned departments by

avoiding delays due to software failure and preventing intruders.

The endeavor is to strike a balance between timely deliveries of system (VOC) and ensure proper

accounting (VOB).


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Problem statement

Non-availability of system on time data.

Project scope

As mentioned earlier non availability of system results to revenue loss for the organization. If

this problem is addressed properly it will help in revenue increment.

Critical tools

Pareto chart fish bone diagram Failure mode effect analysis control chart

Results

It has been observed that 6.52% is the frequency for failure.

Conclusion & Recommendations

Lack of security in the software to stop log in: redesign the software to secure it from intrusions

during audit procedure.Pre night audit corrections: to train staff properly in order to reduce mistakes


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Define Phase

Problem statement

Non-availability of system on time. The ideal time for making the system available is 4 am but it

can be tolerated till 4:30am.

Project scope

As mentioned earlier non availability of system results to revenue loss for the organization. If

this problem is addressed properly it will help in revenue increment.

Audit and systems

Front Office

Guest Room

Restaurant

Laundry

This is a schematic representation of how the information of various types of consumption by a

customer is distributed among various departments. System & audit department is responsible

for posting all room charges. The consumptions made by an in house guest in any outlet is posted

directly to his room along with his room charges. During check outs front office takes out the

actual bill (room charges + other consumptions) through Fedelio, and the bill is presented to the

guest for payment.


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MICROS

(At revenue generating heads)

Interface

FIDELIO

(Used by front office, Audit & systems)

Interface

Oasis

(Final accounting software)

This shows the flow of information within the softwares. Most of the departments use Micros

system while departments like Front Office, Systems and audit uses Fidelio, oasis is only used by

Accounts for final documentation. The flow of information between every software is intermitted

by an interface.

The current system pays attention to the most frequented VOC (voice of customer) System is not

available (due to delay in audit) while a guest is on the verge of leaving the hotel. On the other

hand VOB (voice of business) is responsible for loosing revenue due to non availability of

system. Both VOC & VOB talks about non availability of system- constitute the take of point for

this project.

Key measures

Impact on key business

Following threat-opportunity matrix shows some of the short and long term business impacts.


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Harassment of customers

Revenue loss

Increased customer satisfaction

Increase in revenue

Business value defeated

Loss of good will

Creation of business value

Creation of good will

Short Term

Long Term

Threat Opportunity

The Measure Phase

Performance

Identification of kpivs & kpovs

Quantify current performance level:

Issues Jan Feb Mar April

Number of days 31 28 31 30

System released

on time

28 27 20 29

System release 3 1 11 2


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delayed

DPMO 96774 35714 354838 64516

The month wise data and the current run chart shows that the defect level in the month of March

is abnormally high. This was mainly due to some exceptional machinery failure. Except for the

data of March the rest of three month data is considered in arriving at the process defect.

Current defect level

Total number of System release delays ( All three months) *106

Total number of days in 3 months (excluding the month of March)

Total number of System release delays (computing all three months) = 6 days

Total number of days in 3 months (excluding the month of March) = 92 days

= 65217 this is approximately equal to 3.009 Sigma


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Targeted DPMO = 50 % of the current DPMO

Targeted DPMO = 32608 this is approximately equal to = 3.345 Sigma

Current DPMO 65217

Targeted DPMO 32608


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Analysis and Findings

Fish bone diagram

The project team uses a fishbone diagram to identify all the input variables that could be causing

the problem of interest. Once we list out the input variables we can identify the critical few

process input variables to measure and further investigate.

Non delivery of system on time

MEN

Training Experience intrusions

MACHINE

Number of os NO of systems

ENVIRONMENT

Seasons No of employees Experience of employees. Lack of security in the software to stop log in

MATERIAL

Rush at the restaurants Stability of accounting system

METHOD

Closing of RGHs Pre night audit corrections

MEASUREMENT

Revenue loss Customer dissatisfaction


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Starting of CRIS delayedAfter listing of all the input variables, some of the key process input variables (KPIV), Lack of

security in the software to stop log in, pre night audit corrections

are identified as the main culprits. The entire focus is turned to these two problems referred to as

vital Xs.

dentifying vital Xs

Potential Xs Jan Feb April FREQUENCY

1)

2)

3)

Lack of security in the

software to stop log in.

Pre night audit corrections

Rush at the restaurants

2 1 1

1

1

4

1

1

TOTAL 3 1 2 6

It can be observed that out of a total of 6 occurrences 4 are attributed to lack of security in the



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Pareto chart of potential Xs


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It can be seen that the problems Lack of security in the software to stop log in and pre- night

audit corrections together form more than 80% of the assignable cause. Hence we are targeting

these two most prominent problems, solutions of which will help reduction in the problem and

vis--vis increase the sigma level of the operation.

High Medium Low

Within control Lack of security in the


Pre night audit

corrections

Beyond control Rush at the restaurants

Analyzing vital Xs

The focus now converges into two controllable factors affecting replenishment performance

Lack of security in the software to stop log in Pre night audit corrections

Lack of security in the software to stop log in

It has been observed that the major reason for the delay in releasing the system is log in after the

audit starts off. This results in corruption in the system as a result, finally the entire process of

night audit is delayed and subsequently the system delivery does not take place on time. Out of

the total number of observations 66.67% pertains to this problem.

It is also observed that during the month of January, out of a total 3 failures 2 are assigned to this

current problem of Lack of Security in the software to stop log in.


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As a result any person entitled to use this software can log into the system even after the rights

for the access has been withdrawn and the night audit is hampered.

Pre night audit corrections.

The time of release of system to the users on time is also commanded by the number of

accounting errors that the auditor has to handle before moving on to the night audit procedure.

The problems may vary from incorrect room rent charged to wrong settlement type (credit card

in place of case or vice versa). In all the cases of error (since this is not under the current scope

of the defied problem) it can be assumed that they happen because of lack of proper training and

development and excess work load.

Improvement

Failur e mode and effects analysis

This process is used to understand and quantify the relative importance of the major concerns

and its development components

Concerns Ratings Improvement of

software

Training Increase of

manpower.

Lack of security in

the software to stop

log in.

5 5

(25)

0

(5)

0

(0)


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Pre night audit

corrections

4 2

(8)

2

(8)

3

(12)

Rush at the

restaurants

1 0

(0)

2

(2)

4

(4)

Lack of Training 2 1

(2)

4

(8)

1

(2)

Improvement of software

Improvement of software is one of the major issue of improvement. The software lacks the

facility of restricting the user to access datas or to make entries while auditing is being

conducted. The software also lacks the facility of at least warning the user before allowing access

incase the user is trying to access it during the time audit is being conducted.

Therefore the software has to include a warning signal to user when they try to log in during

night audit, and also restrict the user if necessary.

There should be a window dedicatedly for information purpose and it can be accessed even

during audit. This system will help checking revenue loss by providing updated billing

information to the front office and subsequently to the customers.

Pre night audit corrections

The timely delivery of system also depends on how many errors has crept in during the day, the

auditor first has to resolve these problems before he moves on to automated night audit

procedure.


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The errors are mostly due to lack of proper training and excess work load. The training related

issue can be taken care of by training the staff in using the software by conducting mock

transaction. As far as the workload is concerned it can be handled through proper recruitment

process and decreasing the per day working hours.

Previous sigma level 3.009

Current sigma level 3.249

Time for system access restored for the month of May

DAY Time (am)

1 4

2 4:11

3 4

4 4:02

5 4:05

6 4

7 4


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8 4

9 4:07

10 4:16

11 4:01

12 4

13 4:12

14 4:13

15 4:04

16 4

17 4:17

18 4:22

19 4:45

20 4:08

21 4:16

22 4:03

23 4

24 4

25 4:07

26 4

27 4:11

28 4:23

29 4:14

30 4

31 4:27

Calculation of improved Sigma level:

Issues May June July August

Number of days 31 30 31 31


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System released

on time

30 29 30 29

System release

delayed

1 0 1 2

DPMO 32258 0 32258 32258

Total number of System release delays ( All three months) *106

Total number of days in 4 months

Total number of System release delays = 4 days

Total number of days in 4 months (excluding the month of March) = 123 days

= 32520 this is approximately equal to 3.24 Sigma.

Control phase

For the purpose of verification of control a simplified control chart (attached in the graph) is

implemented with a tolerance limit of 4:30 am, the ideal time for delivery of system remains at 4

am. in the control chart there are three upper limits defined (lower limit does not exist) as 4am

ideal time, 4:15am minimum tolerance time, 4:30 maximum tolerance time. For a one month

data (may) if plotted on a graph it will have 24 points within the minimum tolerance limit

(4:15am), 6 points within the maximum tolerance time(bold points) and 1 point above the

maximum tolerance time (4:30 am, point and a circle)

Every time the system is delivered above the minimum tolerance limit the observer can become

alert and adjust some KPIVs to regain desired performance. If the graph shows a point abovethe maximum tolerance limit it means the system requires adjustments it might have fallen out of

control.


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Conclusions

Restatement of quantified project results:

Operating DPMO: 65217

Operating sigma level: 3.009

No of days under observation: 92 days

Projected results:

Targeted reduction of DPMO: 50%

Predicted DPMO: 32608

Predicted sigma level: 3.34

No of days under observation; 123 days

Key performances input variables

Lack of security in the software to stop log in. Pre night audit corrections.

Recommendations

Lack of security in the software to stop log in: redesign the software to secure it fromintrusions during audit procedure.

Pre night audit corrections: to train staff properly in order to reduce mistakes.

Appendix

Six sigma green belt training module(ISI) All about Six Sigma- Warren Brussee

Six Sigma Project_Gaurav Singh

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