LEAD TIME & INVENTORY REDUCTIONIN APPAREL SUPPLY CHAIN

Team Synergy

Abhishek KumarMangala MRashmi RaoJisna P Gopi

ABOUT THE COMPANY

• Manufacturing arm of Madura Garments having brands like Louis Philippe , Van Heusen , Allen Solly and Peter England

• It comprises of 4 factories located in Bangalore , with a total employee strength close to 3000.

• The product range offered is men’s and women’s formal –Shirts , Trousers and Suits with annual volumes of 43.6 Lakh garments.

Aditya Birla Group

AB Nuvo

Madura Garments

Madura Clothing

Vision: “To be a global benchmark for apparel industry in manufacturing and innovation providing competitive advantage to stake holders”

Note:-To understand the apparel supply chain in brief which will help to understand the project better

APPAREL SUPPLY CHAIN

NEED FOR PROJECTNo well defined and scientific replenishment model and stocking policyStagnating sales growth year-on-year basisHigh finished goods inventoryIncrease in discounted sales year on year leading to profit erosion

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LP Core FG Inventory : FY08-10

FG inventory in the range of 5000pcs while Retail sales in

400pcs per month, hence carrying 10 months more

inventory

Due to such high FG inventory level, cash flow for business is blocked and discounted sales

increasing to improve it

PROJECT CHARTER

Business Case : Total Lead time ofApparel supply chain was 130 daysand there has been noreplenishment leading to high out-of-stock rate. The inventory levelwas very high carrying 9 monthsinventory.

This threw up tremendous potentialfor improving the lead time andinventory reduction

Scope: Fabric procurement toRetail Sales

Relation with business case , approach , scope , CTQ’s and benefits were finalized in the charter

SIPOC

Fabric procurement

from mill

Fabric procurement

from mill

Fabric storage at

factory

Fabric storage at

factory

Garment mfg at factory

Garment mfg at factory

FG storage at

WH

FG storage at

WH

Retail store

replenish

Retail store

replenishRetail salesRetail sales

Core

CORE REPLENISHMENT SYSTEM

Factory

Warehouse

Retail Store

Consumer

CRS ( Pull Strategy)

Fabric Mills

Core products would be managed using continuous replenishment at FG as well as fabric stages …

CORE REPLENISHMENT SYSTEM

Core products would be managed using continuous replenishment at FG as well as fabric stages …

Orders are Aggregated Order

Garment Production

PO Preparation

Sends the order

WO is generated

WO

Supplies Fabric PO

FabricOrderDetails

FabricStatus

Garments

Pending Order File

Warehouse Factory

Purchase

Supplier

Customer

FG Stocks,WIP

Levels

Fabric StocksIn-Transit, Fabric

RoP Levels

FabricAvb.

yes

no

Fulfill

CTQ TREE DIAGRAM

Reduction ofLead time andinventory inApparel Supplychain for CoreReplenishmentSystem

Garment Manufacturing

REWORK%

RECUTTING%

MANUFACTURING LEAD TIME

Finished Goods INVENTORY (DAYS)

Fabric LEAD TIME (DAYS)

Retail RETAIL SALES (PCS)

Critical To Quality Characteristics (CTQ)

Operational Definition Measure

Current Status

CTQ Specification

Defect Definition

KANO Status

1. FABRIC PROCUREMENT LEAD TIME (DAYS)

FABRIC LEAD TIME FROM PO CREATION TO DELIVERY AT FACORY STORES

105 Days <15 Days > 15 Days MUST BE

2. MANUFACTURING LEAD TIME (DAYS)

TIME FROM WO CREATION TO DELIERY AT FACTORY WAREHOUSE

18 Days <12 Days > 12 Days MUST BE

3. FINISHED GOODS INVENTORY IN WH (DAYS)

FINISHED GOODS INVENTORY IN DAYS

271Days < 60 Days > 60 Days MUST BE

4. RETAIL SALES (PCS) RETAIL SALES IN PIECES

400 Pcs >500 Pcs < 500 PCS MUST BE

5. RECUTTING (%) PANELSRECUTTING

4% <3% >3% LOWER THE BETTER

BATCH RECUTTING 3% <1% >1%

6. REWORK (%) END OF LINE 7.83% < 7% >7% LOWER THE BETTER

FQC 1.73% <5% >5%

The project objective (Y) is addressed by focusing on the Must Be” CTQ’s (y’s) identified as shown above

CTQ TABLE

MILESTONE

GANTT CHART

Jun’10 Jul’10 Aug’10 Sep’10 Oct’10 Nov’10 Dec’10 Jan’11

DEFINEProject CharterSIPOCCTQ Tree Diagram

MEASUREAs-is CTQ Status

APPROACH/ ANALYSISCause & Effect DiagramFMEA

DEPLOYMENT/ IMPROVENVA Identification & stratificationSetting up section wise WIP NormsSingle piece clearance on daily basisDeveloping system to monitor online

ASSESSMENT & REVIEW/ CONTROLImplementing control mechanismSustenance (Review & Assessment)Replication

CTQ 1: FABRIC LEAD TIME REDUCTION AT FABRIC MILL

The Strategic supplier relationship management is required to

Ensure the strategic partnership with fabric millsEnsure reduced fabric lead time by Vendor managed inventoryEnsure improved service levels for fabric lead time and qualityEnsure building base stock to service peak season demand

ANALYZE

An internal brainstorming session, helped to narrow down the Focus area for

Deployment in spoke from “12 Spoke solution design”

with strong core

IMPROVE

• SATISFACTIONSURVEY• HALF YEARLY FEEDBACK REPORT

Supplier Segmentation

(Supplier wise strategy )

Vendor Connect

(IT Enablement)

Supplier Forums

(Relationship Mapping)

Supplier Feedback

CONTROL After establishing Strategic supplier

relationship, critical vendors identified based on following parameters for rationalization: Geographic Location Delivery, Quality, Cost

VMI has been adopted for critical vendors by providing them Quarterly projections to deliver stock on-demand

After implementing VMI, due to reduction in Fabric lead time and improved service levels, base stock was built to service

ESCALATION MATRIXLEAD TIME

DELAYVENDOR/ INCHARGE

PURCHASE MANAGER

SOURCING HEAD

BRANDHEAD

14 Days10 Days7 Days2 Days

Safety Stock

Reorder Point

CTQ 2 : GMT MFG LEAD TIME REDUCTION AT FACTORY

The reduction in Garment manufacturing lead time is done by

Ensure timely delivery of finished goods at warehouse against SLAIdentifying potential causes for high manufacturing lead timeIdentifying root causes by using FMEA Implementing improvement solutions for those root causesImplementing controls to ensure that implemented solutions sustain

DIAGNOSING POTENTIAL ROOT CAUSES

An internal brainstorming session, helped to narrow down from 52 x’s to more

likely root causes for further analysis

Single pc clearanceFurther, FMEA was carried out to help in prioritizing the potential root causes

FMEA FOR PRIORITIZING POTENTIAL ROOT CAUSES

Cause

Probability of

Occurrence

Severity Of Conseque

nce

Difficulty of

Detection

(A) Probability

of Occurrenc

e

(B) Consequen

ce(C)

Detection

Risk Priority

No. (RPN)

(High / Medium / Low)Rating (1-6-9) 1 = lowest, 6 =

medium, 9 = highest A x B x C

Lack of work aid Low Medium Medium 1 6 6 36Mismatching of material Medium Medium Low 6 6 1 36Fabric Defect & Shade variation Medium High Low 6 9 1 54Improper method due to lack of adherance to SOP Low High Medium 1 9 6 54Planning procedure leading to improperrelease of work orders Medium High Medium 6 9 6 324High sectional WIP due to lack of adherance to WIP Norms High High Medium 9 9 6 486Delay in single piece clearance due to lack ofsupervision High High High 9 9 9 729

2 main causes having highest RPNs were selected to work on

High RPN root causes 486 and 729 respectively are identified and

action taken to reduce it

IMPROVEMENT Delay in single piece clearance due to lack of supervision

Tracking format implemented for tracking down the single piece in the section

Operators and supervisors were educated to clear single piece

Daily review for deviations

Results Statistical Validation

SINGLE PIECE CLEARANCE TRACKING

2-Variance test was done and since p-value (0.498) is greater than 0.05, there is no significant change in the variation

2-sample t-test was done and since the p-value (0.002) is less than 0.05, there is significant reduction in single piece clearance time.

IMPROVEMENT

High Net WIP due to lack of adherance to WIP norms

Section wise norms were fixed based on the daily productionof section

Implementation of pull system inWIP based WO release

Daily review for deviations

2-Variance test was done and since p-value (0.587) is greater than 0.05, there is no significant change in the variation

2-sample t-test was done and since the p-value (0.006) is less than 0.05, there is significant reduction in Net WIP (pcs)

Results Statistical Validation

FMEA FOR RESULT VALIDATIONFailure Mode Effect Analysis (FMEA) for Validating the solutions.

Cause Probability

Severity Of

Consequence

Difficulty of

Detection

(A) Poten

tial

(B) Consequenc

e

(C) Detect

ion

Risk Priority

No. (RPN)

Implemented Preventive Action

(A1) Probability

(B1) Severi

ty

(C1) Detection

Residual No.

(High / Medium / Low) Rating (1-6-9) 1 = lowest, 6 = medium, 9 =

highest

A x B x C

Rating (1-6-9) 1 = lowest, 6 = medium, 9

= highest

A1 x B1 x C1

Lack of work aid

Low Medium High 1 6 9 54 1 6 9 54

Mismatching of material

Medium Medium Low 6 6 1 36 6 6 1 36

Fabric Defect & Shade variation

Medium High Low 6 9 1 54 6 9 1 54

Improper method due to lack of adherance to SOP

Low High Medium 1 9 6 54 1 9 6 54

Planning procedure leading to improper release of work orders

Medium High Medium 6 9 6 324 Implementation of pull system, WIP based work

order release system

6 1 6 36

High sectionalWIP due to lack of adherance to WIP Norms

High High Medium 9 9 6 486 Establishing section wise WIP norms and ensuring

adherance to it

1 9 6 54

Delay in single piece clearance due to lack ofsupervision

High High High 9 9 9 729 Establishing single piece clearance tracking sheet

and ensuring adherance to it

1 9 6 54

With the implemented solution RPN of root causes came down from 486 and 729 to

54 respectively which validates the

effectiveness of solution

Sheet to record details of all alterations of same product,

different batches

Single piece clearance of monitoring on a day to day basisRegular training to operators on clearing single pieces on top-priorityOn-site board for supervisors to keep tracking single pieces and Section wise WIPHolding dispatch till 100% single pc clearanceWeekly reviews by Production Manager for ensuring adherance to Section wise WIP norm and single pc clearance

CONTROL

On-site board for production monitoring , style description

and daily wo clearance

Standard operating procedures in all sections to

ensure the process adherence

BENEFITS : MFG LEAD TIME REDUCTION

Two-Sample T-Test and CI: After Tpt time, Before Tpt timeTwo-sample T for After vs Before

N Mean StDev SE MeanAfter 4 12.50 2.65 1.3Before 9 29.44 6.37 2.1Difference = mu (After) - mu (Before)Estimate for difference: -16.944495% upper bound for difference: -12.4122T-Test of difference = 0 (vs <): T-Value = -6.78 P-Value = 0.000 DF = 10

2-Variance test was done and since p-value is greater than 0.05, there is no significant change in the variation

2-sample t-test was done and since the p-value is less than 0.05, there is significant reduction in throughput time.

Reduction in Suits average manufacturing lead time from 18 days to 12 days (0.4 times improvement)

CTQ 3: FG INVENTORY REDUCTION AT WAREHOUSE

The Warehouse replenishment system for finished goods to warehouse required to

Ensure work orders are created to fill the inventory gap at warehouseEnsure that replenishment is aligned to sales as per pull modelEnsure that inventory carrying cost of finished goods is reduced

Warehouse replenishment approach to provide the brands with a competitive advantage of Replenishment Model, which characterizes

Planning Horizon of fortnight with Weekly Wave Model of Work Ordering and Delivery cycle

IMPROVEFactory

Warehouse

Wo Creation

Pre-production activity (1 Days)

11 Days against SLA

Wo Release

Forecasting/ WH Stock Gap against Norm

Every Monday

Production Plan for filling Gap Fabrics &

Trims in-stockEvery

Tuesday

1 Day Every Tuesday

Entoma Warehouse

(Retail)2 DaysRetail

Store1 Day

IMPROVE (Contd) Work ordering cycle : Weekly (on every Tuesday),Delivery cycle : 12 working days from day of work order creation for blazers/

SuitsMOQ per style code : 10 pcs (based on cutting and marker laying efficiency)Fabric Norm: 1 month of salesWarehouse Norm: 1 month of sales

Assessment Mechanism (Daily)OTIFLead Time

Review Mechanism (Quarterly)WH InventoryFabric Inventory

Service level Agreement0

50

100

150

200

250

300

May Jun Jul Aug Sep Oct

Jun

+ Ju

l Req

uire

men

tBui

ldin

g

Safe

ty S

tock

Bui

ldin

g

MF&L INVENTORY REPLENISHMENT MODEL (MONTH ON MONTH) - AW

GAP REPLENISHMENT

CONTROL

Based on the Scenarios, work order were created to

replenish the gap in warehouse inventory

Daily Status of Work orders were sent to brands for

ensuring the transparency in work order execution

ESCALATION MATRIXLEAD TIME

DELAYSUPERVISOR PRODUCTION

MANAGERFACTORY

MANAGERHEAD OF

MFG4 Days3 Days2 Days1 Day

For process, Smart Transactional Excel Macros were developed for: Monitoring Retail Sales Monitoring Retail Inventory Monitoring WH Inventory Monitoring Gap in WH inventory

against Norm due to retail sales Work order need to be created

based on gaps on weekly basis

To improve the transparency in work order execution as control sheet, Daily status is sent to all stakeholders

Escalation matrix established for handling lead time delays

BENEFITS : FG INVENTORY REDUCTION

Two-Sample T-Test and CI: After Inventory, Before Inventory Two-sample T for After Inventory vs Before Inventory

SEN Mean StDev Mean

After Inventory 7 72.4 28.4 11Before Inventory 5 208.6 68.8 31Difference = mu (After Inventory) - mu (Before Inventory)Estimate for difference: -136.17195% upper bound for difference: -66.697T-Test of difference = 0 (vs <): T-Value = -4.18 P-Value = 0.007 DF = 4

2-Variance test was done and since p-value is greater than 0.05, there is no significant change in the variation

2-sample t-test was done and since the p-value is less than 0.05, there is significant reduction in inventory

Reduction in Suits inventory from 9 months to 2 months (4.5 times improvement)

CTQ 4: SALES IMPROVEMENT AT RETAIL STORE

The Retail replenishment system for finished goods to retail stores is required to

Ensure timely delivery of finished goods at retail store against SLAEnsure STO are created to fill the inventory gap at retail storesEnsure that replenishment is aligned to sales as per pull modelEnsure that sale of finished goods is improved

Retail replenishment approach would ensure that local customer preferences as well as brand’s targeted sales is maintained...

IMPROVEProvide information on store traffic, demand patterns, gaps in merchandise

Provide with weekly control reports to monitor inventory and store look

IMPROVE

Retail management system -Micro strategy and Business warehouse was implemented in year 2009 to provide transparency across the 68 retail stores of LP Store Sales Store Inventory In-transit inventory

To replenish retail stock in northern and western region, couriers are used to reduce replenishment time within 3 days

All India One Stock (AIOS) system deployed for cross-docking, one retail store to another retail store

Micro strategy software to monitor store sales,

inventory

Business warehouse software to monitor in-transit inventory and AIOS system

CONTROL

ESCALATION MATRIXOUT OF STOCK

VENDOR/ INCHARGE

RETAIL MERCHANT

RETAIL HEAD

BRANDHEAD

4 Days3 Days2 Days1 Day

For process, Out-of-stock and Transit time is monitored and reviewed on daily basis based on: Retail Sales Retail Inventory Retail inventory norm Monitoring gap in Retail inventory

against Norm Stock transfer order need to be

created based on gaps

Escalation matrix established for handling transit time delays

Store Transit Time (Days) Before After

% Improvement

APK 2.56 1.38 46.09%TN/ KERALA 2.45 1.28 47.76%

WEST 6.28 2.96 52.87%NORTH 7.43 3.21 56.80%

AVERAGE 4.68 2.21 52.83%

(IN PCS)

Month NormActual Stock

Out-of-stock

Sales Loss %

Jul 1367 932 435 32%Aug 1367 830 537 39%Sep 1367 1067 300 22%Oct 2734 2568 166 6%Nov 2734 2876 0 0%Dec 2734 2754 0 0%

BENEFITS : SALES IMPROVEMENT

Two-Sample T-Test and CI: Before Sale, After Sale Two-sample T for Before Sale vs After Sale

SEN Mean StDev Mean

Before Sale 12 174.7 43.0 12After Sale 3 717.7 38.7 22Difference = mu (Before Sale) - mu (After Sale)Estimate for difference: -543.00095% upper bound for difference: -482.904T-Test of difference = 0 (vs <): T-Value = -21.26 P-Value = 0.000 DF = 3

2-Variance test was done and since p-value is greater than 0.05, there is no significant change in the variation

2-sample t-test was done and since the p-value is less than 0.05, there is significant improvement in sales

Increase in Suits retail sales from avg 400 pcs sales to avg 785pcs in peak season (2 times improvement)

OVERALL BENEFIT

FINANCIAL BENEFIT FOR SUITS & BLAZER IN RETAIL CHANNELBUDGETED SALES PROJECTION (JAN’11-DEC’11) – 3375 pcs (Rs. 1.68 crores/ Annum)

DUE TO RETAIL REPLENISHMENT, 40% REDUCTION IN BUDGETED SALES LOSSNOV’10- JAN’11 ACTUAL SALES IMPROVEMENT – 800 PCS, ACTUAL EXTRA REVENUE – Rs20 Lacs

EXPECTED SALES IMPROVEMENT DUE TO RETAIL REPLENISHMENT – 1350 pcs/ AnnumEXPECTED PROFIT DUE TO SALES IMPROVEMENT– Rs33.6 Lacs/ Annum (Profit@Rs 2500/pc)

NET LEAD TIME REDUCTION(FABRIC + MANUFACTURING + RETAIL REPLENISHMENT) LEAD TIMEBEFORE, 105 + 18 + 7 (Max in case of Delhi) – 130 DaysAFTER, 15+12+3 (Max in case of Delhi) – 30 DaysIMPROVEMENT IN LEAD TIME – 4 TIMES

FUTURE ROADMAPAutomating the mechanism for forecasting Channel wise sales trend by identifying the best tool among the several tools by Q1

Automating the process of setting the inventory norm across the supply chain quarterly by Q1

Automating the transaction, which triggers the stock transfer order, work order for style codes and purchase order for fabric codes by Q2

Increasing the Scope of this project to different products and channels

BRAND CHANNEL PRODUCT EXP TIMELP RETAIL S&BLP TRADE S&B Q1LP RETAIL SHIRT Q2LP TRADE SHIRT Q2LP RETAIL TROUSER Q1LP TRADE TROUSER Q1VH RETAIL S&B Q1VH TRADE S&B Q1VH RETAIL SHIRT Q1VH TRADE SHIRT Q1VH RETAIL TROUSER Q2VH TRADE TROUSER Q2

THANK YOU