Madura coats : Supply chain optimisation through order frequency analysis

Presented by – Saurabh Srivastava (16)

PGDM (2010-12)ITM, Warangal.

Coats India-SCM

Coats India is the threads division of Madura Coats Pvt. Ltd.It’s an Indian subsidiary of Coats Ltd.It operates out 65 nations.World largest manufacturer of Industrial sewing threads & consumer needlecraft products.Coats India manufactures & markets a complete range of cotton, synthetic & corespun threads for the Indian & export markets.The threads division is the largest business of Madura Coats, contributing to 91% of the turnover.

Obstacle & recoveryThe enhanced quantities of stocks that used to the fast moving once are dormant now.Previously, Coats India had a SKU range of over 30,000 covering regular colors & customer specials.Additionally, 10 new colors were added everyday to this range.

StrategiesMadura Coats decided to take up the SCM project, which it called “supply Chain Optimization through Order Frequency Analysis”.The Order Frequency Analysis (OFA) project resulted in the following benefits to the organization within a year of complete implementation:Reduction of 14% in finished goods.Reduction of 15% in dormant stocks.Increase from 51% to 77% in the percentage of orders completed in 48 hours.

ORGANIZATION BACKGROUND

•Business span in four segments:-• a) Consumer Threads.• b) Industrial Threads.• c) Exports.• d) Other accessories.•Direct and indirect customers.•Different types of customers.•MTO business.

SCM- THE NEEDQuality of the color.Large number of global buyers.Change in fashion trends.Reduction in volume of garment production.Demand for thread.High cost of production.Judgmental and inaccurate process.

THE PROJECT ARCHITECTUREPROJECT METHODOLOGY

1- SALES DATA FROM EACH LOCATION WAS COMPILED, VALIDATED, AND CLEANSED, TO ISOLATE THE PARAMETERS OF VOLUME, NUMBERO OF CUSTOMERS, AND TIME OF THE ORDER.

2- THE DATA WAS FILTERED USING USING THE ACCOUNTS CODE TO ACCURATELY CAPTURE THE CUSTOMER SPREAD.

3- REGIONS ARE DEFINED ON THE BASIS OF STOCKING LOCATIONS IN THAT GEOGRAPHICAL AREA.

4 - Simulation exercise was done for each stocking locationson the basis of three different criteria –i. Volume ii. Frequency iii. Customer spread. Determination of stock range is done on the basisof these three criteria for each location.5 – Items which met 2 out of the 3 criteria are

studied separately to see if they could be included in the stock range. Items sold to dealers & low risk are identified separately.

6 – A set of inclusions & deletion list is generated to determine the added & deleted stock from the earlier stock range.

7 – A stock report was prepared for each location in the following categories –i. The regional stock range.ii. The dormant.iii. Slow moving stock range.iv. Customer specials.An action plan is drawn for each category.

8 – The sales data is used to predict future sales for the SKU and based on this, a replenishment quantity (ROQ) and a replenishment point (ROP) were set up for the stock replenishment to happen.

OPERATIONAL IMPLEMENTATION For efficiency a codification is used to codify the stock range at depot level & regional level.Sales based replenishment system was set into motion.ROP/ROQ model was developed.Past sales data was used to establish the estimated level of sale for each SKU.Current actual stock was used with ROP/ROQ model to trigger replenishment.OFA run was implemented from both the ends of the supply chain- the manufacturing end and the ‘buy in from the marketing team’.

Contribution of manufacturing end & buy in from the marketing team.

1. Steps are taken to ensure that the production would match the ordered quantity to the extent possible.

2. Developing a solution to the identified dormant stocks by reprocessing them into other saleable products.

3. Stock ranges were implemented with the consultation of the front end sales personnel so that there was a full buy in to the strategy.

THE SUPPLY CHAIN PROJECTBasic tenet is to optimize stocks.Keep production cost low.Deliver best customer service.Objective of ORDER FREQUENCY ANALYSIS –Improve availability & service. Reduce inventory & associated costs.To reduce risk of dormancy.To manufacture cost effectively.To expand capacity at the right place in the right machine configuration.

KEY POINTS IN OFAUsing past order data to determine SKUs.Usage of simplistic volume criteria.Frequency of sale and consumer spread as risk criteria to determine stock range.Stock holding levels were based on frequency of orders received.Categorization of items into stock & MTO.ABC classification to define stock level.Replenishment is triggered by the sales & was tracked on a daily basis.

CAPACITY RESOURCE ALLOCATION

Matched existing capacity with order inflow.Suggested the key areas where capacity addition was required.Gives scientific basis to a high value capital expenditure.Guides the investment decisions accurately.

BENEFITS OF SCM PROJECTFINISHED GOODS STOCK –oReduced 27% from April 2002 to December 2002.o14 % reduction in 2003.o6% reduction in 2004.

DORMANT STOCK – oReduced 62% from April 2002 to December 2002.o51% reduction in 2003.o8% reduction in 2004.

More accurate capacity addition.Yielded better services.Orders –oIncreased by 50% from April 2002 to mid 2004.oOrders completing in 48 hours increased from 51% to 77%. 98% orders were completed within 6 days.

After OFA project –1) finished goods stock reduced 14%.2) Dormant stock reduced 51%.3) Percentage of orders completed in 48 hours

increased from 51% to 77%

IMPACT ON THE ORGANISATIONGrowing trend of factory gate invoicing to customers.Factory warehouses were established to stock and invoice finished goods from there.Reducing stocks at depots considerably.Increased stock range.Improved manufacturing efficiency to a great extent.

Any queries………