Submitted by :- GROUP 15Soham Ranjan

PGP/15/252Mudaliar Ravin MohanPGP/15/292S Hariprasad

PGP/15/314Saurabh Pillai

PGP/15/318

Ski garments and equipment fashion product Short life cycle and high cyclical variance in demand

Very long supply chain cycle 2 years from supplier to customer Plans good at the time of formulation become meaningless by the end of cycle

High uncertainty in demand Both seasonality and random variation Random variation can’t be predicted unlike seasonality, trends, and cycles

Poor forecasting No quantitative techniques usedGreat many SKUs Increase cost and affect profitability

Make planning and forecasting difficult

Long lead times Foster uncertainty, create phase lag and increase risk

Sole market High seasonality, No alternate complimentary channel

Under produce hit products (cash cows) Risk lost sales, lost customer, and permanently damaged image

Over produce undesired products Have to sell at 8% loss

Key issues

04/07/2023 2

1) All Production in Hong KongOrdered quantities

Average Forecast – 2*Standard DeviationMinimum order quantity per style for Hong

Kong is 600Total order quantity should be at least 10,000

units

All Production in Hong Kong

StyleAverage Forecast

Standard Deviation

2*Standard Deviation

Calculated Order

Actual Order (HK)

Gail 1017 194 388 629 629Isis 1042 323 646 396 600

Entice 1358 248 496 862 862Assault 2525 340 680 1845 1845

Teri 1100 381 762 338 600Electra 2150 404 808 1342 1342

Stephanie 1113 524 1048 65 600Seduced 4017 556 1112 2905 2905

Anita 3296 1047 2094 1202 1202Daphne 2383 697 1394 989 989

Total 11574

2) Measure of RiskCoefficient of Variation (CV) can be used as a

measure of riskHigher CV means a more risky proposition

CV = Standard Deviation/Average ForecastThe products with lesser Coefficient of

Variation are at a lower risk than the products with higher Coefficient of Variation

Measure of Risk

“Stephanie” and “Teri” are high risk products“Assault” and “Seduced” are low risk

products

StyleAverage Forecast

Standard Deviation

Coefficient of Variation

Gail 1017 194 0.191Isis 1042 323 0.310

Entice 1358 248 0.183Assault 2525 340 0.135

Teri 1100 381 0.346Electra 2150 404 0.188

Stephanie 1113 524 0.471Seduced 4017 556 0.138

Anita 3296 1047 0.318Daphne 2383 697 0.292

3) All Production in ChinaOrdered quantities

Average Forecast – 2*Standard DeviationMinimum order quantity per style for China is

1200Total order quantity should be at least 10,000

units

All Production in China

StyleAverage Forecast

Standard Deviation

2*Standard Deviation

Calculated Order

Actual Order (Ch)

Actual (Ch) - Calculated

Actual (Ch) - Actual (HK)

Gail 1017 194 388 629 1200 571 571Isis 1042 323 646 396 1200 804 600

Entice 1358 248 496 862 1200 338 338Assault 2525 340 680 1845 1845 0 0

Teri 1100 381 762 338 1200 862 600Electra 2150 404 808 1342 1342 0 0

Stephanie 1113 524 1048 65 1200 1135 600Seduced 4017 556 1112 2905 2905 0 0

Anita 3296 1047 2094 1202 1202 0 0Daphne 2383 697 1394 989 1200 211 211

Total 14494

Sourcing changesLengthy cycle mismatches resource and production peaksMinimum order requirements high Long lead times for key itemsChange order cycle

No prototyping reduced effective lead time Split demand into two

Order basic colors early and fashion specific colors later

Forecasting changesUse previous years’ demand base

Factor in weather forecasts, cyclical (macroeconomic) and seasonal factors

Use EOQ/ hybrid model, use statistical smoothing techniques Base forecast by product line per quarter e.g. Men’s parka,

women’s parka etc

4) Supply chain changes

04/07/2023 9

Manufacturing changesProduce during low volume monthsUse assemble to order technique

Manufacture standard sub assemblies and stock. This will eliminate finished good inventory and decrease order lead time

This is also consistent with decreasing the number of SKUs

Distribution changesShip by A B C rule

A – Ski resorts and ski shops – least risk, high margins ship early B – Sports departmental stores – higher risk ship later C – Discount and retail outlets – highest risk ship out of demand

products

Expand to alternate complimentary channels Target Australia, New Zealand, and South America Southern

hemisphere, will have peak season when demand dries up in US Thus they can avoid selling at loss

Supply chain changes

04/07/2023 10

5) Hong Kong Vs. ChinaLong-term sourcing to China for cost benefits but

not sourcing entirely to China due to quota restrictions in US and the low labour productivity

Short-term increased demand for specific SKU should be sourced to Hong Kong for timely delivery and lower minimum order quantity

Sourcing policy:Continue sourcing in both China and Hong Kong

with more focus on China for cost benefits, sourcing more demand SKU’s to Hong Kong for timely delivery.