Supply Chain Management

Sources: plants vendors ports Regional Warehouses: stocking points Field Warehouses: stocking points Customers, demand centers sinks Supply Production/ purchase costs Inventory & warehousing costs Transportation costs Inventory & warehousing costs Transportation costs

Inventory    Where do we hold inventory?

   Suppliers and manufacturers warehouses and distribution centers retailers Types of Inventory  WIP   raw materials finished goods Why do we hold inventory?

  Economies of scale Uncertainty in supply and demand

Understanding Inventory

 The inventory policy is affected by:   Demand Characteristics Lead Time    Number of Products Objectives   Service level Minimize costs Cost Structure

Cost Structure   Order costs   Fixed Variable Holding Costs   Insurance Maintenance and Handling    Taxes Opportunity Costs Obsolescence

EOQ: A Simple Model*   Book Store Mug Sales  Demand is constant, at 20 units a week    Fixed order cost of $12.00, no lead time Holding cost of 25% of inventory value annually Mugs cost $1.00, sell for $5.00

Question

 How many, when to order?

EOQ: A View of Inventory* Inventory Note: • No Stockouts • Order when no inventory • Order Size determines policy Order Size Avg. Inven Time

EOQ: Calculating Total Cost*     Purchase Cost Constant Holding Cost: (Avg. Inven) * (Holding Cost) Ordering (Setup Cost): Number of Orders * Order Cost Goal: Find the Order Quantity that Minimizes These Costs:

EOQ:Total Cost* 160 140 120 100 80 60 40 20 0 0 Total Cost Holding Cost Order Cost 500 1000

Order Quantity

1500

EOQ: Optimal Order Quantity*  Optimal Quantity = (2*Demand*Setup Cost)/holding cost  So for our problem, the optimal quantity is 316

EOQ: Important Observations*   Tradeoff between set-up costs and holding costs when determining order quantity. In fact, we order so that these costs are equal per unit time Total Cost is not particularly sensitive to the optimal order quantity Order Quantity 50% Cost Increase 80% 90% 100% 110% 120% 150% 200% 125% 103% 101% 100% 101% 102% 108% 125%

The Effect of Demand Uncertainty  Most companies treat the world as if it were predictable:  Production and inventory planning are based on forecasts of demand made far in advance of the selling season  Companies are aware of demand uncertainty when they create a forecast, but they design their planning process as if the forecast truly represents reality

Demand Forecast



The three principles of all forecasting techniques:

   Forecasting is always wrong The longer the forecast horizon the worst is the forecast Aggregate forecasts are more accurate

The Effect of Demand Uncertainty   Most companies treat the world as if it were predictable:   Production and inventory planning are based on forecasts of demand made far in advance of the selling season Companies are aware of demand uncertainty when they create a forecast, but they design their planning process as if the forecast truly represents reality Recent technological advances have increased the level of demand uncertainty:   Short product life cycles Increasing product variety

SnowTime Sporting Goods   Fashion items have short life cycles, high variety of competitors SnowTime Sporting Goods  New designs are completed    One production opportunity Based on past sales, knowledge of the industry, and economic conditions, the marketing department has a probabilistic forecast The forecast averages about 13,000, but there is a chance that demand will be greater or less than this.

SnowTime Demand Scenarios Demand Scenarios 30% 25% 20% 15% 10% 5% 0% 80 00 10 00 0 12 00 0 14 00 0 Sales 16 00 0 18 00 0

SnowTime Costs      Production cost per unit (C): $80 Selling price per unit (S): $125 Salvage value per unit (V): $20 Fixed production cost (F): $100,000 Q is production quantity, D demand  Profit =

Revenue - Variable Cost - Fixed Cost + Salvage

SnowTime Best Solution   Find order quantity that maximizes weighted average profit.

Question: Will this quantity be less than, equal to, or greater than average demand?

    What to Make?

Question: Will this quantity be less than, equal to, or greater than average demand?

Average demand is 13,100 Look at marginal cost Vs. marginal profit  if extra jacket sold, profit is 125-80 = 45  if not sold, cost is 80-20 = 60 So we will make less than average

  SnowTime Scenarios Scenario One:  Suppose you make 12,000 jackets and demand ends up being 13,000 jackets.

 Profit = 125(12,000) - 80(12,000) - 100,000 = $440,000 Scenario Two:   Suppose you make 12,000 jackets and demand ends up being 11,000 jackets.

Profit = 125(11,000) - 80(12,000) - 100,000 + 20(1000) = $

335,000

SnowTime Expected Profit $400,000 $300,000 $200,000 $100,000 $0 8000

Expected Profit

12000 16000

Order Quantity

20000

SnowTime Expected Profit $400,000 $300,000 $200,000 $100,000 $0 8000

Expected Profit

12000 16000

Order Quantity

20000

SnowTime Expected Profit $400,000 $300,000 $200,000 $100,000 $0 8000

Expected Profit

12000 16000

Order Quantity

20000

SnowTime:

Important Observations    Tradeoff between ordering enough to meet demand and ordering too much Several quantities have the same average profit Average profit does not tell the whole story  Question: 9000 and 16000 units lead to about the same average profit, so which do we prefer?

Probability of Outcomes 100% 80% 60% 40% 20% 0% -3 00 00 0 -1 00 00 0 100000 300000 500000

Cost

Q=9000 Q=16000

Key Points from this Model     The optimal order quantity is not necessarily equal to average forecast demand The optimal quantity depends on the relationship between marginal profit and marginal cost As order quantity increases, average profit first increases and then decreases As production quantity increases, risk increases. In other words, the probability of large gains

and

of large losses increases

Sequential Optimization vs. Global Optimization Sequential Optimization

Procurement Planning Manufacturing Planning

Global Optimization

Distribution Planning Demand Planning Supply Contracts/Collaboration/Information Systems and DSS Procurement Planning Manufacturing Planning Distribution Planning Demand Planning

Supply Contract – Example



The Gigantic Pocket Monster (Gipokmon) is a new toy that Mattel has introduced.



Mattel currently allows toy retailers to place an order in August for delivery in November for the holiday season.

Example – Cost and Demand



It costs Mattel $1.50 to manufacture and ship each Gipokmon.

  

Mattel charges a wholesale price of $10. The Toys ‘R’ Us manager plans to sell the toy for $20.

Demand   11000 units (40%) 8000 units (60%)

Question  

How many Gipokmons should the manager at Toy “R” Us order?

How much profit does Toys “R” Us expect to make as a result?

Maximize Expected Profit   8000  X  11000 Expected Profit: 0.4*(20*X-10*X) +0.6*(20*8000-10*X) = - 2 X +96000  Best X = 8000

Resulted Profit 

How much profit does Toys “R” Us expect to make as a result?

-2 * 8000 + 96000 = 80000



How much will Mattel make as a result?

10*8000 – 1.5*8000 = 68000

Buy Back   Suppose Mattel buys back for $4 per unit. Expected Profit of Toy ‘R’ Us: 0.4*(20*X-10*X) +0.6*[20*8000-10*X+4*(X-8000)] = 0.4 X +76800  Best X = 11000

Resulted Profit – Buy Back 

How much profit does Toys “R” Us expect to make as a result?

0.4 * 11000 + 76800 = 81200



How much does Mattel expect to make as a result?

0.4 *[10*11000 – 1.5*11000] +0.6 *[10*11000 – 1.5*11000 – 4*3000] = 86300

General Demand Distribution D

General Demand Distribution

General Demand Distribution

General Demand Distribution

General Demand Distribution

General Demand Distribution