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System’s Perspective
 Understand supply chain dynamics and adopt a holistic view.
 Consider the business ecosystem in which you are operating.
 Supply Chain Dynamics
 Enterprises can experience huge variations at each step in the chain, with variations typically more pronounced the further upstream the enterprise is from the ultimate user.

 Results in:
 Larger inventory carrying costs
 Lost sales from stock outs
 Lack of responsiveness to customer demand

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A slight motion of the handle of a bullwhip can make the top thrash wildly at up to 900mph.
Increasing demand variability as you move upstream.
Most demand distortion is caused by the supply chain itself, not by the customer.
Results in:
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 excessive inventory investment poor customer service
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 lost revenues misguided capacity planning ineffective transportation
Ineffective production schedules.

 Underscores the importance of understanding supply chain dynamics and applying systems thinking to coordinate activities within and between enterprises.
 Explains the crucial role lead times play in enhancing or inhibiting competitiveness
 Elaborates on the role of information systems in the lean supply chain.

 Assumes a linear SC, 4 enterprises, one type of beer
Factory Distributor Wholesaler Retailer
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Goal is to manage demand as imposed by it’s customer
Each enterprise has only one manager
Runs for 50 wks.

 Each week, an enterprise receives an order from downstream customers and places an order upstream.
 Two week lead time between when an order is placed and when it is received.
 Another two week lead time before the order is delivered.
 Each enterprise starts with 12 cases of beer.
 At the beginning of each week we know what demand will be.

 Everyone acts in their own self interest on the basis of their own forecasts
 The system is in a steady state with demand at four cases each week.
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In week 5, demand is disrupted to 8 cases a week and remains constant.
E ach player’s ordering policy is based on two rules

The forecast rule: The weekly demand for each of the next four weeks is the average of the weekly demand over the four most recent weeks. Four period moving average: (4+4+4+4)/4=4

Given the forecasts, the amount ordered is just enough to replenish the ending inventory (Four weeks from now-when the order arrives) to a target of 12 cases.
 12+(Forecast demand for next 4 weeks)-
(current inventory)-(Orders already placed for the next three weeks.

Customer and Retailer: Week 4
Forecast Demand: (4+4+4+4)/4 4
Demand (this period) 4
Demand(next 3 periods): 4+4+4 12
Target Safety Stock 12
Order 4
4 Order just received
12 Orders on the way: 4+4+4
12 Inventory on hand
Retailer and Wholeseller: Week 4
Forecast Demand: (4+4+4+4)/4 4
Demand (this period) 4
Demand(next 3 periods): 4+4+4 12
Target Safety Stock 12
Order 4
4 Order just received
12 Orders on the way: 4+4+4
12 Inventory on hand

Customer and Retailer: Week 5
Forecast Demand(4+4+4+8)/4 5
Demand (this period) 8
Demand(next 3 periods): 5+5+5 15
Target Safety Stock 12
Order 12
4 Order just received
12 Orders on the way: 4+4+4
8 Inventory on hand
 Consumer demand increased by 100%
 4  8 cases
 The retailers order to the wholesaler increased by
200%
 4  12 cases
 The retailer doubled the variation in demand

Retailer and Wholeseller: Week 5
Forecast Demand (4+4+4+12)/4 6
Demand (this period) 12
Demand(next 3 periods): 6+6+6 18
Target Safety Stock 12
Order 20
4 Order just received
12 Orders on the way: 4+4+4
4 Inventory on hand
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The wholesaler’s order to the distributor increased by
400%.
 4  20

Wholeseller and Distributor: Week 5
Forecast Demand (4+4+4+20)/4 8
Demand (this period) 20
Demand(next 3 periods): 8+8+8 24
Target Safety Stock 12
Order 36
4 Order just received
12 Orders on the way: 4+4+4
-4 Inventory on hand
Distributor and Factory: Week 5
Forecast Demand (4+4+4+36)/4 12
Demand (this period) 36 4 Order just received
Demand(next 3 periods): 12+12+12 36 12 Orders on the way: 4+4+4
Target Safety Stock 12 -20 Inventory on hand
Order 68

Retailer
200%
Wholesaler
400%
Distributor
800%
Factory
1,600%
 The variation doubles at each stage.
 However, of the 64-case increase in the factory's orders, only four cases were directly attributable to a change in consumer demand.
 The lead times present in this value stream created
94 percent of the variation observed in the factory’s orders.

Retailers
Warehouses/
Distributors
Manufacturers
 Lead times significantly exacerbate the bullwhip effect
 Reducing lead time, in combination with improved visibility along the supply chain, can significantly and positively relieve the bullwhip effect

 Assume all of the same factors except that each stage is aware of the customer’s orders.
 Assume we know that demand for week six and onward is five cases.
 Following exactly the same steps.

Forecast Demand: (4+4+4+8)/4 5
Demand (this period) 8
Demand(next 3 periods):5+5+5 15
Target Safety Stock 12
Order 12
4 Order just received
12 Orders on the way:4+4+4
8 Inventory on hand
Forecast Demand 5
Demand (this period) 12
Demand(next 3 periods):5+5+5 15
Target Safety Stock 12
Order 16
4 Order just received
12 Orders on the way:4+4+4
4 Inventory on hand
Forecast Demand 5
Demand (this period) 16
Demand(next 3 periods):5+5+5 15
Target Safety Stock 12
Order 20
Forecast Demand 5
Demand (this period) 20
Demand(next 3 periods):5+5+5 15
Target Safety Stock 12
Order 24
4 Order just received
12 Orders on the way:4+4+4
0 Inventory on hand
4 Order just received
12 Orders on the way:4+4+4
-4 Inventory on hand

Retailer
Wholesaler
Distributor
Retailer orders 12 cases- a 200% increase
Wholesaler orders 16 cases- a 300% increase
Distributor orders 20 cases- a 400% increase
Manufacturer
Manufacturer order Raw Materials to make
24 cases- a 500% increase

 Perfect forecasting does not eliminate the bullwhip effect
 Lesson: The bullwhip effect is present even if there is perfect information about the future that is shared among all channel partners.

 Lead times can multiply the variation in demand and so everyone in the supply chain should be working to reduce lead times.
 The implications of Little's Law are that when inventory in the supply chain is high, lead times increase, and, conversely, longer lead times result in more inventories in the pipeline.
 This problematic and cyclical relationship between lead times and inventory is a powerful reason for reducing lead times.

 Lack of visibility
 Long lead time
 Many stages in the supply chain
 Lack of pull signals
 Order batching
 Price discount and promotions
 Forward buying
 Rationing

 Over-reaction to backlogs
 Neglecting to order to reduce inventory
 Hoarding customers
 Shortage gaming for customers
 Demand forecast inaccuracies
 Attempts to meet end-of-month metrics

 Reduce lead times
 Use/sharing of POS data
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Smaller orders
 Work with suppliers on more frequent deliveries of smaller order increments
Use stable pricing, “everyday low prices”
 Levels out customer demand
 Allocation based on past sales