Lean Supply Chains: The Foundation 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.

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

Bullwhip Effect 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: excessive inventory investment poor customer service lost revenues misguided capacity planning ineffective transportation Ineffective production schedules.

 The Beer Game 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.  

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

Assumptions 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.

Playing the game 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. In week 5, demand is disrupted to 8 cases a week and remains constant. Each player’s ordering policy is based on two rules

Demand Forecast Rule 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

Order Quantity Rule 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.

week 4:Customer/Retailer/Wholeseller

week 5: Customer/Retailer/Wholeseller 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

week 5: Customer/Retailer/Wholeseller The wholesaler’s order to the distributor increased by 400%. 4  20

week 5: Wholeseller/Didtributor/Factory

The variation doubles at each stage. Retailer Wholesaler Distributor Factory 200% 1,600% 400% 800% 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.

The Implications of Lead Time on the Bullwhip Effect 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 15

The impact of information 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.

The impact of information

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

The Impact of Information on the Bullwhip Effect 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. 19

The Impact of Lead Time on the Bullwhip Effect 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. 20

Structure Drives Behavior: Causes of the Bullwhip Effect 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 21

Other Behaviors that Cause the Bullwhip Effect 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 22

Ways to Mitigate the Bullwhip Effect Reduce lead times Use/sharing of POS data 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 23