1. Supply Chain Management Lecture 14

2. Outline February 25 (Today) –Network design simulation description –Chapter 8 –Homework 4 (short) March 2 –Chapter 8, 9 –Network design simulation due before 5:00pm March 4 –Simulation results –Midterm overview –Homework 4 due March 9 –Midterm

3. Measures of Forecast Error Error measureFormula EtEt Forecast ErrorF t - D t Bias t Bias ∑ t n=1 E t AtAt Absolute Deviation |Et||Et| MAD n Mean absolute deviation (1/n)*∑ n t=1 A t TS t Tracking signalBias t / MAD t MAPE n Mean absolute percentage error (1/n)*∑ n t=1 (A t / D t )*100 MSE n Mean squared error (1/n)*∑ n t=1 E t 2

4. Measures of Forecast Error Error measureDescription EtEt Forecast ErrorForecast – Demand Bias t BiasSum of errors AtAt Absolute DeviationAbsolute error MAD t Mean absolute deviationAverage of absolute error TS t Tracking signalBias t / MAD t MAPE n Mean absolute percentage error Average of absolute percentage error MSE n Mean squared errorAverage of squared error

5. Measures of Forecast Error Error measureDesired outcome / Use EtEt Forecast ErrorClose to zero Bias t BiasClose to zero AtAt Absolute DeviationClose to zero MAD t Mean absolute deviation STDEV(E t )  1.25 MAD t TS t Tracking signalStay within (-6, +6) MAPE n Mean absolute percentage error Stay under 10% (30% not uncommon) MSE n Mean squared error VAR(E t )  MSE t

6. Simulation Assignment (25%) Design the supply chain network for Jacobs Industries on the fictional continent of Pangea –Jacobs only product is an industrial chemical that can be mixed with air to form a foam (used in air conditioner retrofit kits)

7. Demand Demand for Jacob’s product in Pangea –Existing and new markets Air conditioner retrofit kit Hardwood floor laminates Premium home appliances Insulation products

8. Demand Average demand for Jacob’s product in Pangea –Existing and new markets 250

9. Assignment Jacobs management would like to design a supply chain network for Pangea. It’s current network consist of a factory in Calopeia with a capacity of 20. You have been hired to suggest a network design that will maximize profits for Jacobs Industry. Designing such a network is complex and includes the following decisions: –Should the factory in Calopeia be expanded? –Should factories in other regions be built? If so, what should their capacity be? –What regions should each factory serve?

10. Production parameters 20

11. Production parameters A factory must serve the region in which it is located 300

12. Production parameters 20

13. Production parameters You have $20,000,000 to design your network The cost of building a factory is $500,000 regardless of the factory capacity The cost of capacity is $50,000 20 5 500,000 + 5*50,000 = $750,000

14. Production parameters You have $20,000,000 to design your network The cost of building a factory is $500,000 regardless of the factory capacity The cost of capacity is $50,000 40 5 500,000 + 5*50,000 = $750,000 20*50,000 = $1,000,000

15. Transportation parameters Finished drums are shipped from the factory warehouse by mail to the customers Factories may ship to all the regions in Pangea Shipping time is 1 day independent of origin and destination

16. Financial and Other Parameters All customers pay $1450 per drum and the production cost is $1200 per drum The drum must be shipped within 24 hours of receiving the order or the order is lost Orders may be partially filled and one order may be filled from multiple factories Each factory has warehouse space to hold up to 500 finished drums –If warehouse space is used completely, the factory will remain idle until warehouse space becomes available Interest accrues on cash at 10% per year, compounded daily

17. The Goal Your network design will run from day 1 till day 1460 Investment in capital (such as new factories and factory capacity) will become obsolete on day 1460 The winning team is the one with the highest cash position on day 1460

18. From Forecasting to Planning Capacity How should a company best utilize the resources that it has?

19. Aggregate Planning Strategies Basic strategies –Level strategy (using inventory as lever) Synchronize production rate with long term average demand Swim wear –Chase (the demand) strategy (using capacity as lever) Synchronize production rate with demand Fast food restaurants –Time flexibility strategy (using utilization as lever) High levels excess (machine and/or workforce) capacity Machine shops, army –Tailored strategy Combination of the chase, level, and time flexibility strategies

20. Aggregate Planning Aggregate planning involves aggregate decisions rather than stock-keeping unit (SKU)-level decisions for a medium term planning horizon (2-18 months) All-Terrain Vehicle (ATV) Engine Assembly Transmission Model AModel BModel CAutomaticManual

21. Case Study Results In general, the chase strategy is used when –Products are valuable –Products are bulky or hard to store –Products are perishable or carry an appreciable risk of obsolescence –High variety Accurate sales predictions are hard to obtain making stockpiling hazardous Fashion items In general, the level strategy is used when –Operators take a long time to become proficient at critical tasks –Products with negligible probability of obsolescence –Low variety Forecasts are quite good

22. Importance of Aggregate Planning Without a sufficiently long-term view one may make short-term decisions that hurt the organization in the long-term

23. Importance of Aggregate Planning Aggregate planning at Henry Ford Hospital involves matching available capacity, workers, and supplies to a highly variable customer demand pattern

24. Importance of Aggregate Planning Aggregate planning at Henry Ford Hospital involves matching available capacity, workers, and supplies to a highly variable customer demand pattern –903 beds arranged into 30 nursing units –Cost $5,000 of turning away a patient (simple cases) –Cost of one idle 8-bed module is $35,000/month or $420,000/year –High degree of demand variability Demand for beds could change by as many as 16% in less than two weeks

25. Importance of Aggregate Planning Shortly after Henry Ford Hospital reduced staff, it determined the staff was needed –New staff was recruited –Both staff reduction and recruiting costs were incurred Without a sufficiently long-term view one may make short-term decisions that hurt the organization in the long-term

26. Aggregate Planning Aggregate planning –A general plan that determines ideal levels of capacity, production, subcontracting, inventory, stockouts, and even pricing over a specified time horizon (i.e. planning horizon) Production rate (number of units to produce) Workforce (number of workers needed) Overtime (number of overtime hours) Machine capacity level (machine capacity needed) Subcontracting (subcontracted capacity) Backlog (total demand carried over to future periods) Inventory on hand (total inventory carried over to future periods)

27. Generic tool, call it Shovel Example: Aggregate planning at RedTomatoTools RedTomatoTools –A small manufacturer of gardening equipment Shovels Spades Forks

28. Inputs of an Aggregate Plan Demand forecast in each period Production costs –labor costs, regular time ($/hr) and overtime ($/hr) –subcontracting costs ($/hr or $/unit) –cost of changing capacity: hiring or layoff ($/worker) and cost of adding or reducing machine capacity ($/machine) Other costs –Labor/machine hours required per unit –Inventory holding cost ($/unit/period) –Stockout or backlog cost ($/unit/period) Constraints –Limits on overtime, layoffs, capital available, stockouts and backlogs

29. Example: Red Tomato Tools Constraints –Workforce, hiring, and layoff constraints –Capacity constraints –Inventory balance constraints –Overtime limit constraints –Inventory at end of Period 6 is at least 500 –Stockout at end of Period 6 equals 0

30. Example: Red Tomato Tools

31. Average Flow Time Average flow time –Average time one unit spends in inventory Average inventory Throughput Average flow time =

32. Average Inventory Average Inventory = (0.5(I 0 + I 1 ) + 0.5(I 1 + I 2 ) + 0.5(I 2 + I 3 ) + 0.5(I 3 + I 4 ) + 0.5(I 4 + I 5 ) + 0.5(I 5 + I 6 ))/6

33. Average Inventory Average Inventory = (0.5I 0 + 0.5I 1 + 0.5I 1 + 0.5I 2 + 0.5I 2 + 0.5I 3 + 0.5I 3 + 0.5I 4 + 0.5I 4 + 0.5I 5 + 0.5I 5 + 0.5I 6 )/6

34. Average Inventory Average Inventory = (0.5I 0 + 0.5I 6 + I 1 + I 2 + I 3 + I 4 + I 5 )/6 = (0.5(I 0 + I 6 ) + I 1 + I 2 + I 3 + I 4 + I 5 )/6

35. Average Flow Time Little’s Law Average inventory Throughput Average flow time =