1. Andy Guo Planning Demand and Supply in a Supply Chain 第二單元 (3) ： Planning Demand and Supply in a Supply Chain 郭瑞祥教授 【本著作除另有註明外，採取創用 CC 「姓名標示 －非商業性－相同方式分享」台灣 3.0 版授權釋出】創用 CC 「姓名標示 －非商業性－相同方式分享」台灣 3.0 版 1

2. Andy Guo Outline ►Part I: Aggregate planning ►Part II: Managing predictable variability 2

3. Andy Guo Aggregate Planning ►A►A process by which a company determines levels of capacity, production, subcontracting, inventory, stockouts, and pricing to maximize the firm’s profit over the planning horizon (3-18 months) given the demand forecast for each period. ►F►Focus on aggregate decisions rather than SKU level decisions. ►I►Identify operational parameters: –Production rate –Workforce –Overtime –Machine capacity level –Subcontracting –Backlog –Inventory on hand 3

4. Andy Guo Information Required for Aggregate Planning ►D►Demand forecast for each period in the planning horizon ►P►Production costs ►L►Labor/machine hours required per unit ►I►Inventory holding cost ►S►Stockout or backlog cost ►C►Constraints: limits on overtime, layoffs, capital, stockouts/backlogs –Labor costs: regular time and overtime costs –Subcontracting cost –Cost of changing capacity: hiring/laying off labor, machine capacity change 4

5. Andy Guo Aggregate Planning ►Production quantity from regular time, overtime, and subcontracted time ►Inventory held ►Backlog/stockout quantity ►Workforce hired/laid off ►Machine capacity increase/decrease ►Capacity (regular time, overtime, subcontracted) ►Inventory ►Backlog/lost sales Determinations Tradeoffs 5

6. Andy Guo Basic Strategy ►Use capacity as the lever ►Production rate synchronized with demand rate by varying capacity of employee and machine ►Result in low inventory and high level of change in capacity and workforce ►Used when the cost of carrying inventory is very expensive and cost to change levels of capacity and workforce are low Chase Strategy 6

7. Andy Guo Basic Strategy Time Flexibility from Workforce or Capacity Strategy ►Use utilization as the lever ►Workforce is kept stable but the number of hours worked is varied over time ►Result in low inventory and lower average utilization ►Used when inventory carrying cost are high and capacity is inexpensive 7

8. Andy Guo Basic Strategy ►Use inventory as the lever ►Stable machine capacity and workforce are maintained with a constant output rate ►Result in large inventory and backlogs ►Used when inventory carrying costs and backlog costs are low Level Strategy 8

9. Andy Guo Scenario 1: Aggregate Planning at Red Tomato Tools MonthDemand Forecast January1,600 February3,000 March3,200 April3,800 May2,200 June2,200 Microsoft Office 2010 多媒體藝廊 9

10. Andy Guo Costs for Red Tomato ItemCost Material cost$10/unit Inventory holding cost$2/unit/month Marginal cost of stockout/backlog$5/unit/month Hiring and training costs$300/worker Layoff cost$500/worker Labor hours required4/unit Regular time cost$4/hour Overtime cost$6/hour Cost of subcontracting$30/unit 10

11. Andy Guo Red Tomato ►S►Sell gardening tool which is highly seasonal –P–Peak in spring –M–Main capacity is “size of workforce” ►S►Sell each tool at $40 ►S►Starting inventory in January is 1000 tools ►S►Starting employees in January is 80 persons ►T►The plant has a total of 20 working days/month and 8 regular hours/day ►E►Ending inventory is 500 ►A►All demand must be satisfied; no stock out in the last period 11

12. Andy Guo Costs for Red Tomato ItemCost Material cost$10/unit Inventory holding cost$2/unit/month Marginal cost of stockout/backlog$5/unit/month Hiring and training costs$300/worker Layoff cost$500/worker Labor hours required4/unit Regular time cost$4/hour Overtime cost$6/hour Cost of subcontracting$30/unit 12

13. Andy Guo Aggregate Planning Model W t = Workforce size for month t, t = 1,...,6 H t = Number of employees hired at the beginning of month t, t = 1,...,6 L t = Number of employees laid off at the beginning of month t, t = 1,...,6 P t = Production in month t, t = 1,...,6 I t = Inventory at the end of month t, t = 1,...,6 S t = Number of units stocked out/backlogged at the end of month t, t = 1,...,6 C t = Number of units subcontracted for month t, t = 1,...,6 O t = Number of overtime hours worked in month t, t = 1,...,6 Define Decision Variables 13

14. Andy Guo Define Objective Function Regular time labor cost Overtime labor cost Cost of hiring and layoffs Cost of inventory and stockout Cost of materials and subcontracting Regular time labor cost Overtime labor cost Cost of hiring and layoffs Cost of inventory and stockout Regular time labor cost = 4/hr * 8 hr/day * 20 day/month = 640 Since all demands is met, revenue is fixed maximizing profit = minimizing cost 14

15. Andy Guo ►W►Workforce size for each month is based on hiring and layoffs ►P►Production for each month cannot exceed capacity ►I►Inventory balance for each month ►O►Overtime limit for each month Define Constraints 15

16. Andy Guo ►Workforce size for each month is based on hiring and layoffs ►Production for each month cannot exceed capacity ►Inventory balance for each month ►Overtime limit for each month Define Constraints 20*8=160 hrs 4 hours/unit 160 4 16

17. Andy Guo ►W►Workforce size for each month is based on hiring and layoffs ►P►Production for each month cannot exceed capacity ►I►Inventory balance for each month ►O►Overtime limit for each month Define Constraints Net supply in current period Net supply in previous period SupplyDemand 17

18. Andy Guo ►W►Workforce size for each month is based on hiring and layoffs ►P►Production for each month cannot exceed capacity ►I►Inventory balance for each month ►O►Overtime limit for each month Define Constraints 18

19. Andy Guo Aggregate Planning Model W t = Workforce size for month t, t = 1,...,6 H t = Number of employees hired at the beginning of month t, t = 1,...,6 L t = Number of employees laid off at the beginning of month t, t = 1,...,6 P t = Production in month t, t = 1,...,6 I t = Inventory at the end of month t, t = 1,...,6 S t = Number of units stocked out/backlogged at the end of month t, t = 1,...,6 C t = Number of units subcontracted for month t, t = 1,...,6 O t = Number of overtime hours worked in month t, t = 1,...,6 Define Decision Variables 19

20. Andy Guo Defining Constraints 160 4 20*8=160 hrs 4 hours/unit Net supply in current period Net supply in previous period SupplyDemand 20

21. Andy Guo Evaluation of Performance Little’s law: average flow time = average inventory / throughput ►A►Average inventory = ►A►Average flow time = 21

22. Andy Guo Evaluation of Performance Little’s law: average flow time = average inventory / throughput ►A►Average inventory = ►A►Average flow time = 22

23. Andy Guo EXCEL-DEMO W t = Workforce size for month t, t = 1,...,6 H t = Number of employees hired at the beginning of month t, t = 1,...,6 L t = Number of employees laid off at the beginning of month t, t = 1,...,6 P t = Production in month t, t = 1,...,6 I t = Inventory at the end of month t, t = 1,...,6 S t = Number of units stocked out/backlogged at the end of month t, t = 1,...,6 C t = Number of units subcontracted for month t, t = 1,...,6 O t = Number of overtime hours worked in month t, t = 1,...,6 23

24. Andy Guo EXCEL-DEMO 300 X B5 24

25. Andy Guo EXCEL-DEMO2 Define Objective Function 25

26. Andy Guo EXCEL-DEMO3 cost Decision Variables 26

27. Andy Guo EXCEL-DEMO4 Define Objective Function 27

28. Andy Guo EXCEL-DEMO5 28

29. Andy Guo EXCEL-DEMO6 29

30. Andy Guo ►Workforce size for each month is based on hiring and layoffs ►Production for each month cannot exceed capacity ►Inventory balance for each month ►Overtime limit for each month Define Constraints 30

31. Andy Guo EXCEL-DEMO7 31

32. Andy Guo Optimal Aggregate Plan for Scenario 1 Period t No. Hired H t No. Laid Off L t Workforce Size W t Overtime O t Inventory I t Stockout S t Subcontract C t Total Production P t 0008001,00000 10156501,983002,583 2006501,567002,583 300650950002,583 400650026702,583 500650117002,583 600650500002,583 ►Total cost over planning horizon = $422,275 ►Revenue over planning horizon = 40  16,000 = $640,000 ►Average seasonal inventory = 895 ►Average flow time = 895 / 2,667 = 0.34 months 32

33. Andy Guo Regular time labor cost Overtime labor cost Cost of hiring and layoffs Cost of inventory and stockout Cost of materials and subcontracting Define Objective Function 33

34. Andy Guo ►Workforce size for each month is based on hiring and layoffs ►Production for each month cannot exceed capacity ►Inventory balance for each month ►Overtime limit for each month Define Constraints 34

35. Andy Guo Optimal Aggregate Plan for Scenario 1 Perio d t No. Hired H t No. Laid Off L t Workforc e Size W t Overtim e O t Inventor y I t Stocko ut S t Subcontr act C t Total Producti on P t 0008001,00000 10156501,983002,583 2006501,567002,583 300650950002,583 400650026702,583 500650117002,583 600650500002,583 ►T►Total cost over planning horizon = $422,275 ►R►Revenue over planning horizon = 40  16,000 = $640,000 ►A►Average seasonal inventory = 895 ►A►Average flow time = 895 / 2,667 = 0.34 months 35

36. Andy Guo Scenario 2: Increased Demand Fluctuation The same overall demand (16,000 units) as scenario 1 MonthDemand Forecast January1,000 February3,000 March3,800 April4,800 May2,000 June1,400 Microsoft Office 2010 多媒體藝廊 36

37. Andy Guo Optimal Aggregate Plan for Scenario 2 Peri od t No. Hired H t No. Laid Off L t Workfo rce Size W t Overti me O t Invento ry I t Stock out S t Subcont ract C t Total Produc tion P t 0008001,00000 10156502,58300 2006502,167002,583 300650950002,583 40065001,26702,583 500650068302,583 600650500002,583 ►T►Total cost over planning horizon is higher = $432,858 ►A►Average seasonal inventory = 1,075 ►A►Average flow time = 1,075 / 2,667 = 0.40 months ►I►Inventories and stockouts go up compared with the plan for scenario 1 37

38. Andy Guo Optimal Aggregate Plan for Scenario 3 Perio d t No. Hired H t No. Laid Off L t Workfor ce Size W t Overtim e O t Inventor y I t Stocko ut S t Subcontr act C t Total Producti on P t 0008001,00000 10235701,667002,267 200570933002,267 3005700002,267 4005700671,4672,267 5005700002,267 60057050004332,267 ►S►Suppose holding cost is increased from $2 to $6 compared to scenario 1 ►T►Total cost over planning horizon is higher = $441,200 ►A►Average seasonal inventory = 558 ►A►Average flow time = 558 / 2,667 = 0.21 months ►I►Inventories carried is reduced while subcontracted amount is increased compared with the plan for scenario 1 38

39. Andy Guo Handle Forecast Error in Aggregate Plans ►Use safety stock or safety capacity –Use overtime (safety capacity) –Carry extra workforce (safety capacity) –Use subcontractors (safety capacity) –Build and carry extra inventory (safety inventory) –Purchase capacity or product from open market (safety capacity) 39

40. Andy Guo Outline ►Part I: Aggregate planning ►Part II: Managing predictable variability 40

41. Andy Guo Managing Predictable Variability - Managing Supply - ►Managing capacity –Time flexibility from workforce –Use of seasonal workforce –Use of subcontracting –Use of dual facilities – dedicated and flexible –Designing product flexibility into the production processes ►Managing inventory –Using common components across multiple products –Building inventory of high demand or predictable demand products 41

42. Andy Guo Managing Predictable Variability - Managing Demand - ►Demand can be influenced using pricing and other forms of promotions. ►Four key factors influence the timing of a trade promotion: ►Demand increase from promotion results from three factors: –Market growth –Stealing market share –Forward buying –Impact of the promotion on demand –Product margins –Cost of holding inventory –Cost of changing capacity 42

43. Andy Guo Scenario 4: Aggregate Planning and Promotion at Red Tomato ►Discounting a unit from $40 to $39 results in the period demand’s increasing by 10 percent because of increased consumption or substitution. Further, 20 percent of each of the two following months demand is moved forward. ►Consider the discount offering in off-peak month of January. The demand forecast is shown below: MonthDemand Forecast January3,000 February2,400 March2,560 April3,800 May2,200 June2,200 43

44. Andy Guo Optimal Aggregate Plan for Scenario 4 Perio d t No. Hired H t No. Laid Off L t Workfor ce Size W t Overtim e O t Inventor y I t Stocko ut S t Subcontr act C t Total Producti on P t 0008001,00000 1015650610002,610 200650820002,610 300650870002,610 400650032002,610 50065090002,610 600650500002,610 ►Total cost over planning horizon = $421,915 ►Revenue over planning horizon = $643,400 ►Profit over planning horizon = $221,485 44

45. Andy Guo Scenario 5: Aggregate Planning and Promotion at Red Tomato Demand fluctuation has increased relative to the profile in scenario 1. ►Discounting a unit from $40 to $39 results in the period demand’s increasing by 10 percent because of increased consumption or substitution. Further, 20 percent of each of the two following months demand is moved forward. ►Consider the discount offering in peak month of April. The demand forecast is shown below: MonthDemand Forecast January1,600 February3,000 March3,200 April5,060 May1,760 June1,760 45

46. Andy Guo Optimal Aggregate Plan for Scenario 5 Peri od t No. Hired H t No. Laid Off L t Workfo rce Size W t Overti me O t Invento ry I t Stock out S t Subcont ract C t Total Produc tion P t 0008001,00000 10146602,047002,647 2006601,693002,647 3006601,140002,647 40066001,27302,647 500660038702,647 600660500002,647 ►Total cost over planning horizon = $438,857 ►Revenue over planning horizon = $650,140 ►Profit over planning horizon = $211,283 46

47. Andy Guo Conclusions based on Scenarios 1, 4 & 5 ►A price promotion in January (scenario 4) results in a higher profit than no promotion (scenario 1). A promotion in April (scenario 5) results in a lower profit than no promotion (scenario 1). ►Even though revenues are higher when promotions is offered in April, the increase in operating costs makes it a less profitable option. ►Red Tomato should offer the discount in the off-peak month of January. ►The above conclusions could be different if Red Tomato were in a situation in which most of the demand increase comes from market growth or stealing market share rather than forward buying (see scenarios 6 & 7) ►It is not appropriate for a firm to leave pricing decisions solely in the domain of marketing and aggregate planning solely in the domain of operations. It is crucial that forecasts, pricing, and aggregate planning be coordinated in the supply chain. 47

48. Andy Guo Scenario 6: Aggregate Planning and Promotion at Red Tomato ►Discounting a unit from $40 to $39 results in the period demand’s increasing by 100 percent because of increased consumption or substitution. Further, 20 percent of each of the two following months demand is moved forward. ►Consider the discount offering in off-peak month of January. The demand forecast is shown below: MonthDemand Forecast January4,440 February2,400 March2,560 April3,800 May2,200 June2,200 48

49. Andy Guo Optimal Aggregate Plan for Scenario 6 Peri od t No. Hired H t No. Laid Off L t Workfo rce Size W t Overti me O t Invento ry I t Stock out S t Subcont ract C t Total Produc tion P t 0008001,00000 100800024003,200 2011690140002,780 300690360002,780 400690066002,780 50069008002,780 600690500002,780 ►Total cost over planning horizon = $456,750 ►Revenue over planning horizon = $699,560 ►Profit over planning horizon = $242,810 49

50. Andy Guo Scenario 7: Aggregate Planning and Promotion at Red Tomato Demand fluctuation has increased relative to the profile in scenario 1. ►Discounting a unit from $40 to $39 results in the period demand’s increasing by 100 percent because of increased consumption or substitution. Further, 20 percent of each of the two following months demand is moved forward. ►Consider the discount offering in peak month of April. The demand forecast is shown below: MonthDemand Forecast January1,600 February3,000 March3,200 April8,480 May1,760 June1,760 50

51. Andy Guo Optimal Aggregate Plan for Scenario 7 Period t No. Hired H t No. Laid Off L t Workfor ce Size W t Overtim e O t Inventor y I t Stocko ut S t Subcon tract C t Total Production P t 0008001,00000 1008002,600003,200 2008002,800003,200 3008002,800003,200 40080002,3801003,200 500800094003,200 600800500003,200 ►Total cost over planning horizon = $536,200 ►Revenue over planning horizon = $783,520 ►Profit over planning horizon = $247,320 ►When forward buying is a small part of the increase in demand from discounting, Red Tomato should offer the discount in the peak demand month of April. 51

52. Andy Guo Performance Under Different Scenarios Regular Price Promotion Price Promotion Period Percent Increase in Demand Percent Forward Buy ProfitAverage Inventory $40 NA $217,725895 $40$39January20 % $221,485523 $40$39April20% $211,283938 $40$39January100%20%$242,810208 $40$39April100%20%$247,3201,492 $31 NA $73,725895 $31$30January100%20%$84,410208 $31$30April100%20%$69,1201,492 52

53. Andy Guo Conclusions Regarding Promotions ►Pricing and aggregate planning must be done jointly. ►Average inventory increases if a promotion is run during the peak period and decreases if run during off-peak period. ►Promotion during the peak period may decrease overall profitability if a significant fraction of the demand increase results from a forward buy. ►Promotion during the peak period may increase overall profitability if forward buying becomes a smaller fraction of the demand increase. ►As product margin declines, promotion during the peak period becomes less profitable. 53

54. Andy Guo Summary of Impact on Promotion Timing FactorFavored timing High forward buyingLow demand period High stealing market shareHigh demand period High growth of marketHigh demand period High marginHigh demand period Low marginLow demand period High holding costsLow demand period High cost of changing capacityLow demand period 54

55. Andy Guo 頁碼作品授權條件作者 / 來源 9, 36 本作品轉載自 Microsoft Office 2007 多媒體藝廊，依據 Microsoft 服務合約及著 作權法第 46 、 50 、 52 、 65 條合理使用。 Microsoft 服務合約 版權聲明 55