1. Supply Chain Management

2. First appearance – Financial Times Importance - → Inventory ~ 14% of GDP → GDP ~ $12 trillion → Warehousing/Trans ~ 9% of GDP → Rule of Thumb - $12 increase in sales to = $1 savings in Supply Chain 1982 Peter Drucker – last frontier Supply Chain problems can cause ≤ 11% drop in stock price Customer perception of company

3. SCOR Reference: www.supply-chain.org

4. Supply Chain All activities associated with the flow and transformation of goods and services from raw materials to the end user, the customer All activities associated with the flow and transformation of goods and services from raw materials to the end user, the customer A sequence of business activities from suppliers through customers that provide the products, services, and information to achieve customer satisfaction A sequence of business activities from suppliers through customers that provide the products, services, and information to achieve customer satisfaction

5. Supply Chain “The global network used to deliver products and services from raw materials to end customers through an engineered flow of information, physical distribution, and cash.” APICS Dictionary, 10th ed.

6. Supply Chain Management Synchronization of activities required to achieve maximum competitive benefits Synchronization of activities required to achieve maximum competitive benefits Coordination, cooperation, and communication Coordination, cooperation, and communication Rapid flow of information Rapid flow of information Vertical integration Vertical integration

7. Supply Chain Uncertainty Forecasting, lead times, batch ordering, price fluctuations, and inflated orders contribute to variability Forecasting, lead times, batch ordering, price fluctuations, and inflated orders contribute to variability Inventory is a form of insurance Inventory is a form of insurance Distorted information is one of the main causes of uncertainty Bullwhip effect Distorted information is one of the main causes of uncertainty Bullwhip effect

8. Information in the Supply Chain Centralized coordination of information flows Centralized coordination of information flows Integration of transportation, distribution, ordering, and production Integration of transportation, distribution, ordering, and production Direct access to domestic and global transportation and distribution channels Direct access to domestic and global transportation and distribution channels Locating and tracking the movement of every item in the supply chain - RFID Locating and tracking the movement of every item in the supply chain - RFID

9. Information in the Supply Chain Consolidation of purchasing from all suppliers Consolidation of purchasing from all suppliers Intercompany and intracompany information access Intercompany and intracompany information access Electronic Data Interchange Electronic Data Interchange Data acquisition at the point of origin and point of sale Data acquisition at the point of origin and point of sale Instantaneous updating of inventory levels Instantaneous updating of inventory levels Visibility Visibility

10. Electronic Business Replacement of physical processes with electronic ones Replacement of physical processes with electronic ones Cost and price reductions Cost and price reductions Reduction or elimination of intermediaries Reduction or elimination of intermediaries Shortening transaction times for ordering and delivery Shortening transaction times for ordering and delivery Wider presence and increased visibility Wider presence and increased visibility In Theory:

11. Electronic Business Greater choices and more information for customers Greater choices and more information for customers Improved service Improved service Collection and analysis of customer data and preferences Collection and analysis of customer data and preferences Virtual companies with lower prices Virtual companies with lower prices Leveling the playing field for smaller companies Leveling the playing field for smaller companies Gain global access to markets & customers Gain global access to markets & customers

12. Electronic Data Interchange Computer-to-computer exchange of business documents in a standard format Computer-to-computer exchange of business documents in a standard format Quick access, better customer service, less paperwork, better communication, increased productivity, improved tracing and expediting, improves billing and cost efficiency Quick access, better customer service, less paperwork, better communication, increased productivity, improved tracing and expediting, improves billing and cost efficiency

13. Bar Codes Computer readable codes attached to items flowing through the supply chain Computer readable codes attached to items flowing through the supply chain Generates point-of-sale data which is useful for determining sales trends, ordering, production scheduling, and deliver plans Generates point-of-sale data which is useful for determining sales trends, ordering, production scheduling, and deliver plans 1234 5678

14. IT Issues Increased benefits and sophistication come with increased costs Increased benefits and sophistication come with increased costs Efficient web sites do not necessarily mean the rest of the supply chain will be as efficient Efficient web sites do not necessarily mean the rest of the supply chain will be as efficient Security problems are very real – camera phones, cell phones, thumb drives Security problems are very real – camera phones, cell phones, thumb drives Collaboration and trust are important elements that may be new to business relationships Collaboration and trust are important elements that may be new to business relationships

15. Suppliers Purchased materials account for about half of manufacturing costs Purchased materials account for about half of manufacturing costs Materials, parts, and service must be delivered on time, of high quality, and low cost Materials, parts, and service must be delivered on time, of high quality, and low cost Suppliers should be integrated into their customers’ supply chains Suppliers should be integrated into their customers’ supply chains Partnerships should be established Partnerships should be established On-demand delivery (JIT) is a frequent requirement - what is JIT and does it work? On-demand delivery (JIT) is a frequent requirement - what is JIT and does it work?

16. Sourcing Relationship between customers and suppliers focuses on collaboration and cooperation Relationship between customers and suppliers focuses on collaboration and cooperation Outsourcing has become a long-term strategic decision Outsourcing has become a long-term strategic decision Organizations focus on core competencies Organizations focus on core competencies Single-sourcing is increasingly a part of supplier relations Single-sourcing is increasingly a part of supplier relations How does single source differ from sole source?

17. E-Procurement Business-to-business commerce conducted on the Internet Business-to-business commerce conducted on the Internet Benefits include lower transaction costs, lower prices, reduce clerical labor costs, and faster ordering and delivery times Benefits include lower transaction costs, lower prices, reduce clerical labor costs, and faster ordering and delivery times Currently used more for indirect goods Currently used more for indirect goods E-Marketplaces service industry-specific companies and suppliers E-Marketplaces service industry-specific companies and suppliers

18. Distribution The actual movement of products and materials between locations The actual movement of products and materials between locations Handling of materials and products at receiving docks, storing products, packaging, and shipping Handling of materials and products at receiving docks, storing products, packaging, and shipping Often called logistics Often called logistics Driving force today is speed Driving force today is speed Particularly important for Internet dot-coms Particularly important for Internet dot-coms

19. Distribution Centers and Warehousing DCs are some of the largest business facilities in the United States DCs are some of the largest business facilities in the United States Trend is for more frequent orders in smaller quantities Trend is for more frequent orders in smaller quantities Flow-through facilities and automated material handling Flow-through facilities and automated material handling Final assembly and product configuration (postponement) may be done at the DC Final assembly and product configuration (postponement) may be done at the DC

20. Warehouse Management Systems Highly automated systems Highly automated systems A good system will control item slotting, pick lists, packing, and shipping A good system will control item slotting, pick lists, packing, and shipping Most newer systems include transportation management (load management/configuration), order management, yard management, labor management, warehouse optimization Most newer systems include transportation management (load management/configuration), order management, yard management, labor management, warehouse optimization

21. Vendor-Managed Inventory Not a new concept – same process used by bread deliveries to stores for decades Not a new concept – same process used by bread deliveries to stores for decades Reduces need for warehousing Reduces need for warehousing Increased speed, reduced errors, and improved service Increased speed, reduced errors, and improved service Onus is on the supplier to keep the shelves full or assembly lines running Onus is on the supplier to keep the shelves full or assembly lines running variation of JIT variation of JIT Proctor&Gamble - Wal-Mart Proctor&Gamble - Wal-Mart DLA – moving from a manager of supplies to a manager of suppliers DLA – moving from a manager of supplies to a manager of suppliers Direct Vendor Deliveries – loss of visibility Direct Vendor Deliveries – loss of visibility

22. Collaborative Distribution and Outsourcing Collaborative planning, forecasting, and replenishment (CPFR) started by Nabisco Collaborative planning, forecasting, and replenishment (CPFR) started by Nabisco Allows suppliers to know what is really needed and when Allows suppliers to know what is really needed and when Electronic-based exchange of data and information Electronic-based exchange of data and information Significant decrease in inventory levels and more efficient logistics - maybe not! Significant decrease in inventory levels and more efficient logistics - maybe not! Companies work together for benefit of all of the supply chain Companies work together for benefit of all of the supply chain

23. Transportation Common methods are railroads, trucking, water, air, intermodal, package carriers, and pipelines Common methods are railroads, trucking, water, air, intermodal, package carriers, and pipelines

24. Railroads 150,000 miles in US 150,000 miles in US Low cost, high-volume Low cost, high-volume Improving flexibility Improving flexibility intermodal service intermodal service double stacking double stacking Complaints: slow, inflexible, large loads Advantages: large/bulky loads, intermodal

25. Award-Winning Service Recognition Wal-Mart Stores, Inc. Carrier of the Year – 5 years in a row Target Only rail carrier to receive the Vice President’s Award American Honda Motor Company Premier Partner – 4 consecutive years Toyota’s North American Parts and Logistics Division (NAPLD) Rail Carrier of the Year – 3 consecutive years KIA Carrier of the Year Schneider Carrier of the Year – 3 consecutive years Federal Express Only rail carrier to receive outstanding supplier award - 2 years in a row United Parcel Service 99.5% failure free, damage free and on-time rating from United Parcel Service every year since 1995

26. Most used mode in US -75% of total freight (not total weight) Most used mode in US -75% of total freight (not total weight) Flexible, small loads Flexible, small loads Consolidation, Internet load match sites Consolidation, Internet load match sites Single sourcing reduces number of trucking firms serving a company Single sourcing reduces number of trucking firms serving a company Truck load (TL) vs. Less Than Truck Load (LTL) Truck load (TL) vs. Less Than Truck Load (LTL) Trucking

27. Air Rapidly growing segment of transportation industry Rapidly growing segment of transportation industry Lightweight, small items Lightweight, small items Quick, reliable, expensive (relatively expensive depending on costs of not getting item there) Quick, reliable, expensive (relatively expensive depending on costs of not getting item there) Major airlines and US Postal Service, UPS, FedEx, DHL Major airlines and US Postal Service, UPS, FedEx, DHL

28. Package Carriers FedEx, UPS, US Postal Service, DHL FedEx, UPS, US Postal Service, DHL Significant growth driven by e-businesses and the move to smaller shipments and consumer desire to have it NOW Significant growth driven by e-businesses and the move to smaller shipments and consumer desire to have it NOW Use several modes of transportation Use several modes of transportation Expensive - relative!! Expensive - relative!! Fast and reliable - relative!! Fast and reliable - relative!! Innovative use of technologies in some cases Innovative use of technologies in some cases Online tracking – some better than others Online tracking – some better than others

29. Intermodal Combination of several modes of transportation Combination of several modes of transportation Most common are truck/rail/truck and truck/water/rail/truck Most common are truck/rail/truck and truck/water/rail/truck Enabled by the use of containers – the development of the 20 and 40 foot containers significantly changed the face of shipping Enabled by the use of containers – the development of the 20 and 40 foot containers significantly changed the face of shipping ~2% of all US cargo via intermodal ~2% of all US cargo via intermodal

30. Water One of oldest means of transport One of oldest means of transport Low-cost, high-volume, slow (relative) Low-cost, high-volume, slow (relative) Security - sheer volume - millions of containers annually Security - sheer volume - millions of containers annually Bulky, heavy and/or large items Bulky, heavy and/or large items Standardized shipping containers improve service Standardized shipping containers improve service The most common form of international shipping The most common form of international shipping

31. Pipelines Primarily for oil & refined oil products Primarily for oil & refined oil products Slurry lines carry coal or kaolin Slurry lines carry coal or kaolin High initial capital investment High initial capital investment Low operating costs Low operating costs Can cross difficult terrain Can cross difficult terrain

32. Global Supply Chain Free trade & global opportunities Free trade & global opportunities Nations form trading groups Nations form trading groups No tariffs or duties No tariffs or duties Freely transport goods across borders Freely transport goods across borders Security!! Security!!

33. Global Supply Chain Problems National and regional differences National and regional differences Customs, business practices, and regulations Customs, business practices, and regulations Foreign markets are not homogeneous Foreign markets are not homogeneous Quality can be a major issue Quality can be a major issue

34. Security ~ 10+ million containers annually Customs-Trade Partnership Against Terrorism (C- TPAT) Port Security – SAFE Ports Act; Scanning of all Containers Cost - $2 billion closing of major port 66% of all goods into US comes through 20 major ports 44% through LA/Long Beach Cost of attack on major port estimated at $20 Billion

39. Chapter 11 Forecasting

40. Forecasting Survey How far into the future do you typically project when trying to forecast the health of your industry?  less than 4 months3%  4-6 months12%  7-12 months28%  > 12 months57% Fortune Council survey, Nov 2005

41. Indices to forecast health of industry Consumer price index 51% Consumer Confidence index44% Durable goods orders20% Gross Domestic Product35% Manufacturing and trade inventories and sales27% Price of oil/barrel34% Strength of US $46% Unemployment rate53% Interest rates/fed funds59% Fortune Council survey, Nov 2005

42. Forecasting Importance Improving customer demand forecasting and sharing the information downstream will allow more efficient scheduling and inventory management Boeing, 1997: $2.6 billion write down due to “raw material shortages, internal and supplier parts shortages” Wall Street Journal, Oct 23, 1987

43. Forecasting Importance “Second Quarter sales at US Surgical Corporation decline 25%, resulting in a $22 mil loss…attributed to larger than anticipated inventories on shelves of hospitals.” US Surgical Quarterly, Jul 1993 “IBM sells out new Aetna PC; shortage may cost millions in potential revenue.” Wall Street Journal, Oct 7, 1994

44. Principles of Forecasting Forecasts are usually wrong every forecast should include an estimate of error Forecasts are more accurate for families or groups Forecasts are more accurate for nearer periods.

45. Important Factors to Improve Forecasting Record Data in the same terms as needed in the forecast – production data for production forecasts; time periods Record circumstances related to the data Record the demand separately for different customer groups

46. Forecast Techniques Extrinsic Techniques – projections based on indicators that relate to products – examples Intrinsic – historical data used to forecast (most common)

47. Forecasting Forecasting errors can increase the total cost of ownership for a product - inventory carrying costs - obsolete inventory - lack of sufficient inventory - quality of products due to accepting marginal products to prevent stockout

48. Forecasting Essential for smooth operations of business organizations Estimates of the occurrence, timing, or magnitude of uncertain future events Costs of forecasting: excess labor; excess materials; expediting costs; lost revenues

49. Forecasting Predicting future events Predicting future events Usually demand behavior over a time frame Usually demand behavior over a time frame Qualitative methods Qualitative methods Based on subjective methods Based on subjective methods Quantitative methods Quantitative methods Based on mathematical formulas Based on mathematical formulas

50. Impact of Just-in-Time on Forecasting Just in time as a inventory method Just in time as a Continuous process improvement program Just in time - one on the shelf Usage factors Single order vs. Case order

51. Strategic Role of Forecasting Focus on supply chain management Focus on supply chain management Short term role of product demand Short term role of product demand Long term role of new products, processes, and technologies Long term role of new products, processes, and technologies Focus on Total Quality Management Focus on Total Quality Management Satisfy customer demand Satisfy customer demand Uninterrupted product flow with no defective items Uninterrupted product flow with no defective items Necessary for strategic planning Necessary for strategic planning

52. Strategic Role of Forecasting Focus on supply chain management Focus on supply chain management Short term role of product demand Short term role of product demand Long term role of new products, processes, and technologies Long term role of new products, processes, and technologies Focus on Total Quality Management Focus on Total Quality Management Satisfy customer demand Satisfy customer demand Uninterrupted product flow with no defective items Uninterrupted product flow with no defective items Necessary for strategic planning Necessary for strategic planning

53. Total Quality Management Management approach to long term success through customer satisfaction Total Quality Control - process of creating and producing quality goods and services that meet the expectations of the customer quality - conformance to requirements or fitness for use

54. Trumpet of Doom As forecast horizon increases, so does the forecasting error (i.e., accuracy decreases) – shorten horizon by shortening of cycles or flow times Law of Large Numbers – as volume increases, relative variability decreases – forecasting error is smaller: goal – forecast at aggregate levels; collaborate; standardize parts Volume and activity increase at end of reporting periods – Krispy Kreme

55. Time Frame Time Frame Short-range, medium- range, long-range Short-range, medium- range, long-range Demand Behavior Demand Behavior Trends, cycles, seasonal patterns, random Trends, cycles, seasonal patterns, random Components of Forecasting Demand

56. Time Frame Short-range to medium-range Short-range to medium-range Daily, weekly monthly forecasts of sales data Daily, weekly monthly forecasts of sales data Up to 2 years into the future Up to 2 years into the future Long-range Long-range Strategic planning of goals, products, markets Strategic planning of goals, products, markets Planning beyond 2 years into the future Planning beyond 2 years into the future

57. Demand Behavior Trend Trend gradual, long-term up or down movement gradual, long-term up or down movement Cycle Cycle up & down movement repeating over long time frame up & down movement repeating over long time frame Seasonal pattern Seasonal pattern periodic oscillation in demand which repeats periodic oscillation in demand which repeats Random movements follow no pattern Random movements follow no pattern

58. Forms of Forecast Movement Time (a) Trend Time (d) Trend with seasonal pattern Time (c) Seasonal pattern Time (b) Cycle Demand Demand Demand Demand Random movement Figure 8.1

59. Forecasting Methods Time series Time series Regression or causal modeling Regression or causal modeling Qualitative methods Qualitative methods Management judgment, expertise, opinion Management judgment, expertise, opinion Use management, marketing, purchasing, engineering Use management, marketing, purchasing, engineering Delphi method Delphi method Solicit forecasts from experts Solicit forecasts from experts

60. Forecasting Process 6. Check forecast accuracy with one or more measures 4. Select a forecast model that seems appropriate for data 5. Develop/compute forecast for period of historical data 8a. Forecast over planning horizon 9. Adjust forecast based on additional qualitative information and insight 10. Monitor results and measure forecast accuracy 8b. Select new forecast model or adjust parameters of existing model 7. Is accuracy of forecast acceptable? 1. Identify the purpose of forecast 3. Plot data and identify patterns 2. Collect historical data Figure 8.2

61. Time Series Methods Statistical methods using historical data Statistical methods using historical data Moving average Moving average Exponential smoothing Exponential smoothing Linear trend line Linear trend line Assume patterns will repeat Assume patterns will repeat Naive forecasts Naive forecasts Forecast = data from last period Forecast = data from last period

62. Moving Average Average several periods of data Average several periods of data Dampen, smooth out changes Dampen, smooth out changes Use when demand is stable with no trend or seasonal pattern Use when demand is stable with no trend or seasonal pattern stock market analysis - trend analysis stock market analysis - trend analysis

63. Moving Average Average several periods of data Average several periods of data Dampen, smooth out changes Dampen, smooth out changes Use when demand is stable with no trend or seasonal pattern Use when demand is stable with no trend or seasonal pattern Sum of Demand In n Periods n

64. Simple Moving Average Jan120 Feb90 Mar100 Apr75 May110 June50 July75 Aug130 Sept110 Oct90 ORDERS MONTHPER MONTH Example 8.1

65. Jan120 Feb90 Mar100 Apr75 May110 June50 July75 Aug130 Sept110 Oct90 ORDERS MONTHPER MONTH Example 8.1 MA nov = 3 = 90 + 110 + 130 3 = 110 orders for Nov Simple Moving Average D aug +D sep +D oct

66. Jan120– Feb90 – Mar100 – Apr75103.3 May11088.3 June5095.0 July7578.3 Aug13078.3 Sept11085.0 Oct90105.0 Nov –110.0 ORDERSTHREE-MONTH MONTHPER MONTHMOVING AVERAGE Example 8.1 Simple Moving Average

67. Jan120– Feb90 – Mar100 – Apr75103.3 May11088.3 June5095.0 July7578.3 Aug13078.3 Sept11085.0 Oct90105.0 Nov –110.0 ORDERSTHREE-MONTH MONTHPER MONTHMOVING AVERAGE Example 8.1 MA 5 = 5 i = 1  DiDiDiDi 5 = 90 + 110 + 130 + 75 + 50 5 = 91 orders for Nov Simple Moving Average

68. Example 8.1 Simple Moving Average Jan120– – Feb90 – – Mar100 – – Apr75103.3 – May11088.3 – June5095.099.0 July7578.385.0 Aug13078.382.0 Sept11085.088.0 Oct90105.095.0 Nov –110.091.0 ORDERSTHREE-MONTHFIVE-MONTH MONTHPER MONTHMOVING AVERAGEMOVING AVERAGE

69. 150 150 – 125 125 – 100 100 – 75 75 – 50 50 – 25 25 – 0 0 – ||||||||||| JanFebMarAprMayJuneJulyAugSeptOctNov Orders Month Figure 8.2 Smoothing Effects

70. 150 150 – 125 125 – 100 100 – 75 75 – 50 50 – 25 25 – 0 0 – ||||||||||| JanFebMarAprMayJuneJulyAugSeptOctNov Orders Month Actual Figure 8.2

71. Smoothing Effects 150 150 – 125 125 – 100 100 – 75 75 – 50 50 – 25 25 – 0 0 – ||||||||||| JanFebMarAprMayJuneJulyAugSeptOctNov 3-month Actual Orders Month Figure 8.2

72. Smoothing Effects 150 150 – 125 125 – 100 100 – 75 75 – 50 50 – 25 25 – 0 0 – ||||||||||| JanFebMarAprMayJuneJulyAugSeptOctNov 5-month 3-month Actual Orders Month Figure 8.2

73. Weighted Moving Average Adjusts moving average method to more closely reflect data fluctuations Adjusts moving average method to more closely reflect data fluctuations

74. Weighted Moving Average WMA n = i = 1  Wi DiWi DiWi DiWi Di where W i = the weight for period i, between 0 and 100 percent  W i = 1.00 Adjusts moving average method to more closely reflect data fluctuations Adjusts moving average method to more closely reflect data fluctuations

75. Weighted Moving Average Example MONTH WEIGHT DATA August 17%130 September 33%110 October 50%90 Example 8.2

76. Weighted Moving Average Example MONTH WEIGHT DATA August 17%130 September 33%110 October 50%90 November forecast WMA 3 = 3 i = 1  Wi DiWi DiWi DiWi Di = (0.50)(90) + (0.33)(110) + (0.17)(130) = 103.4 orders 3 Month = 110 5 month = 91

77. Averaging method Averaging method Weights most recent data more strongly Weights most recent data more strongly Reacts more to recent changes Reacts more to recent changes Widely used, accurate method Widely used, accurate method Exponential Smoothing

78. F t +1 =  D t + (1 -  )F t where F t +1 =forecast for next period D t =actual demand for present period F t =previously determined forecast for present period  =weighting factor, smoothing constant Averaging method Averaging method Weights most recent data more strongly Weights most recent data more strongly Reacts more to recent changes Reacts more to recent changes Widely used, accurate method Widely used, accurate method Exponential Smoothing

79. Forecast for Next Period Forecast = (weighting factor)x(actual demand for period)+(1-weighting factor)x(previously determined forecast for present period) 0 >  <= 1 Lesser reaction to recent demand Greater reaction to recent demand

80. PERIODMONTHDEMAND 1Jan37 2Feb40 3Mar41 4Apr37 5May 45 6Jun50 7Jul 43 8Aug 47 9Sep 56 10Oct52 11Nov55 12Dec 54 Example 8.3 Exponential Smoothing

81. PERIODMONTHDEMAND 1Jan37 2Feb40 3Mar41 4Apr37 5May 45 6Jun50 7Jul 43 8Aug 47 9Sep 56 10Oct52 11Nov55 12Dec 54 F 2 =  D 1 + (1 -  )F 1 = (0.30)(37) + (0.70)(37) = 37 F 3 =  D 2 + (1 -  )F 2 = (0.30)(40) + (0.70)(37) = 37.9 F 13 =  D 12 + (1 -  )F 12 = (0.30)(54) + (0.70)(50.84) = 51.79 Exponential Smoothing

82. FORECAST, F t + 1 PERIODMONTHDEMAND(  = 0.3) 1Jan37– 2Feb4037.00 3Mar4137.90 4Apr3738.83 5May 4538.28 6Jun5040.29 7Jul 4343.20 8Aug 4743.14 9Sep 5644.30 10Oct5247.81 11Nov5549.06 12Dec 5450.84 13Jan–51.79 Example 8.3 Exponential Smoothing

83. FORECAST, F t + 1 PERIODMONTHDEMAND(  = 0.3)(  = 0.5) 1Jan37–– 2Feb4037.0037.00 3Mar4137.9038.50 4Apr3738.8339.75 5May 4538.2838.37 6Jun5040.2941.68 7Jul 4343.2045.84 8Aug 4743.1444.42 9Sep 5644.3045.71 10Oct5247.8150.85 11Nov5549.0651.42 12Dec 5450.8453.21 13Jan–51.7953.61 Example 8.3 Exponential Smoothing

84. y = a + bx where a =intercept (at period 0) b =slope of the line x =the time period y =forecast for demand for period x Linear Trend Line

85. Seasonal Adjustments Repetitive increase/ decrease in demand Repetitive increase/ decrease in demand Use seasonal factor to adjust forecast Use seasonal factor to adjust forecast

86. Seasonal Adjustments Repetitive increase/ decrease in demand Repetitive increase/ decrease in demand Use seasonal factor to adjust forecast Use seasonal factor to adjust forecast Seasonal factor = S i = DiDiDDDiDiDD = demand for period/sum of demand

87. Seasonal Adjustment 1999 12.68.66.317.545.0 2000 14.110.37.518.250.1 2001 15.310.68.119.653.6 Total 42.029.521.955.3148.7 DEMAND (1000’S PER QUARTER) YEAR1234Total

88. Seasonal Adjustment 1999 12.68.66.317.545.0 2000 14.110.37.518.250.1 2001 15.310.68.119.653.6 Total 42.029.521.955.3148.7 DEMAND (1000’S PER QUARTER) YEAR1234Total S 1 = = = 0.28 D1D1DDD1D1DD42.0148.7 S 2 = = = 0.20 D2D2DDD2D2DD 29.5148.7 S 4 = = = 0.37 D4D4DDD4D4DD 55.3148.7 S 3 = = = 0.15 D3D3DDD3D3DD21.9148.7

89. Seasonal Adjustment 1999 12.68.66.317.545.0 2000 14.110.37.518.250.1 2001 15.310.68.119.653.6 Total 42.029.521.955.3148.7 DEMAND (1000’S PER QUARTER) YEAR1234Total S i 0.280.200.150.37

90. Seasonal Adjustment 1999 12.68.66.317.545.0 2000 14.110.37.518.250.1 2001 15.310.68.119.653.6 Total 42.029.521.955.3148.7 DEMAND (1000’S PER QUARTER) YEAR1234Total S i 0.280.200.150.37 Forecast for 2002 using simple 3 year moving ave Forecast for 1st qtr 2002

91. Forecast Accuracy Find a method which minimizes error Find a method which minimizes error Error = Actual - Forecast Error = Actual - Forecast Mean Absolute Deviation (MAD) Mean Absolute Deviation (MAD)

92. Mean Absolute Deviation (MAD) where t = the period number t = the period number D t = demand in period t D t = demand in period t F t = the forecast for period t F t = the forecast for period t n = the total number of periods n = the total number of periods  = the absolute value  D t - F t  n MAD =

93. Forecast Control Reasons for out-of-control forecasts Reasons for out-of-control forecasts Change in trend Change in trend Appearance of cycle Appearance of cycle Weather changes Weather changes Promotions Promotions Competition Competition Politics Politics

94. Tracking Signal Tracking Signal establishes control limits - usually +/- 3 MAD The greater the tracking signal the more the demand exceeds the forecast Sum(Demand-Forecast)/Mean Absolute Deviation Sometimes called Running Sum of Forecasting Error

95. Tracking Signal Compute each period Compute each period Compare to control limits Compare to control limits Forecast is in control if within limits Forecast is in control if within limits Use control limits of +/- 2 to +/- 5 MAD Tracking signal = =  (D t - F t ) MADEMAD

96. Tracking Signal Values 13737.00––– 24037.003.003.003.00 34137.903.106.103.05 43738.83-1.834.272.64 54538.286.7210.993.66 65040.299.6920.684.87 74343.20-0.2020.484.09 84743.143.8624.344.06 95644.3011.7036.045.01 105247.814.1940.234.92 115549.065.9446.175.02 125450.843.1549.324.85 DEMANDFORECAST,ERROR  E = PERIODD t F t D t - F t  (D t - F t )MAD

97. Tracking Signal Values 13737.00––– 24037.003.003.003.00 34137.903.106.103.05 43738.83-1.834.272.64 54538.286.7210.993.66 65040.299.6920.684.87 74343.20-0.2020.484.09 84743.143.8624.344.06 95644.3011.7036.045.01 105247.814.1940.234.92 115549.065.9446.175.02 125450.843.1549.324.85 DEMANDFORECAST,ERROR  E = PERIODD t F t D t - F t  (D t - F t )MAD TS 3 = = 2.00 6.10 3.05 Tracking signal for period 3

98. Tracking Signal Values 13737.00–––– 24037.003.003.003.001.00 34137.903.106.103.052.00 43738.83-1.834.272.641.62 54538.286.7210.993.663.00 65040.299.6920.684.874.25 74343.20-0.2020.484.095.01 84743.143.8624.344.066.00 95644.3011.7036.045.017.19 105247.814.1940.234.928.18 115549.065.9446.175.029.20 125450.843.1549.324.8510.17 DEMANDFORECAST,ERROR  E =TRACKING PERIODD t F t D t - F t  (D t - F t )MADSIGNAL

99. Forecasting Long Term – location, capacity, new product design Short Term – production, inventory control, labor levels, cost controls Questions?

100. Next Class – After your Break Chap 6 Chapter 12 The Beer Game