Demand Forecasting for Inventory Control (eBook)

Nick T. Thomopoulos is professor emeritus at the Illinois Institute of Technology. He is the author of nine books, including: Applied Forecasting Methods, Prentice Hall, Strategic Inventory Management and Planning, Hitchcock, Essentials of Monte Carlo Simulation, Springer, and Production, Inventory and the Supply Chain, Atlantic Publishers. He has over 100 publications and presentations to his credit, and for many years, he has consulted in a wide variety of industries in the United States, Europe and Asia. Nick received honors over the years, such as the Rist Prize from the Military Operations Research Society, the Distinguished Professor Award in Bangkok, Thailand from the IIT Asian Alumni Association, and the Professional Achievement Award from the IIT Alumni Association.

Preface 6
Contents 8
Chapter-1 13
Demand Forecasting for Inventory Control 13
1.1 Introduction 13
1.1.1 Demand Forecasting 13
1.1.2 At the Beginning 14
1.1.3 Calculators 14
1.1.4 Data Processing 15
1.1.5 Forecasting Pioneers 15
1.1.6 Computer Era 16
1.1.7 Qualification 16
1.2 Chapter Summaries 17
Chapter-2 23
Demand History 23
2.1 Introduction 23
2.2 Customer Demand History for a Part 24
2.3 Demand-to-Date 24
2.4 Service Part Regular and Emergency Demands 25
2.5 New and Replenish Stock Demands for Retail Items at DC 25
2.6 Weekly Demands 26
2.7 445 Fiscal Months at Plants 26
2.8 Regular Demands and Other Requirements at DCs 27
2.9 Regular and Promotion Demands at DCs and Stores 28
2.10 Advance Demands 28
2.11 Demand Patterns 28
2.12 Return Demands 29
2.13 Outlier Demands 30
2.14 Coefficient of Variation 30
2.15 Demand Distribution 30
2.16 Cumulative Round Algorithm 31
2.17 Cumulative Forecasts 31
2.18 Inventory Profile 31
Summary 33
Chapter-3 34
Horizontal Forecasts 34
3.1 Introduction 34
3.2 Horizontal Forecasts 34
3.3 Raw Forecasts 35
3.4 Cumulative Rounding Algorithm 35
3.5 Estimate the Level 36
3.6 Raw Forecasts 36
3.7 Integer Forecasts 36
3.8 Standard Deviation and Cov 37
3.9 Horizontal Moving Average Forecasts 38
3.10 Standard Deviation and Cov 38
3.11 Horizontal Discount Forecasts 40
3.12 Standard Deviation and Cov 41
3.13 Horizontal Smoothing Forecasts 43
3.14 Standard Deviation 44
3.15 2-Stage Forecasts 45
3.16 Raw Lines to Integer Forecasts 46
3.17 Integer Lines to Integer Forecasts 49
Summary 50
Chapter-4 51
Trend Forecasts 51
4.1 Introduction 51
4.2 Trend Regression Forecast 51
4.3 Trend Discount Forecasts 55
4.4 Trend Smoothing Forecasts 59
4.5 Dampening 63
4.6 Linear Trend Forecast Model 63
4.7 Geometric Forecast Model 64
4.8 Maximum Forecast Model 65
4.9 Other Dampening Applications 67
Summary 67
Chapter-5 69
Seasonal Forecasts 69
5.1 Introduction 69
5.2 Seasonal Multiplicative Model 69
5.3 Revised Forecasts 75
5.4 Initialize with 12-Months of Demand History 76
5.5 Seasonal Additive Model 77
5.6 Initialize With 12-Months of Demand History 78
5.7 Revision Forecasts 78
Summary 79
Chapter-6 80
Promotion Forecasts 80
6.1 Introduction 80
6.2 Promotion Horizontal Model 80
6.3 Initialize Stage 81
6.4 Standard Deviation and Cov 84
6.5 Forecasts 84
6.6 Revision Stage 85
6.7 Unbiased Estimates 85
6.8 Promotion Trend Model 87
6.9 Initialize Stage 88
6.10 Standard Deviation and Cov 90
6.11 Revision Stage 93
6.12 Unbiased Estimates 93
Summary 96
Chapter-7 97
Multi-SKU Forecasts 97
7.1 Introduction 97
7.2 SKU Mean and Standard Deviation 98
7.3 Derivation of Binomial When n is a Random Variable 99
7.4 Top-Down Forecasting Method 100
7.5 Total Demand Forecasts 100
7.6 Location Portion of Demand 101
7.7 The Level by Location and Total 102
7.8 Standard Deviation by Location and Total 103
7.9 Cov by Location and Total 105
7.10 Bottom-Up Forecasting Method 105
7.11 Location j Forecasts 106
7.12 Bottom-Up Total Forecast 107
7.13 Total Forecast at Month 1 109
7.14 Horizontal SKU Forecasts 110
7.15 SKU Forecasts at the Distribution Center 111
7.16 SKU Forecasts at the Stores 113
Summary 114
Chapter-8 115
Forecast Sensitivity 115
8.1 Introduction 115
8.2 Cov by NMH when Horizontal Demands and Forecasts 115
8.3 Cov by NMH when Trend Demands and Forecasts 116
8.4 Cov by Parameter and Forecast Model when Horizontal Demands 118
8.5 Cov by Parameter and Forecast Model when Trend Demands 119
8.6 Cov by Parameter and Forecast Model when Seasonal Demands 120
8.7 Cov when Horizontal Demands with an Outlier 121
8.8 Cov when Trend Demands with an Outlier 123
Summary 125
Chapter-9 126
Filtering Outliers 126
9.1 Introduction 126
9.2 Horizontal Filtering 126
9.2.1 Horizontal Filtering Algorithm (HFA) 127
9.3 Trend Filtering 132
9.3.1 Trend Filtering Algorithm (TFA) 132
9.4 Seasonal Filtering 136
9.4.1 Seasonal Filtering Algorithm (SFA) 136
9.5 Filtering Line Demands in Order Entry 139
9.6 Derivation of Mean and Standard Deviation of Line Demands 141
Summary 143
Chapter-10 144
Standard Normal and Truncated Normal Distributions 144
10.1 Introduction 144
10.2 Normal Distribution 144
10.3 Standard Normal Distribution 145
10.3.1 Probability Density 145
10.3.2 Cumulative Distribution Function 145
10.4 Partial Measures 146
10.4.1 Partial Expectation 146
10.4.2 Partial Standard Deviation 146
10.4.3 Partial When (x?> ?xo)
10.4.4 Table Measures 147
10.5 Truncated Normal Distribution 147
10.5.1 Truncated Mean and Variance 149
10.5.2 Some Useful Identities 149
10.5.3 Truncated Cov 150
10.5.4 Three Related Variables: z, t and w 152
10.5.5 Limits on w 153
10.5.6 Hastings Approximations 153
10.5.7 Approximation of F(z) from z 154
10.5.8 Approximation of z from F(z) 154
Summary 155
Chapter-11 156
Safety Stock 156
11.1 Introduction 156
11.2 Control of the Inventory 156
11.3 Safety Stock when Normal Distribution 157
11.4 Service Level Method 158
11.5 Percent Fill Method 159
11.6 Sensitivity of Safety Stock with Cov 161
11.7 Service Level Safety Stock and Cov 161
11.8 Percent Fill Safety Stock and Cov 161
11.9 Safety Stock when Truncated Normal Distribution 163
11.10 Lead Time Demand 164
11.11 Service Level Methods and Truncated Normal 165
11.12 Percent Fill Method and Truncated Normal 167
Summary 170
Chapter-12 171
Auxiliary Forecasts 171
12.1 Introduction 171
12.2 Month-1 Forecasts and Demand-to-Date 171
12.3 Advance Demand 173
12.4 Initial Forecasts 175
12.5 All Time Forecasts 179
Summary 184
Bibliography 185
Index 186