SUPPLY CHAIN …MN 799 • TEXT: SUPPLY CHAIN – Chopra and Meindl – Prentice Hall • COURSE OUTLINE – Description Book pages – 1/22 Introduction, curriculum, rules, exams, Infrastructure (1-27) – 1/27 Strategic Fit and Scope. Supply Chain Drivers (27-51) – 2/05 No Class – 2/12 Demand Management (169-204) – 2/19 Aggregate Planning, Managing (205-225) – 2/26 Guest Lecture Network Operations (71-168) – 3/04 Managing Supply and Demand (121-144) – 3/11 Class trip to see Supply Chain in Operation – 3/18 No Class – 3/25 Mid Term – 4/01 Managing Inventory(249-295); – 4/08 Product Availability (297-384) – 4/15 Sourcing and Procurement (387-410) – 4/22 Transportation (411-219); Facility Decisions (109-133) – 4/29 Beer Game – 5/06 Co-ordination Information Information Technology & E- (477- 557) – 5/13 FINAL EXAMINATION

Supply Chain Engineering MN 799 1# GUIDELINES

• GRADING: – HOMEWORK – 20% – BEER GAME – 5% – MID TERM – 30% – FINAL – 45% • HOMEWORK MUST BE COMPLETED IN TIME. LATE SUBMISSIONS WILL START WITH A ‗B‘ GRADE • CLASSES WILL START AT 6.00PM AND GO STRAIGHT THRU TO 8.00PM

Supply Chain Engineering MN 799 2# DEFINITION OF A SUPPLY CHAIN • WHAT IS A SUPPLY CHAIN? • A SUPPLY CHAIN COVERS THE FLOW OF MATERIALS, INFORMATION AND CASH ACROSS THE ENTIRE ENTERPRISE • IS THE INTEGRATED PROCESS OF INTEGRATING, PLANNING, SOURCING, MAKING AND DELIVERING PRODUCT, FROM RAW MATERIAL TO END CUSTOMER, AND MEASURING THE RESULTS GLOBALLY • TO SATISFY CUSTOMERS AND MAKE A PROFIT • WHY A ‗SUPPLY CHAIN‘?

Supply Chain Engineering MN 799 3# Traditional View: in the Economy

1990 1996 2006 • Freight Transportation $352, $455 $809 B • % Freight 57% 62% • Inventory Expense $221, $311 $ 446 B • % Inventory 39% 33% • Administrative Expense $27, $31 $ 50 B • Logistics related activity 11%, 10.5%,9.9% • % of GNP.

Source: Cass Logistics Homework: What are 2007 statistics?

Supply Chain Engineering MN 799 4# Traditional View: Logistics in the Firm

• Profit 4% Profit Logistics • Logistics Cost 21% Cost

Marketing • Marketing Cost 27% Cost

• Manufacturing Cost 48% Manufacturing Cost

Homework: What it the profile for Consumables; Pharamas and Computers

Supply Chain Engineering MN 799 5# Supply Chain Management: The Magnitude in the Traditional View • Estimated that the grocery industry could save $30 billion (10% of operating cost by using effective logistics and supply chain strategies – A typical box of cereal spends 104 days from factory to sale – A typical car spends 15 days from factory to dealership • Compaq estimates it lost $0.5 billion to $1 billion in sales in 1995 because laptops were not available when and where needed • P&G estimates it saved retail customers $65 million by collaboration resulting in a better match of supply and demand • Laura Ashley turns its inventory 10 times a year, five times faster than 3 years ago

Supply Chain Engineering MN 799 6# HAMBURGERS AND FRIES

HAMBURGERS (4/LB) FRIES (3Large/lb) • CATTLE FARM – 50c/lb • POTATO FARM 25C/lb • BUTCHER • POTATO PROCESSOR • PACKAGING • DISTRIBUTION CENTER • DISTRIBUTION CENTER • RETAILER • RETAILER • CUSTOMER • CUSTOMER

Provide Sales Price at each stage Provide Sales Price at each stage

Supply Chain Engineering MN 799 7# Burger and Fries Examine this process – What do you observe?

What problems do you foresee in this Supply Chain? Please write some down

Supply Chain Engineering MN 799 8# Understanding the Supply Chain … a chain is only as good as its weakest link

Recall that saying? The saying applies to the principles of building a competitive infrastructure:

Supplier Manufacturer Wholesaler Retailer Customer …there is a limit to the surplus or profit in a supply chain

Strong, well-structured supply chains are critical to sustained competitive advantage.

We are all part of a Supply Chain in everything we buy

Supply Chain Engineering MN 799 9# OBJECTIVES OF A SUPPLY CHAIN

• MAXIMIZE OVERALL VALUE GENERATED – SATISFYING CUSTOMER NEEDS AT A PROFIT – VALUE STRONGLY CORRELATED TO PROFITABILITY – SOURCE OF REVENUE – CUSTOMER – COST GENERATED WITHIN SUPPLY CHAIN BY FLOWS OF INFORMATION, PRODUCT AND CASH – FLOWS OCCUR ACROSS ALL STAGES – CUSTOMER, RETAILER, WHOLESALER, DISTRIBUTOR, MANUFACTURER AND SUPPLIER – MANAGEMENT OF FLOWS KEY TO SUPPLY CHAIN SUCCESS

UNDERSTAND EACH OBJECTIVE

Supply Chain Engineering MN 799 10# DECISION PHASES IN A SUPPLY CHAIN • OVERALL STRATEGY OF COMPANY – EFFICIENT OR RESPONSIVE • SUPPLY CHAIN STRATEGY OR DESIGN ? – LOCATION AND CAPACITY OF PRODUCTION AND FACILITIES? – PRODUCTS TO BE MANUF, PURCHASED OR STORED BY LOCATION? – MODES OF TRANSPORTATION? – INFORMATION SYSTEMS TO BE USED? – CONFIGURATION MUST SUPPORT OVERALL STRAGEGY • SUPPLY CHAIN PLANNING? – OPERATING POLICIES – MARKETS SERVED, INVENTORY HELD, SUBCONTRACTING, PROMOTIONS, …? • SUPPLY CHAIN OPERATION? – DECISIONS AND EXECUTION OF ORDERS?

Supply Chain Engineering MN 799 11# Basic Supply Chain Architectures (Examples)

1. Indirect Channel Retailer Customer Supplier Wholesale Factory Retailer Customer Supplier Wholesale Retailer Customer 2. Direct Channel Supplier Supplier Supplier Fabricator Factory Integrator Customer Supplier

3. Virtual Channel Supplier Credit Virtual Service Store Supplier Fabricator Factory Express Customer Freight Supply Chain Engineering MN 799 12# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. Supply Chain Architecture Demand

LOCAL REGIONAL GLOBAL Strategic Issues MARKET MARKET MARKET . Demand Reach

INDIRECT CHANNEL DIRECT CHANNEL . Demand Risk VIRTUAL CHANNEL

MAKE •Cost Structure vs. • Asset Utilization BUY • Responsiveness SOLE SOURCE SINGLE SOURCE MULTI-SOURCE Supply Risk Supply Supply Chain Engineering MN 799 13# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. SUPPLY CHAIN FRAMEWORK AND INFRASTRUCTURE

PRINCIPLE:

BUILD A COMPETITIVE INFRASTRUCTURE

This principle is about

VELOCITY

Supply Chain Engineering MN 799 14# Cycle View of Supply Chains DEFINES ROLES AND RESPONSIBILITIES OF MEMBERS OF SUPPLY CHAIN Customer to Customer Order Cycle Retailer Replenishment Cycle to Distributor

Manufacturing Cycle to Manufacturer

Procurement Cycle to Supplier Supply Chain Engineering MN 799 15# PROCESS VIEW OF A SUPPLY CHAIN

• CUSTOMER ORDER CYCLE – TRIGGER: MAXIMIZE CONVERSION OF CUSTOMER ARRIVALS TO CUSTOMER ORDERS – ENTRY: ENSURE ORDER QUICKLY AND ACCURATELY COMMUNICATED TO ALL SUPPLY CHAIN PROCESSES – FULFILLMENT: GET CORRECT AND COMPLETE ORDERS TO CUSTOMERS BY PROMISED DUE DATES AT LOWEST COST – RECEIVING: CUSTOMER GETS ORDER

Supply Chain Engineering MN 799 16# PROCESS VIEW OF A SUPPLY CHAIN

• REPLENISHMENT CYCLE – REPLENISH INVENTORIES AT RETAILER AT MINIMUM COST WHILE PROVIDING NECESSARY PRODUCT AVAILABILITY TO CUSTOMER – RETAIL ORDER: • TRIGGER – REPLENISHMENT POINT – BALANCE SERVICE AND INVENTORY • ENTRY – ACCURATE AND QUICK TO ALL SUPPLY CHAIN • FULFILLMENT – BY DISTRIBUTOR OR MFG. – ON TIME • RECEIVING – BY RETAILER, UPDATE RECORDS • MANUFACTURING CYCLE – INCLUDES ALL PROCESSES INVOLVED IN REPLENISHING DISTRIBUTOR (RETAILER) INVENTORY, ON TIME @ OPTIMUM COST – ORDER ARRIVAL – PRODUCTION SCHEDULING – MANUFACTURING AND SHIPPING – RECEIVING

Supply Chain Engineering MN 799 17# PROCESS VIEW OF A SUPPLY CHAIN

• PROCUREMENT CYCLE – SEVERAL TIERS OF SUPPLIERS – INCLUDES ALL PROCESSES INVOLVED IN ENSURING MATERIAL AVAILABLE WHEN REQUIRED

• SUPPLY CHAIN MACRO PROCESSES • CRM – All processes focusing on interface between firm and customers • ISCM – A processes internal to firm • SRM – All processes focusing on interface between firm and suppliers

Supply Chain Engineering MN 799 18# FRONT OFFICE A Customer’s View of the Supply Chain Ex.-Travel arrangements on line

Order the product... Take delivery... with configuration complexity on-line the next day at home, and get started without a hassle

Pay for the product... Service the product... in a foreign currency by credit card anywhere in the world

Supply Chain Engineering MN 799 19# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. Push/Pull View of Supply Chains PULL – PROCESSES IN RESPONSE TO A CUSTOMER ORDER PUSH – PROCESSES IN ANTICIPATION OF A CUSTOMER ORDER Procurement, Customer Order Manufacturing and Cycle Replenishment cycles Customer Order arrives

PUSH PROCESSES PULL PROCESSES

Supply Chain Engineering MN 799 20# UNDERSTANDING THE SUPPLY CHAIN

• Homework • EXAMPLES: – EXAMPLES OF SUPPLY CHAINS –1.5 – pp 20-25 – WHAT ARE SOME OF THE KEY ISSUES IN THESE SUPPLY CHAINS – ANALYSE AND COMMENT ON 7-Eleven and Amazon– ANSWER QUESTIONS 1TO 6 FOR EACH

Supply Chain Engineering MN 799 21# SUPPLY CHAIN PERFORMANCE – STRATEGIC FIT AND SCOPE (Lesson 2) FILM – CHAIN REACTION

Business Strategy

New Product Marketing Strategy Strategy Supply Chain Strategy

New Marketing Product and Operations Distribution Service Development Sales Supply and Manufacture Finance, Accounting, Information Technology, Human Resources

EXAMPLES? Supply Chain Engineering MN 799 22# ACHIEVING STRATEGIC FIT

• Step 1. Understanding the Customer and Demand – Quantity - Lot size Implied – Response time Demand – Product variety Uncertainty – Service level See Table 2.1 – Price Regular Demand – Innovation Uncertainty due to customers demand and Implied Demand Uncertainty due to uncertainty in Supply Chain

Supply Chain Engineering MN 799 23# Levels of Implied Demand Uncertainty

Detergent High Fashion Long lead time steel Emergency steel Customer Need Price Responsiveness

Low High Implied Demand Uncertainty Attributes (Table 2-2) Low Implied Uncertainty High Implied Uncertainty Product Margin Low – High Aver. Forecast Error 10% 40-100%; Aver. Stockout rate 1-2% 10-40%; Aver. markdown 0% 10-25%

Supply Chain Engineering MN 799 24# SUPPLY SOURCE UNCERTAINTY

• TABLE 2.3 SUPPLY UNCERTAINTY – FREQUENT BREAKDOWNS – UNPREDICTABLE AND/OR LOW YIELDS – POOR QUALITY – LIMITED SUPPLIER CAPACITY – INFLEXIBLE SUPPLY CAPACITY – EVOLVING PRODUCTION PROCESSES • LIFE CYCLE POSITION OF PRODUCT – NEW PRODUCTS HIGH UNCERTAINTY • DEMAND AND SUPPLY UNCERTAINTY FIG 2.2

Supply Chain Engineering MN 799 25# Step 2 - Understanding the Supply Chain: Cost-Responsiveness Efficient Frontier (Table: 2.4)

Responsiveness – to Quantity, Time, Variety, Innovation, Service level

Exercise: Give examples of products that are: Highly efficient, Somewhat efficient, Responsiveness Somewhat responsive and highly responsive High

Low

Fig 2.3 High Low Cost (efficient) Supply Chain Engineering MN 799 26# Step 3. Achieving Strategic Fit

Responsive Companies try to move supply chain Zone of Strategic fit High Cost

Responsiveness spectrum

Low Cost Efficient supply chain

Certain Implied Uncertain demand uncertainty demand spectrum Supply Chain Engineering MN 799 27# SCOPE • Comparison of Efficient & Responsive Supply Chain Table 2.4 – EFF Vs RESPON. STRATEGY for DESIGN; PRICING; MANUF; INVEN; LEAD TIME; SUPPLIER – THERE IS A RIGHT SUPPLY CHAIN STRATEGY FOR A GIVEN COMPETITIVE STRATEGY (without a competitive strategy there is no right supply chain!) • OTHER ISSUES AFFECTING STRATEGIC FIT – MULTIPLE PRODUCTS AND CUSTOMER SEGMENTS • TAILOR SC TO MEET THE NEEDS OF EACH PRODUCT‘S DEMAND – PRODUCT LIFE CYCLE Fig 2.8 • AS DEMAND CHARACTERISTICS CHANGE, SO MUST SC STRATEGY - EXAMPLES – COMPETITIVE CHANGES OVER TIME (COMPETITOR) • EXPANDING STRATEGIC SCOPE – INTERCOMPANY INTERFUNCTIONAL SCOPE • MAXIMIZE SUPPLY CHAIN SURPLUS VIEW – EVALUATE ALL ACTIONS IN CONTEXT OF ENTIRE SUPPLY CHAIN (FIG 2.12) – FLEXIBLE INTERCOMPANY INTERFUNCTIONAL SCOPE • FLEXIBILITY CRITICAL AS ENVIRONMENT BECOMES DYNAMIC

Supply Chain Engineering MN 799 28#

Strategic Scope

Suppliers Manufacturer Distributor Retailer Customer

Competitive Strategy

Product Dev. Strategy

Supply Chain Strategy

Marketing Strategy

Supply Chain Engineering MN 799 29# Drivers of Supply Chain Performance

Competitive Strategy

Supply Chain Strategy

Efficiency Responsiveness

Supply chain structure

Inventory Transportation Facilities Information

Drivers TRADE OFF FOR EACH DRIVER

Supply Chain Engineering MN 799 30# INVENTORY – ‗WHAT‘ OF SUPPLY CHAIN – MISMATCH BETWEEN SUPPLY AND DEMAND – MAJOR SOURCE OF COST – HUGE IMPACT ON RESP0NSIVENESS – MATERIAL FLOW TIME • I = R T (I – Inventory, R – Throughput, T – Flow time) – ROLE IN COMPETITIVE STRATEGY – COMPONENTS • CYCLE INVENTORY – AVERAGE INVENTORY BETWEEN REPLENISHMENTS • SAFETY INVENTORY - TO COVER DEMAND AND SUPPLY UNCERTAINITY • SEASONAL INVENTORY – COUNTERS PREDICTABLE VARIATION – OVERALL TRADE OFF: RESPONSIVENESS VS EFFICIENCY

Supply Chain Engineering MN 799 31# TRANSPORTATION

• ‗HOW‘ OF SUPPLY CHAIN • LARGE IMPACT ON RESPONSIVENESS AND EFFICIENCY • ROLE IN COMPETITIVE STRATEGY • COMPONENTS – MODE – AIR, TRUCK, RAIL, SHIP, PIPELINE, ELECTRONIC – ROUTE SELECTION – IN HOUSE OR OUTSOURCE • OVERALL TRADE OFF: RESPONSIVENESS VS EFFICIENCY

Supply Chain Engineering MN 799 32# FACILITIES • ‗WHERE‘ OF SUPPLY CHAIN • TRANSFORMED (FACTORY) OR STORED (WAREHOUSE) • ROLE IN COMPETITIVE STRATEGY • COMPONENTS – LOCATION - CENTRAL OR DECENTRAL – CAPACITY – FLEXIBILITY VS EFFICIENCY – MANUFACTURING METHODOLOGY – PRODUCT OR PROCESS FOCUS – WAREHOUSING METHODOLOGY – STORAGE – SKU, JOB LOT, CROSSDOCKING • OVERALL TRADE OFF: RESPONSIVENESS VS EFFICIENCY

Supply Chain Engineering MN 799 33# INFORMATION • AFFECTS EVERY PART OF SUPPLY CHAIN – CONNECTS ALL STAGES – ESSENTIAL TO OPERATION OF ALL STAGES • ROLE IN COMPETITIVE STATEGY – SUBSTITUTE FOR INVENTORY • COMPONENTS – PUSH VS PULL – COORDINATION AND INFORMATION SHARING – AND AGGREGATE PLANNING – ENABLING TECHNOLOGIES • EDI • INTERNET • ERP • SCM • OVERALL TRADE OFF: RESPONSIVENESS VS EFFICIENCY ?

Supply Chain Engineering MN 799 34# Considerations for Supply Chain Drivers

Driver Efficiency Responsiveness

Inventory Cost of holding Availability

Transportation Consolidation Speed

Facilities Consolidation / Proximity / Dedicated Flexibility Information What information is best suited for each objective

Supply Chain Engineering MN 799 35# MAJOR OBSTACLES TO ACHIEVING FIT • Multiple global owners / incentives in a supply chain – Information Coordination & Contractual Coordination

Local optimization and lack of global fit

• Increasing product variety / shrinking life cycles / demanding customers/customer fragmentation

Increasing demand and supply uncertainty

Supply Chain Engineering MN 799 36# OBSTACLES TO ACHIEVING STRATEGIC FIT

• INCREASING VARIETY OF PRODUCTS • DECREASING PRODUCT LIFE CYCLES • INCREASINGLY DEMANDING CUSTOMERS • FRAGMENTATION OF SUPPLY CHAIN OWNERSHIP • GLOBALIZATION • DIFFICULTY EXECUTING NEW STRATEGIES • ALL INCREASE UNCERTAINTY

Supply Chain Engineering MN 799 37# Dealing with Product Variety: Mass Customization

Long Lead Time Lead Short Mass Customization Low Low

High High

Supply Chain Engineering MN 799 38# Fragmentation of Markets and Product Variety

• Are the requirements of all market segments served identical? • Are the characteristics of all products identical? • Can a single supply chain structure be used for all products / customers? • No! A single supply chain will fail different customers on efficiency or responsiveness or both.

Supply Chain Engineering MN 799 39# HOMEWORK

• Page 49 – Nordstrom – Answer Questions 1 to 4 • Answer the above questions for Amazon.com • Page 67 – Answer Questions 1 to 4

Supply Chain Engineering MN 799 40# REVIEW QUESTIONS • WHAT IS STRATEGIC FIT? HOW IS IT ACHIEVED? – COMPANY‘S APPROACH TO MATCH DEMAND REQUIREMENTS AND SUPPLY POSITIONING – MULTIPLE PRODUCTS AND CUSTOMER SEGMENTS – PRODUCT LIFE CYCLE • WHAT IS STRATEGIC SCOPE? – INTERCOMPANY, INTERFUNCTIONAL EXTENSION • WHAT ARE THE SUPPLY CHAIN DRIVERS. WHAT ARE THEIR ROLES AND COMPONENTS? – INVENTORY; FACILITIES; TRANSPORTATION; INFORMATION • OBSTACLES

Supply Chain Engineering MN 799 41#

Demand-Management Activities Lesson 3

Forecasting (uncertainty) Order service (certainty)

Demand management

RULE: Do not forecast what you can plan, calculate, or extract from supply chain feedback.

Source: Adapted from Plossl, “Getting the Most from Forecasts,” APICS 15th International Conference Proceedings, 1972

Supply Chain Engineering MN 799 42# DETERMINING DEMAND • FORECASTING – TWO TYPES – WRONG AND LUCKY – TWO NUMBERS – QUANTITY AND DATE – ELEMENTS of a GOOD FORECASTING SYSTEM: • EQUAL CHANCE OF BEING OVER OR UNDER • INCLUDES KNOWN FUTURE EVENTS • HAS RANGE OR FORECAST ERROR ESTIMATE • REVIEWED REGULARLY

Supply Chain Engineering MN 799 43# FORECASTING

• GENERAL PRINCIPLES: – MORE ACCURATE AT THE AGGREGATE LEVEL – MORE ACCURATE FOR SHORTER PERIODS OF TIME CLOSER TO PRESENT – SET OF NUMBERS TO WORK FROM, NOT TO WORK TO – MOSTLY ALWAYS WRONG

– EXAMPLE: MONTHLY vs DAILY EXPENDITURE

Supply Chain Engineering MN 799 44# FORECASTING • MAIN TECHNIQUES: – QUALITATIVE • MANAGEMENT REVIEW • DELPHI METHOD • MARKET RESEARCH – QUANTITIVE • MOVING AVERAGE • WEIGHTED MOVING AVERAGE • EXPONENTIAL SMOOTHING • REGRESSION ANALYSIS • SEASONALILTY • PYRAMID

Supply Chain Engineering MN 799 45# FORECASTING • QUALITATIVE – USEFUL ON NEW PRODUCTS – AS A SUPPLEMENT TO QUANTITATIVE NUMBERS • QUANTITATIVE – NEEDS HISTORICAL DATA OR PROJECTED DATA – AVAILABLE – CONSISTENT – ACCURATE – UNITS - MEASURABLE

Supply Chain Engineering MN 799 46# WORK OUT JUNE’s FORECASTS FOR ALL SKU’s Month SKU Jan Feb Mar Apr May Jun

A 25 21 23 2321 21

B 27 23 26 21 25

C 16 18 17 23 30

D 23 26 25 52 23

E 29 30 ? 26 28

Total 120 118 91 2443 127

What actions should be taken? What is forecast for June? For each SKU? For total?

Supply Chain Engineering MN 799 47# Simple Moving Averages (SMA)

D + D + D Simple Moving Average (SMA) F = T T- 1 T- 2 T+ 1 n Demand (3-period) (4-period) Forecast Forecast

180 start-up start-up 160 220 186.6 200 193.3 190 260 226.6 210 240 233.3 230 Where F = Forecast T = Current time period D = Demand n = Number of periods( max)

Exercise: Work out the SMA for two periods Question: What determines the number of periods used? Why?

Supply Chain Engineering MN 799 48# Weighted Moving Averages

Weighted Moving Average (WMA) FT1  WTDT  WT1DT1...  ...WTn1DTn1

Forecast Forecast Demand (.2, .3, .5) (.1, .2, .3, .4) 180 start-up start-up 160 220 194 200 198 196 260 234 224 240 238 236 Where: F = Forecast T = Current time period D = Demand n = Number of periods (max) W = Weight, where greatest weight applies to most recent period and sum of weights = 1 Exercise: Work out forecast for two periods with weights of 0.4,0.6 What periods and weights will use for forecasting soap and fashion clothes Why? Supply Chain Engineering MN 799 49# Exponential Smoothing

 Decision þ Select or compute a smoothing constant ( ) þ Relationship of exponential smoothing to simple moving average

Formulas Where F = forecast value FT1FFT1 DT DDT(1(1(1)FT )FT T1 T T T = current time period or For F FF (D (D F)F ) orT 1FTT11 T FTT T (DT T FT ) D = demand  = exponential factor <1   2 Where n1 n = number of past periods to be captured

Supply Chain Engineering MN 799 50# Exponential Smoothing — Continued

FT+1 = FT + a (DT – FT)

Period Demand Forecast Forecast Forecast ( = .1) ( = .5) ( = .9) 0 180 start-up start-up start-up 1 160 180 180 180 2 220 178 170 162 3 200 182 195 214 4 260 184 198 201 5 240 192 229 254 6 196 234 241 Work out forecasts with =0.3 What ’s will use for forecasting soap and fashion clothes Why?

Supply Chain Engineering MN 799 51# Simple Trended Series — Example

 Algebraic Trend Projection X Y a. Trend (“rise” over “run”) = (13 - 4)/3 = 3 = b 0 4 b. Y-intercept (a) = “compute” 1 7 the Y value for X = 0, thus Y-int = 4 2 10 3 13 c. Period 4: Y = a + bX = 4 + 3 (4 [for period 4]) = 16

13 10 Rise 7

4 Run 1 2 3

Supply Chain Engineering MN 799 52# REGRESSION ANALYSIS • Regression formula b=slope, a=intercept

• Slope b= n XY   X  Y Intercept 2 2 a  Y - bX • and n X  ( X ) Y  a bX • Work out this example: • Year Variableb Y (Passengers) • 1 77 • 2 75 • 3 72 • 4 73 • 5 71 • What is the regression equation? What is the forecast for Year 6?

Supply Chain Engineering MN 799 53# TRENDED TIME SERIES FORECASTING

• Question: How do you forecast a seasonal item

• Y(forecast) = [A (intercept) + X (trend) x T (time period) ]

x S (seasonality factor) • FIRST DETERMINE LEVEL AND TREND - IF SEASONAL DESEASONALIZE • THEN FORECAST USING EXPONENTIAL OR TREND • RESEASONALIZE

Supply Chain Engineering MN 799 54# Seasonal Series Indexing

Seasonal Month Year 1 Year 2 Year 3 Total Index

Jan 10 12 11 33 0.33 Feb 13 13 11 37 0.37 Mar 33 38 29 100 1.00

Apr 45 54 47 146 1.46 May 53 56 55 164 1.64 Jun 57 56 55 168 1.68

Yr 1 Yr2 Jul 33 27 34 94 0.94 Aug 20 18 19 57 0.57 Sep 19 22 20 61 0.61

Oct 18 18 15 51 0.51 Nov 46 50 45 141 1.41 Dec 48 53 47 148 1.48 Total 395 417 388 1200 12.00

Supply Chain Engineering MN 799 55# Seasonal Series Indexing Sample Data — Continued 1. FIND SEASONALITY FOR EACH PERIOD 2. DEASONALIZE 3. PROJECT USING EXPONENTIAL, REGRESSION ETC 4. REASONALIZE Where: Monthly Total (MT) 1200 Formula: Seasonal Index (SI) = AM = = 100 Average Month (AM) 12

33 SI = = .33 JAN 100

94 SI = = .94 JUL 100

Supply Chain Engineering MN 799 56# Integrative Example: Calculating a Forecast with Seasonal Indexes and Exponential Smoothing  Given Deseasonalized Seasonal Demand Forecast Index July 34 36 0.94 Aug 0.57  Rationale and Computations 1. Deseasonalize current (July) actual demand Actual demand ActualActual demand demandActual  34/0.9434/0.94  demand34/0.9434 36.1736.17 34/0.9436.17 36.17 SeasonalSeasonalSeasonal index index Seasonalindex 0.94 index

2. Use exponential smoothing to project deseasonalized data one period ahead ( = .2)

FT  1   D T  (1   )FT  (0.2) (36.17)  (0.8) (36)  36.03 3. Reseasonalize forecast for desired month (August) = Deseasonalized forecast  seasonal factor = 36.03  0.57 = 20.53 or 21

Supply Chain Engineering MN 799 57# Exercise

• Boler Corp has the following sales history: • Quarter Year1 Year2 • 1 140 210 • 2 280 350 • 3 70 140 • 4 210 280 • What seasonal index for each quarter could be used to forecast the sales of the product for Year 3? • What would be a forecast for year 3 using an a=0.3 and assuming the forecast for year 2 was 1000? What would be the forecast for each quarter in this forecast?

Supply Chain Engineering MN 799 58# Normal Distribution Using the Measures of Variability

x 68.26%

95.44%

99.74%

Source: Adapted from CPIM Inventory Management Certification Review Course (APICS, 1998).

Supply Chain Engineering MN 799 59# Standard Deviation (sigma)

A = Error F= Actual (Sales – Error Period Forecast Sales Forecast) Square 1 1,000 1,200 200 d 40,000 2 1,000 1,000 0 0 3 1,000 800 – 200 40,000 4 1,000 900 – 100 10,000 5 1,000 1,400 400 160,000 6 1,000 1,200 200 40,000 7 1,000 1,100 100 10,000 8 1,000 700 – 300 90,000 9 1,000 1,000 0 0 10 1,000 900 – 100 10,000 10,000 10,200 200 400,000

Supply Chain Engineering MN 799 60# Standard Deviation — Continued

2 (A - F) Standard Deviation  i i 400,000 = = = 211 n - 1 9

2 ( - )  Ai Fi 400,000 Standard Deviation = = = 200 n 10

NOTE: About the use of n or n - 1 in the above equations

n Use with a large population (> 30 observations) n - 1 Use with a small population (< 30 observations)

Supply Chain Engineering MN 799 61# Bias and MAD

A = Error F = Actual (Sales – Absolute Period Forecast Sales Forecast) Error Cumulative sum of error = 1 1,000 1,200 200 200 2 1,000 1,000 0 0  (Ai  Fi )  200 3 1,000 800 – 200 200 4 1,000 900 – 100 100 Bias = 5 1,000 1,400 400 400 (A - F) 200  i i = = 20 6 1,000 1,200 200 200 n 10 7 1,000 1,100 100 100 8 1,000 700 – 300 300 Mean Absolute Deviation (MAD) 9 1,000 1,000 0 0 - 10 =  A i Fi = 1600 = 160 1,000 900 – 100 100 n 10 10,000 10,200 200 1,600

Supply Chain Engineering MN 799 62# Measures of Forecast Error  Cumulative Sum of Error  (A - F ) i i  Bias  (A i - F i ) n  Mean Absolute Deviation (MAD)  A i - F i n  Standard Deviation=1.25 MAD or 2 2 (A - F) (A - F)  i i or  i i NOTE: About the use of n or n-1 in the above equations n - 1 n n Use with a large population (> 30 observations) n-1 Use with a small population (< 30 observations)

Supply Chain Engineering MN 799 63# Confidence Intervals  Definition A confidence interval is a measure of distance, increments of which are represented by the z value  Formulas 2 2  (A - F)  (A - F ) s (1 Std Dev) = i i OR i i n -1 n

Distance - Mean x - x z = = i StandardDeviation s  Relationship or x i = x + z s  1 standard deviation (s) = 1.25  MAD  In the example data s = 1.25  MAD = 1.25  160 = 200 Source: Raz and Roberts, ―Statistics,‖ 1987

Supply Chain Engineering MN 799 64# Expressing z Values (for +ve probabilities)

Probabilit y Back

D +1 SD +2 SD +3 SD

Cumulative normal distribution from left side of distribution (x + z)

z .0 .1 .2 .3 .4 .5 .6 .7 .8 .9 0.0 .5000 .5398 .5793 .6179 .6554 .6915 .7257 .7580 .7881 .8159 1.0 .8413 .8643 .8849 .9032 .9192 .9332 .9452 .9554 .9641 .9713 2.0 .9773 .9821 .9861 .9893 .9918 .9938 .9953 .9965 .9974 .9981 3.0 .9987 .9990 .9930 .9995 .9997 .9998 .9998 .9999 .9999 .9999

Supply Chain Engineering MN 799 65# Application Problem — Service Level

 Given Average sales for item P is 50 units per week with a standard deviation of 4  Required What is the probability that more than 60 units will be sold?

a. .006 b. .494 c. .506 d. .994

Supply Chain Engineering MN 799 66# Homework

Q1 - 2. A demand pattern for ten periods for a certain product was given as 127, 113, 121, 123, 117, 109, 131, 115, 127, and 118. Forecast the demand for period 11 using each of the following methods: a three-month moving average, a three-month weighted moving average using weights of 0.2, 0.3, and 0.5, exponential smoothing with a smoothing constant of 0.3, and linear regression. Compute the MAD for each method to determine which method would be preferable under the circumstances. Also calculate the bias in the data, if any, for all four methods, and explain the meaning.

Q2 - The following information is presented for a product: • 2001 2002 • Forecast Demand Forecast Demand • Quarter I 200 226 210 218 Quarter II 320 310 315 333 • Quarter III 145 153 140 122 • Quarter IV 230 212 240 231 • a) What are the seasonal indicies that should be used for each quarter? • What is the MAD for the data above?

Supply Chain Engineering MN 799 67# Supply Chain Network Fundamentals

William T. Walker, CFPIM, CIRM, CSCP Practitioner, Author, and Supply Chain Architect

Supply Chain Engineering MN 799 68# Session Outline

• Understanding How Supply Chains Work • The Value Principle and Network Stakeholders • Mapping a Supply Chain Network • The Velocity and Variability Principles • Locating the Push/Pull Boundary • The Vocalize and Visualize Principles • Summary

Supply Chain Engineering MN 799 69# Learning Objectives

By teaching the principles of supply chain management to understand how a supply chain network works...

. We learn how to map a supply chain network.

. We learn how to engineer reliable network infrastructure by maximizing velocity and minimizing variability.

. We learn how the Bill Of Materials relates to the network.

. We learn how locating the push/pull boundary converts network operations from Build-To-Stock to Build-To-Order.

. We learn how to maximize throughput by engineering the means to vocalize demand and to visualize supply.

Supply Chain Engineering MN 799 70# A SUPPLY CHAIN is the global network used to deliver products and services from raw materials to end customers through engineered flows of information, material, and cash.

Contributed to the APICS Dictionary, 10th Edition by William T. Walker

Supply Chain Engineering MN 799 71# Network Terminology

"Source" "Make" "Deliver" "Return"

Upstream Midstream Downstream Reverse Stream Zone Zone Zone Zone Customer Physical Flow Info Flow Cash Flow

Value-Adding Value-Subtracting

Supply Chain Engineering MN 799 72# Supply Chain Network Operations

Material moves downstream to the customer. Cash moves upstream to the supplier.

Material M1 M2 M3

Supplier Trading Customer Partner

Cash $3 $2 $1

Supply Chain Engineering MN 799 73# The Value Principle: Every stakeholder wins when throughput is maximized.

Value is Return In Investment

Shareholders Value is Trading the Perfect Suppliers Value is Partner Customers Order Continuity of Demand Employees

Value is Employment Stability Supply Chain Engineering MN 799 74# The Network Rules In an effective supply chain network each trading partner works to...

. Maximize velocity, . Minimize variability, . Vocalize demand, and . Visualize supply

...in order to maximize throughput providing Value for each stakeholder.

However, a lack of trust often gets in the way.

Supply Chain Engineering MN 799 75# The Network Trust Factor Network trust is based upon personal relationships and the perception that things are okay regarding:

. Network operating rules are clear

. Supply and demand information is shared

. Performance measures are agreed upon

. Relationship non-disclosures are kept secret

. Inventory investment is not a win-lose game

Supply Chain Engineering MN 799 76# Bill Of Materials

Item Master Product Structure - Stock Keeping Unit (SKU) Number - Parent To Child Relationship - Description - Quantity Per Relationship - Unit Of Measure - Approved Supplier - Country Of Origin For Example - Cost Items: A3, B2, B5, C1, C2, C3, D1 - Lead Time Suppliers: S1, S2, S3, S4, S5

A3 BOM Level 0. S1

BOM Level 1. B5 B2 S2

BOM Level 2. C1 C2 C3 S4 S3 BOM Level 3. D1 S5

Supply Chain Engineering MN 799 77# Supply Chain Network Map

Upstream Midstream Downstream

Driven by the Bill Of Materials Driven by the Delivery Channel

Supply Chain Engineering MN 799 78# How To Map A Network

1. Start midstream and imagine finished goods sitting on a rack at the central depot. 2. Now, use the Bill Of Materials and work upstream to reach each raw material supplier. 3. Then, identify each different fulfillment channel used to reach the local mission. 4. Determine which organizations are trading partners versus nominal trading partners. 5. Logistics service providers, information service providers, and financial service providers are not part of the network map.

Supply Chain Engineering MN 799 79# The Velocity Principle:

In network implementation throughput is maximized when order-to-delivery-to-cash velocity is maximized by minimizing process cycle time.

The 5V Principles of Supply Chain Management explain how a supply chain network works by answering what, when, where, why, and how:

Velocity – how are relationships connected to make the delivery?

Supply Chain Engineering MN 799 80# The Network Flow Model

Material Material

Order-To-Stock Order-To-Delivery

Trading Supplier Info Info Customer Partner

Invoice-To-Cash Invoice-To-Pay Cash Cash

From: William T. Walker, Supply Chain Architecture: A Blueprint for Networking the Flow of Material, Information, and Cash, CRC Press, ©2005.

Supply Chain Engineering MN 799 81# Logistics Touches Every Subcycle

Order-To-Stock Order-To-Delivery

Invoice-To-Cash Invoice-To-Pay

. Transportation moves material from seller to buyer . In some cases orders/ invoices/ cash move by mail . Warehouse issues trigger invoices . Warehouse receipts trigger payments

Supply Chain Engineering MN 799 82# Import/ Export Boundaries

Return Imports Exports

Country A Seller Shipment Buyer Country B Exports Imports

Country A exports and Country B imports in a forward supply chain.

Country B exports and Country A imports in a reverse supply chain.

Import duty and export licensing add complexity to network linkages decreasing velocity and increasing variability.

Supply Chain Engineering MN 799 83# The Variability Principle:

In network implementation throughput is maximized when order-to-delivery-to-cash variability is minimized by minimizing process variance.

The 5V Principles of Supply Chain Management explain how a supply chain network works by answering what, when, where, why, and how:

Variability – what is likely to change from one delivery to the next?

Supply Chain Engineering MN 799 84# Outward Signs of Variability . Unplanned demand . Backordered inventory . Inventory leakage . Capacity constraints . Lower than normal yields . Longer than expected transit times . Delays in clearing Customs . Delayed payment

Supply Chain Engineering MN 799 85# To Maximize Velocity

. Eliminate unnecessary process steps . Shorten the longest serial process steps by eliminating queue time and automating steps . Convert serial process steps into parallel process steps

To Minimize Variability . Rank order the variances . Minimize the root cause of largest variance . Continue with the next largest variance, etc.

Supply Chain Engineering MN 799 86# Push/Pull Boundary

Order

Supply Push Pull Demand

Push/Pull Boundary

Forecast

Supply Chain Engineering MN 799 87# Customer Lead Time

Build-To-Order (BTO) Order

Push Pull Customer Demand Push/Pull F/C Boundary

Build-To-Stock (BTS) Order

Push Pull Customer Demand Push/Pull F/C Boundary

Supply Chain Engineering MN 799 88# How To Locate A Push/Pull Boundary

1. Know the competitive situation; for example, if competitive products are off-the-shelf, then the push/pull boundary must be close to the customer.

2. The push/pull boundary is a physical inventory location that bisects the entire supply chain.

3. Order-To-Delivery Cycle Time = Order Processing and Transmission Time + Shipment Processing, Picking, and Packing Time + Transportation and Customs Clearance Time

Supply Chain Engineering MN 799 89# The Vocalize Principle:

In network operations throughput is maximized by pulling supply to demand by vocalizing actual demand at the network constraint.

The 5V Principles of Supply Chain Management explain how a supply chain network works by answering what, when, where, why, and how:

Vocalize – who knows the full requirements of the order?

Supply Chain Engineering MN 799 90# Common Causes of Stockouts

Quantity Q Demand Uncertainty R SS Time L Quantity Lead Time Variability Q (LT = Cycle Time + Transit Time) R SS Time L Quantity Supply Uncertainty

Q R SS Time L Supply Chain Engineering MN 799 91# The Planning Interface

MRP Materials Sales & Operations Plan Push From Requirements Master Schedule Forecast

CRP Capacity Requirements Preload Inventory Pull To Capable Demand Network

Push Zone Pull Zone I C I C Throughput Push/Pull Boundary Upstream The Supply Chain Network Downstream

Supply Chain Engineering MN 799 92# Push Inventory And Capacity

Push Zone Forecast I C Throughput Safety Safety

Ending Inventory = Starting Inventory - Forecasted Demand + Production

When actual demand exceeds forecasted demand, either capacity or inventory can constrain production causing lead time to expand.

Supply Chain Engineering MN 799 93# Pull Inventory And Capacity

Pull Zone Order I C Max Max Throughput

Ending Inventory = Starting Inventory - Actual Demand + Production

Throughput is limited to the smaller of limited inventory or limited capacity.

Supply Chain Engineering MN 799 94# The Visualize Principle:

In network operations throughput is maximized by pushing supply to demand by visualizing actual inventory supply across the network.

The 5V Principles of Supply Chain Management explain how a supply chain network works by answering what, when, where, why, and how:

Visualize – where is the inventory now and when will it be available?

Supply Chain Engineering MN 799 95# Packaging And Labeling

[ ] Cartons, plastic cushions, and labels Cartons may be missing from the product BOM.

[ ] RFID/ bar code on all packaging.

[ ] Select a wall thickness and box burst Master strength to protect the product. Carton [ ] Keep Country Of Origin labeling consistent from the product to the outside packaging.

[ ] Transportation and warehousing costs Unit Load are a function of cubic dimensions and weight.

[ ] Items that have to be repalletized for or storage cost more.

Supply Chain Engineering MN 799 96# Track and Trace

Supply Chain Engineering MN 799 97# Apply Technology To Visualize

• Bar Code and 2D Bar Code

• Point Of Use Laser Scanners

• Radio Frequency Identification (RFID)

• Global Positioning by Satellite (GPS)

• Wireless Communication

Supply Chain Engineering MN 799 98# Measuring Network Inventory

Upstream Issues = Downstream Receipts Ending Inventory = Starting Inventory + Receipts – Issues Complete Products Reflect BOM Part Proportions

1. Look for leakages between upstream issues and downstream receipts. 2. Look for inventory balance discrepancies at each trading partner. 3. Look for process yield issues within each trading partner.

Supply Chain Engineering MN 799 99# To Vocalize

 Be precise about units and configurations  Acknowledge and handshake all information  Don't skip any link holding inventory in the chain

To Visualize

 Measure throughput rather than production  Measure the network capacity constraint  Measure total network inventory

Supply Chain Engineering MN 799 100#

In Summary Work the 5V Principles to maximize throughput.

I win!

Shareholders

Trading We win! Suppliers Customers We win! Partner Employees

I win!

Supply Chain Engineering MN 799 101# AGGREGRATE PLANNING (Chap8) Lesson 5

• PROCESS OF DETERMINING LEVELS OF – PRODUCTION RATE – WORKFORCE – OVERTIME – MACHINE CAPACITY – SUBCONTRACTING – BACKLOG – INVENTORY • GIVEN DEMAND FORECAST – DETERMINE PRODUCTION, INVENTORY/BACKLOG AND CAPACITY LEVEL FOR EACH PERIOD • FUNDAMENTAL TRADE-OFFS – CAPACITY(REGULAR TIME, OVERTIME, SUBCONTRACING)/COST – INVENTORY/SERVICE LEVEL – BACKLOG/LOST SALES

Supply Chain Engineering MN 799 102# AGGREGRATE PLANNING STRATEGIES • STRATEGIES - SYNCHRONIZING PRODUCTION WITH DEMAND – CHASE- USING CAPACITY AS THE LEVER • BY VARYING MACHINE OR WORKFORCE (numbers or flexibility) • DIFFICULT TO IMPLEMENT AND EXPENSIVE. LOW LEVELS OF INVENTORY – TIME FLEXIBILITY – UTILIZATION AS THE LEVER • IF EXCESS MACHINE CAPACITY, VARYING HOURS WORKED (workforce stable, hours vary) • LOW INVENTORY AND LOWER UTILISATION THAN CHASE • USEFUL WHEN INVENTORY COST HIGH AND CAPACITY CHEAP – LEVEL – USING INVENTORY AS THE LEVER • STABLE WORKFORCE AND CAPACITY • LARGE INVENTORIES AND BACKLOGS • MOST PRACTICAL AND POPULAR

Supply Chain Engineering MN 799 103# SOP FORMAT

PERIOD 1 2 3 4 5 6

SALES

PRODUCTION

INVENTORY/ BACKLOG

• PRODUCTION PLAN = SALES + END INV – BEGIN INV • PRODUCTION PER MONTH = PRODUCTION PLAN NUMBER OF PERIODS • PRODUCTION PLAN = SALES – END BACKLOG + BEGIN BACKLOG

Supply Chain Engineering MN 799 104# Sales and Operations Planning Strategies

Total annual (or period) 0 1 2 3 4 5 6 7 8 9 10 11 12 units Level Method Production 20 20 20 20 20 20 20 20 20 20 20 20 240 Sales 5 5 5 15 25 35 35 35 35 25 15 5 240 Inventory 30 45 60 75 80 75 60 45 30 15 10 15 30 540 Capacity  ------0 Chase Strategy Production 5 5 5 15 25 35 35 35 35 25 15 5 240 Sales 5 5 5 15 25 35 35 35 35 25 15 5 240 Inventory 30 30 30 30 30 30 30 30 30 30 30 30 30 360 Capacity  - - - 1 1 1 - - - 1 1 1 6

Master Planning, Rev. 4.2

Supply Chain Engineering MN 799 105# Production Rates and Levels Application 1 — Make-to-Stock

• Table Format (Inventory) Period 0 1 2 3 4 Forecast 150 150 150 150 Production plan Inventory 200 100

FOR A LEVEL STRATEGY, WORK OUT THE PRODUCTION PLAN AND INVENTORY BY PERIOD

PRODUCTION = SALES + END INV – BEGIN INV

Supply Chain Engineering MN 799 106# Production Rates and Levels Application 2 — Make-to-Order

• Table Format (Backlog) Period 0 1 2 3 4 Forecast 150 150 150 150 Production plan Backlog 200 100

FOR A LEVEL STRATEGY WORK OUT THE PRODUCTION PLAN AND BACKLOG BY PERIOD

PRODUCTION = SALES + BEGIN BL - END BL

Supply Chain Engineering MN 799 107# OPTIMIZATION THRU LINEAR PROGRAMMING

• AGGREGATE PLANNING MODEL – RED TOMATO Pp 210 (105) – MAXIMIZING HIGHEST PROFIT OVER TIME PERIOD – DETERMINE DECISION VARIABLES PP212(107) – OBJECTIVE FUNCTION – MINIMIZE TOTAL COST • DEVELOP EQUATIONS FOR ALL THE COST ELEMENTS- Eq 5/8.1 – CONSTRAINTS EQUATIONS • WORKFORCE • CAPACITY • INVENTORY • OVERTIME – OPTIMIZE OBJECTIVE FUNCTION – FORECAST ERROR • SAFETY INVENTORY • SAFETY CAPACITY

Supply Chain Engineering MN 799 108# Excel File

Aggregate Planning (Define Decision Variables)

Wt = Workforce size for month t, t = 1, ..., 6

Ht = Number of employees hired at the beginning of month t, t = 1, ..., 6

Lt = Number of employees laid off at the beginning of month t, t = 1, ..., 6

Pt = Production in month t, t = 1, ..., 6

It = Inventory at the end of month t, t = 1, ..., 6

St = Number of units stocked out at the end of month t, t = 1, ..., 6

Ct = Number of units subcontracted for month t, t = 1, ..., 6

Ot = Number of overtime hours worked in month t, t = 1, ..., 6

Supply Chain Engineering MN 799 109# Aggregate Planning 8.2

Item Cost Materials $10/unit Inventory holding cost $2/unit/month Marginal cost of a stockout $5/unit/month Hiring and training costs $300/worker Layoff cost $500/worker Labor hours required 4/unit Regular time cost $4/hour Over time cost $6/hour Cost of subcontracting $30/unit

DEMAND Table 8.1 (5.1)

Supply Chain Engineering MN 799 110# Aggregate Planning (Define Objective Function) Monthly

6 6 Min640W t  300 H t t1 t1 6 6 6  500 Lt  6Ot  2I t t1 t1 t1 6 6 6  5St  10 Pt  30Ct t1 t1 t1

Supply Chain Engineering MN 799 111# Aggregate Planning (Define Constraints Linking Variables) • Workforce size for each month is based on hiring and layoffs

W t  W t1  H t  Lt, or

W t W t1  H t  Lt  0

for t 1,...,6, where W 0  80.

Supply Chain Engineering MN 799 112# Aggregate Planning (Constraints)

• Production for each month cannot exceed capacity

Pt  40W t  Ot 4,

40W t  Ot 4  Pt  0, for t 1,...,6.

Supply Chain Engineering MN 799 113# Aggregate Planning (Constraints)

• Inventory balance for each month

I t1  Pt  Ct  Dt  S t1  I t  S t ,

I t1  Pt  Ct  Dt  S t1  I t  S t  0, for t 1,...,6,where I 0 1,000,

S 0  0,and I 6  500.

Supply Chain Engineering MN 799 114# Aggregate Planning (Constraints)

• Over time for each month

Ot 10W t,

10W t Ot  0, for t 1,...,6.

Supply Chain Engineering MN 799 115# SOLVING PROBLEM USING EXCEL • STEP 1 BUILD DECISION VARIABLE TABLE (fig8.1) – ALL CELLS 0, EXCEPT PERIOD 0 FOR WORKFORCE AND INVENTORY – ENTER DEMAND (TABLE 8.4) • STEP 2 CONSTRUCT CONSTRAINT TABLE (fig8.2) • STEP 3 CREATE a CELL HAVING THE OBJECTIVE FUNCTION – (Formula 8.1) Optimizing TOTAL COSTS (Fig 8.3) • STEP 4 USE TOOLS SOLVER (Fig 8.4) • REPEAT IF OPTIMUM SOLUTION NOT OBTAINED

• HOMEWORK (see homework)

Supply Chain Engineering MN 799 116# AGGREGATE PLANNING IN PRACTICE

• MAKE PLANS FLEXIBLE BECAUSE FORECASTS ARE ALWAYS WRONG – PERFORM SENSITIVITY ANALYSIS ON THE INPUTS – I.E. LOOK AT EFFECTS OF HIGH/LOW • RERUN THE AGGREGATE PLAN AS NEW DATA EMERGES • USE AGGREGATE PLANNING AS CAPACITY UTILIZATION INCREASES – WHEN UTILIZATION IS HIGH, THERE IS LIKELY TO BE CAPACITY LIMITATIONS AND ALL THE ORDERS WILL NOT BE PRODUCED

Supply Chain Engineering MN 799 117# Process Flow Measures

• FLOW RATE (Rt), CYCLE TIME (Tt), & INVENTORY (It) RELATIONSHIPS – F = Flow Rate or Throughput is output of a line in pieces per time – T = Cycle time is the time taken to complete an operation – I = Inventory is the material on the line – LITTLE’s LAW: Av. I = Av. R x Av. T x Variability factor Examples: • If Inventory is 100 pieces and Cycle time is 10 hours, the Throughput rate is 10 pcs per hour • If Cycle time is halved; Throughput is doubled • If Inventory is halved; cycle time is halved See Equation 8.6 How do we get Av Inv of 895 and Flow time of 0.34 months on page 227/216

Supply Chain Engineering MN 799 118# Homework

• Ex. Work out Inventory, Rate and cycle time for values in Tables 8.4,8.5

Supply Chain Engineering MN 799 119# Supply Chain Network Basics – Lesson 4

• Guest Lecture – go to Poly Blackboard

Supply Chain Engineering MN 799 120# MANAGING SUPPLY AND DEMAND PREDICTABLE VARIABILITY (LESSON 6) • Predictable Variability – Change in Demand that can be forecast or guided – MANAGING DEMAND – Short time price discounts, trade promotions • MANAGING SUPPLY – Capacity, Inventory, Subcontracting & Backlog, Purchased product – MANAGING CAPACITY • TIME FLEXIBILITY FROM WORKFORCE (OVERTIME) • USE OF SEASONAL WORKFORCE • USE OF SUBCONTRACTING • USE OF DUAL FACILITIES – DEDICATED AND FLEXIBLE • DESIGN PRODUCT FLEXIBILITY INTO PRODUCTION • USE OF MULTI-PURPOSE MACHINES (CNC MACHINE CENTERS) – MANAGING INVENTORY • USING COMMON COMPONENTS ACROSS MULTIPLE PRODUCTS • BUILD INVENTORY OF HIGH DEMAND OR PREDICTABLE DEMAND PRODUCTS

Supply Chain Engineering MN 799 121# MANAGING DEMAND (Predictable Variability) • Manage demand with pricing – Factors influencing the timing of a promotion: • Impact on demand; product margins; cost of holding inventory; cost of changing capacity • Demand increase (from discounting) due to: – Market growth – Stealing market share – Forward buying Discount of $1 increases period demand by 10% Reduce price by $1 in Jan, increases sales by 10% in first month - Tab 9.4, 9.5 – effect on cost, profit, inventory If discount is in April, highest demand month - Tab 9.6, 9.7 • See the effects of various combination Tab 9-12 • Summary Tab 9.12 & 9.13 Discuss

Supply Chain Engineering MN 799 122# PREDICTABLE VARIABILITY IN PRACTICE

• COORDINATE MARKETING, SALES AND OPERATIONS – SALES AND OPERATIONS PLANNING – ONE GOAL MAXIMIZING PROFIT, ONE GAME PLAN • TAKE PREDICABLE VARIABILITY INTO ACCOUNT WHEN MAKING STRATEGIC DECISIONS • PARTNER WITH PRINCIPAL CUSTOMERS, ELIMINATE PREDICTIONS! • PREEMPT (PROMOS ETC.), DO NOT JUST REACT TO PREDICTABLE VARIABILITY

Supply Chain Engineering MN 799 123# MANUFACTURING - MANAGING LEAD TIME

• CRITICAL DRIVER OF ALL MANUFACTURE – LAYOUT AND WORKPLACE ORGANIZATION – CONSTRAINT MANAGEMENT – VARIABILITY AND QUEUES – LOT SIZES AND SET UP REDUCTION – WORK IN PROCESS – FLEXIBILITY • MUST BE COMPANY FOCUS • MEASURED AND MONITORED – X BUTT TO BUTT

Supply Chain Engineering MN 799 124# MANAGING INVENTORY

• The role of inventory in the supply chain – Cycle Inventory (making or purchasing inventory in large lots) takes advantage of economies of scale to lower total cost – material cost, fixed ordering cost and holding cost. • Why hold inventory? – Economies of scale • Batch size and cycle time • Quantity discounts • Short term discounts / Trade promotions – Stochastic variability of supply and demand • Evaluating service level given safety inventory • Evaluating safety inventory given desired service level • Levers to improve performance

Supply Chain Engineering MN 799 125# Role of Inventory in the Supply Chain

• Overstocking: Amount available exceeds demand – Liquidation, Obsolescence, Holding • Understocking: Demand exceeds amount available – Lost margin and future sales

Goal: Matching supply and demand

Supply Chain Engineering MN 799 126# ROLE OF CYCLE INVENTORY (10.1)

• Q – lot or batch size of an order • D – Demand • When demand steady : Cycle Inven = lot size/2 = Q/2 Saw tooth diagram • Average flow time = cycle inven / demand = Q/2D

• C – material cost • S – fixed ordering cost • H – holding cost • h – cost of holding $1 in inventory for one year • H = hC cost of holding one piece for one year

Supply Chain Engineering MN 799 127# Cycle Inventory related costs in Practice • Inventory holding costs – usually expressed as a % per $ per year – Cost of capital (Opportunity cost of capital) – Obsolescence or spoilage cost – Handling cost – Occupancy cost (space cost) – Miscellaneous costs (security, insurance) • Order costs (same as set up costs in a machining environment) – Buyer time – Transportation costs – Receiving costs – Other costs • Cycle Inventory exists in a supply chain because different stages exploit economies of scale to lower total cost – material cost, fixed ordering cost and holding cost Supply Chain Engineering MN 799 128# Fixed costs: Optimal Lot Size and Reorder Interval (EOQ) C: Cost per unit ($C/unit) h: Holding cost per year as a fraction of product cost ($%/unit/Year) H: Holding cost per unit per year H  hC Q: Lot Size D: Annual demand S: Setup or Order Cost 2DS Annual order cost = (D/Q)S Q  Annual inventory cost = (Q/2)hC H Optimum Q =  2DS/hC T: Reorder interval (Q/D) # orders/yr = D/Q = Optimal order freq 2S Total Annual Cost = CD+(D/Q)S+(Q/2)hC T  See Fig 10-2 Showing effects of Lot Size DH

Supply Chain Engineering MN 799 129# Example 10.1

Demand, D = 12,000 computers per year Unit cost, C = $500 Holding cost, h = 0.2 Fixed cost, S = $4,000/order What is the order quantity Q, the flow time, the reorder interval and Total cost? Q = 980 computers Cycle inventory = Q/2 = 490 Flow time = Q/2D = 0.049 month Reorder interval, T = 0.98 month Total Cost = 49,000 + 49,000 + 6,000,000 = $6,098,000

Supply Chain Engineering MN 799 130# EXPLOITING ECONOMIES OF SCALE • SINGLE LOT SIZE OF SINGLE PRODUCT (EOQ) = Q – ANNUAL MATERIAL COST = CD – NO. OF ORDERS PER YEAR = D/Q – ANNUAL ORDER COST = (D/Q)*S – ANNUAL HOLDING COST = (Q/2)H = (Q/2)hC – TOTAL ANNUAL COST (TC) = CR+(D/Q)*S+(Q/2)hC – Optimal lot size Q* = 2DS/hC – Optimal ordering frequency = n* = D/Q* = DhC/2S – Key Point: Total Ordering and Holding costs are relatively stable around the EOQ and a convenient lot size around the EOQ is OK (rather than a precise EOQ) – Key Point: If demand increases by a factor of k, the optimal lot size and no of orders increases by a factor of k. Flow time decreases by a factor of k – Key point: To reduce Q by a factor of k, fixed cost S must be reduced by a factor of k2

Supply Chain Engineering MN 799 131# Reducing Lot Size - Aggregating

• Exercise: • To reduce Q from 980 to 200, how much must order cost be reduced • Key point: To reduce Q by a factor of k, fixed cost S must be reduced by a factor of k2

Supply Chain Engineering MN 799 132# LOT SIZING WITH MULTIPLE PRODUCTS & CUSTOMERS

• Lot sizing with Multiple Product or Customers – Aggregating replenishment across products, retailers or suppliers in a single order, allows for a reduction in lot sizes because fixed costs spread across multiple products and – Ordering and delivering independently (See Ex.10.3) • Each order has independent Holding, Ordering and Annual costs with independent EOQ‘s and Flow Times – Table 10-1 • Total cost = $155,140 – Total cost Ordered and delivered jointly (See Ex.10.4) • Independent holding costs but combined fixed order cost Table 10-2 • Total Cost = $136,528 – Transportation capacity constraint – aggregating multiple products from same supplier; single delivery from multiple suppliers (Ex. 10-5) • Key Point –The key to reducing cycle inventory is reducing lot size. The key to reducing lot size without increasing costs is to reduce fixed costs associated with each lot – by reducing the fixed cost itself or aggregating lots across multiple products, customers or suppliers. We reduce lot size to reduce cycle time

Supply Chain Engineering MN 799 133# Impact of product specific order cost Tailored aggregation – Higher volume products ordered more frequently and lower volume products ordered less frequently (rather than ordered and delivered jointly) 10-6 Summary Total Costs Product specific order cost = $1000 No $155,140 (10-3) Aggregation Complete $136,528 (10-4) Aggregation Tailored $130,767 (10-6) Aggregation

Supply Chain Engineering MN 799 134# Delivery Options

• No Aggregation: Each product ordered separately • Complete Aggregation: All products delivered on each truck • Tailored Aggregation: Selected subsets of products on each truck

Supply Chain Engineering MN 799 135# Economies of Scale to exploit Quantity Discounts

• Two common Lot Size based discount schemes – All unit quantity discounts • Pricing based on specific quantity break points – Marginal unit quantity discounts or multiblock tariffs • Pricing based on quantity break points, but the price is not the average per block, but the marginal cost of a unit that decreases at breakpoint – See example in book on these discounts pages 276-280

Supply Chain Engineering MN 799 136# WHY QUANTITY DISCOUNTS

– Improved coordination to increase total supply chain profits • Commodity Products = price set by market. • Large Manufacturers should use lot based quantity discounts, to maximize profits (cycle inventory will increase) • The supply chain profit is lower if each stage makes pricing decisions independently, maximizing its own profit • Coordination to maximize profit – Two part tariff or quantity discounts – supplier passes on some of the profit to the retailer, depending on volume – Extraction of surplus through price discrimination – Trade Promotions – Lead to significant forward buying by the retailer – Retailer should pass on optimal discount to customer and keep rest for themselves

Supply Chain Engineering MN 799 137# Quantity Discounts

• Discounts improve coordination between Supplier and Retailer to maximize Supply Chain profits. • Quantity Discounts are a form of manufacturer returning some reduced costs (less orders) to the retailer (costs increase as more holding costs) • Supply chain profit is lower, if each stage of supply chain independently makes its pricing decisions with the objective of maximizing its own profit. A coordinated solution results in higher profit • For products that have market power, two-part tariffs or volume based quantity discounts can be used to achieve coordination in the supply chain and maximize profits • Promotions lead to significant increase in lot size and cycle inventory, because of forward buying by the retailer. This generally reduces the supply chain profits 280-281

Supply Chain Engineering MN 799 138# Strategies for reducing fixed costs

• Wal-Mart: 3 day replenishment cycle • Seven Eleven Japan: Multiple daily replenishment • P&G: Mixed truck loads • Efforts required in: – Transportation (Cross docking) – Information – Receiving Aggregate across products, supply points, or delivery points in a single order, allows reduction of lot size for individual products Ex 10.6

Supply Chain Engineering MN 799 139# ESTIMATING CYCLE INVENTORY COSTS

• HOLDING COSTS – Cost of capital – Obsolescence or spoilage costs – Handling costs – Occupancy cost – Miscellaneous • Order Cost – Buyer time – Transportation costs – Receiving costs – Other costs

Supply Chain Engineering MN 799 140# Lessons From Aggregation • Key to reducing cycle inventory is reducing lot size. Key to reducing lot size without increasing costs is to reduce the fixed cost itself by aggregation (across multiple products, customers or suppliers) • Aggregation allows firm to lower lot size without increasing cost • Complete aggregation is effective if product specific fixed cost is a small fraction of joint fixed cost • Tailored aggregation is effective if product specific fixed cost is large fraction of joint fixed cost

Supply Chain Engineering MN 799 141# Lessons From Discounting Schemes

• Lot size based discounts increase lot size and cycle inventory in the supply chain • The supply chain profit is lower if each stage independently makes pricing decisions with the objective of maximizing its own profit. Coordinated solution results in higher profit • Lot size based discounts are justified to achieve coordination for commodity products – competitive market and price fixed by market • Volume based discounts with some fixed cost passed on to retailer are more effective in general – Volume based discounts are better over rolling horizon

Supply Chain Engineering MN 799 142# Levers to Reduce Lot Sizes Without Hurting Costs

• Cycle Inventory Reduction – Reduce transfer and production lot sizes • Aggregate fixed cost across multiple products, supply points, or delivery points – Are quantity discounts consistent with manufacturing and logistics operations? • Volume discounts on rolling horizon • Two-part tariff – volume based discount in stages – Are trade promotions essential? • EDLP (Every day low pricing) • Base on sell-thru (customers) rather than sell-in (retailers) • HOMEWORK • EXERCISES 1 AND 2 Pp291/297

Supply Chain Engineering MN 799 143# Discussions on Site Visit • Macy‘s Distribution Center (DC) • In teams please answer the following: – What is the size of the operation – What strategy do they adopt and why – What are the key competitive practices – How do they deal with each of the Supply Chain Drivers • Measurements used for efficiency?

• How can they improve their operations?

Supply Chain Engineering MN 799 144# Mid Term • Show your calculations • Do not get stuck on any question 1. Strategy applications and implications 15 2. Demand Management 20 3. Aggregate Demand 20 4. Cycle Inventory 20 5. Supply Chain Networks 25

Supply Chain Engineering MN 799 145# Role of Inventory in the Supply Chain (LESSON 7)

Improve Matching of Supply and Demand Improved Forecasting

Reduce Material Flow Time

Reduce Waiting Time

Reduce Buffer Inventory

Supply / Demand Seasonal Economies of Scale Variability Variability

Cycle Inventory Safety Inventory Seasonal Inventory Figure Error! No text of Supply Chain Engineering MN 799 146# WHY HOLD SAFETY INVENTORY? (SAFETY STOCK) • DEMAND UNCERTAINTY • SUPPLY UNCERTAINTY • TODAY‘S ENVIRONMENT – INTERNET MAKES SEARCH EASIER – PRODUCT VARIETY GROWN WITH CUSTOMIZATION – EASE AND VARIETY PUTS PRESSURE ON PRODUCT AVAILABILITY – PUSH UP LEVELS OF INVENTORY / SAFETY STOCK • KEY QUESTIONS – APPROPRIATE LEVEL OF SAFETY STOCK – WHAT ACTIONS IMPROVE AVAILABILITY AND REDUCE SAFETY STOCK? Measures of product availability – Product fill rate (fr) – Order fill rate – Cycle service level (CSL) - THIS COURSE WILL DEAL mainly WITH CSL

Supply Chain Engineering MN 799 147# Lot Size = Q Inventory Cycle Inventory Q/2 ROP

Safety Stock SS = ROP - DL

Demand during Time Lead time APPROPRIATE LEVEL OF SAFETY STOCK DEPENDS ON: UNCERTAINTY OF DEMAND OR SUPPLY REPLENISHMENT LEAD TIME & DESIRED SERVICE LEVEL CSL – Cycle service level -CSL is the fraction of replenishment cycles that end with all the customer demand being met. A replenishment cycle is the interval between two successive replenishment deliveries

Supply Chain Engineering MN 799 148# Replenishment policies • Replenishment policies – When to reorder? – How much to reorder? Continuous Review: Order fixed quantity when total inventory drops below Reorder Point (ROP) Periodic Review: Order at fixed time intervals to raise total inventory to Order up to Level (OUL) Factors driving safety inventory – Demand and/or Supply uncertainty – Desired level of product availability – Replenishment lead time • Demand Uncertainty– Av.Demand; Stnd Devn; Lead Time

Supply Chain Engineering MN 799 149# Continuous Review Policy: Safety Inventory and Cycle Demand Uncertainty & Service Level

L: Lead time for replenishment SS = ROP - RL D: Average demand per unit time sD:Standard deviation of demand Average Inventory = Q/2 + SS per period

DL : Mean demand during lead time sL: Standard deviation of demand during lead time CSL: Cycle service level – Probability of not stocking out in replenishment cycle SS: Safety inventory ROP: Reorder point Cv: Coefficient of variance

Supply Chain Engineering MN 799 150# FORMULAS USED FOR CALCULATING SERVICE LEVELS

 LD DL  L s L s D ROP   ss DL CSL  F(ROP, , ) DL s L cv  s / 

CSL  F(ROP, DL, )  NORMDIST(ROP, , ,1) s L DL s L fr1 ESC / Q  (Q  ESC) / Q orESC  (ss[1 NORMDIST(ss / ,0,1,1] NORMDIST(ss / ,0,1,1) s L s L s L

Supply Chain Engineering MN 799 151# Example 11.1&2, 11.4 (Continuous Review Policy) = 8.xx New book

11.1: R = 2,500 /week; sR = 500 L = 2 weeks; Q = 10,000; ROP = 6,000 CSL = 90%

SS = ROP - DL = Average Inventory = Z Chart Average Flow Time = 11.2: Evaluating CSL given a replenishment policy CSL = Prob (demand during lead time <= ROP) Distribution of demand during lead time of 2 weeks

 DL DL Cycle service level, CSL = F(RL + ss, RL , sL ) = F(ROP, RL , sL )  L s L s D Excel: NORMDIST (ROP, RL , sL ,1)

X1= Xbar + Z sL or ROP = RL + Z sL Calculate the % z represents. Calculate Safety Stock for above

Supply Chain Engineering MN 799 152# Examples of Safety Stock Calculations

• Weekly demand for Lego at Wal Mart is normally distributed with a mean of 2500 boxes and a standard deviation of 500. The replenishment lead time is 2 weeks. Assuming a continuous replenishment policy, evaluate the safety inventory that the store should carry to achieve a cycle service of 90 percent

Supply Chain Engineering MN 799 153# Factors Affecting Fill Rate • Fill Rate: Proportion of customer demand that is satisfied from Inventory. Directly related to CSL • Safety inventory: Safety inventory is increased by: – Increasing fill rate (Table 11-1) – Increasing CSL – Increasing supplier lead time by factor k – SS increases by factor of SQRT k – Increasing standard deviation of demand by factor k – SS increases by factor of k • Lot size: Fill rate increases on increasing the lot size even though cycle service level does not change.

Actions: 1. Reduce supplier Lead Time L

2. Reduce underlying uncertainty of demand sR

Supply Chain Engineering MN 799 154# Evaluating Safety Inventory Given Fill Rate Required safety stock grows rapidly with increase in the desired Product availability

Fill Rate Safety Inventory 97.5% 67 98.0% 183 98.5% 321 99.0% 499 99.5% 767

The required SS grows rapidily with increase in desired Fill Rate The required SS increases with increase in Lead time and the σ of demand

Supply Chain Engineering MN 799 155# Impact of Supply Uncertainty

Considering variation in Demand and in Replenishment Lead time (Ex 11.6) • D: Average demand per period

• sD: Standard deviation of demand per period • L: Average lead time for replenishment

• sL: Standard deviation of supply lead time

Mean demand  DL during lead time DL

Standard Deviation 2 2 2 of demand during lead time  Ls D  s L D sL

Supply Chain Engineering MN 799 156# Impact of Supply Uncertainty ((See Ex. 11.6 & Table 11.2)

Ex.11.6: R = 2,500/day; sR = 500; L = 7 days; Q = 10,000;

CSL = 0.90 (z=1.29); sL = Standard Deviation of lead time=7days What is S.S? Large potential benefits of reducing Lead time or lead time variability in reduction of Safety stock

SS units SS (d) Stnd Dev(sL )

Safety inventory when sL = 0 1,695 0.68 1,323 Safety inventory when sL = 1 3,625 1.45 2,828 Safety inventory when sL = 2 6,628 2.65 5,172 Safety inventory when sL = 3 9,760 3.90 7,616 Safety inventory when sL = 4 12,927 5.17 10,087 Safety inventory when sL = 5 16,109 6.44 12,750 Safety inventory when sL = 6 19,298 7.72 16,109 Safety inventory when sL = 7 is 22,491 8.99 17,550

Supply Chain Engineering MN 799 157# Basic Quick Response Initiatives

• Reduce information uncertainty in demand • Reduce replenishment lead time • Reduce supply uncertainty or replenishment lead time uncertainty • Increase reorder frequency or go to continuous review

Supply Chain Engineering MN 799 158# Factors Affecting Value of Aggregation • DEMAND CORRELATION – – AS CORRELATION INCREASES, THE SS BENEFIT OF AGGREGRATION DECREASES – IF THERE IS LITTLE CORRELATION BETWEEN DEMAND, AGGREGRATION REDUCES STND. DEVN. OF DEMAND AND HENCE SAFETY STOCK (see ex. 11.7, Table 11.3) • Coefficient Of Variation = Stnd Devn/Mean (uncertainty relative to size of demand) p=0 No Correlation – THE HIGHER THE COEFFICIENT OF VARIATION OF AN ITEM, THE GREATER THE REDUCTION IN SAFETY STOCK AS A RESULT OF CENTRALIZATION (LOW COEFFICIENT OF VARIATION ALLOW ACCURATE FORECASTING AND DECENTRALIZED STOCKING) • REDUCING SUPPLY VARIATION REDUCES SAFETY STOCK WITHOUT REDUCING CSL • VALUE OF A PRODUCT – DIRECTLY DETERMINES THE SAFETY STOCK LEVEL

Supply Chain Engineering MN 799 159# IMPACT OF AGGREGRATION ON SAFETY STOCK • HOW TO REDUCE SS WITHOUT REDUCING CSL? – AGGREGRATION REDUCES STANDARD DEVIATION OF DEMAND, ONLY IF DEMAND ACROSS AREAS IS NOT CORRELATED, THAT IS EACH AREA IS INDEPENDENT • See Table 11.4 p323 – AGGREGRATION REDUCES SS BY THE SQRT OF NUMBER OF AREAS AGGREGRATED (REDUCING NUMBER OF STOCKING LOCATIONS)– SQUARE ROOT LAW (Ex. AMAZON) See Fig 11.4 – INFORMATION CENTRALIZATION – ORDERS FILLED FROM WAREHOUSE CLOSEST TO CUSTOMER – SPECIALIZATION BY LOCATION • LOW DEMAND, SLOW MOVING ITEMS: CENTRALIZED – HIGH COEFFICIENT OF VARIATION • HIGH DEMAND, FAST MOVING ITEMS: DECENTRALIZED – LOW COEFFICIENT OF VARIATION – Centralization Disadvantage: • Increase in Response time; • Increase in Transport costs

Supply Chain Engineering MN 799 160#

IMPACT OF AGGREGRATION ON SAFETY STOCK

• HOW TO REDUCE SS WITHOUT REDUCING CSL? – PRODUCT SUBSTITUTION • MANUFACTURER DRIVEN – AGGREGATE DEMAND & REDUCE SS; • IF PRODUCTS STRONGLY CORRELATED, LESS VALUE IN SUBSTITUTION • CUSTOMER DRIVEN – TWO WAY SUBSTITUTION – ALLOWS REDUCTION IN SS WHILE MAINTAINING HIGH PRODUCT AVAILABILITY • GREATER THE VARIABILITY AND LESS THE CORRELATION OF DEMAND, THE GREATER THE BENEFIT IN SUBSTITUTION – COMPONENT COMMONALITY (TABLE 11.5) • WITHOUT COMMONALITY, UNCERTAINTY OF DEMAND FOR COMPONENTS SAME AS THAT FOR PRODUCT (SEE Ex. 11.9) – POSTPONMENT • DELAY DIFFERENTIATION OR CUSTOMIZATION AS CLOSE TO SALE TIME AS POSSIBLE – COMMON COMPONENTS IN PUSH PHASE – POWERFUL CONCEPT FOR E-COMMERCE

Supply Chain Engineering MN 799 161# Example 11.9: Value of Component Commonality Y Axis – SS Quantity; X Axis – No. of common components 450000 400000 350000 300000 250000 SS 200000 150000 100000 50000 0 1 2 3 4 5 6 7 8 9 Without component commonality and postponment, product differentiation Occurs early in the Supply Chain and inventories are disaggregate Supply Chain Engineering MN 799 162# ESTIMATING AND MANAGING SS IN PRACTICE

• ACCOUNT FOR LUMPY SUPPLY CHAIN DEMAND – CAUSED BY LARGE LOT SIZES & ADDS TO VARIABILITY – EMPIRICALLY – RAISING SS BY HALF LOT SIZE • ADJUST INVENTORY POLICY IF DEMAND SEASONAL – CHANGE BOTH MEAN AND STND DEVN • USE SIMULATION TO TEST INVENTORY POLICIES – EXCEL • START WITH A PILOT • MONITOR SERVICE LEVELS • FOCUS ON REDUCING SAFETY STOCK • PERIODIC REVIEW REPLENISHMENT REQUIRES MORE SAFETY STOCK THAN CONTINUOUS REVIEW POLICIES

Supply Chain Engineering MN 799 163# Mass Customization I: Customize Services Around Standardized Products

Source: B. Joseph Pine

DEVELOPMENT PRODUCTION MARKETING DELIVERY

Deliver customized services as well as standardized products and services Market customized services with standardized products or services Continue producing standardized products or services Continue developing standardized products or services Supply Chain Engineering MN 799 164# Mass Customization II: Create Customizable Products and Services

DEVELOPMENT PRODUCTION MARKETING DELIVERY

Deliver standard (but customizable) products or services Market customizable products or services

Produce standard (but customizable) products or services Develop customizable products or services Supply Chain Engineering MN 799 165# Mass Customization III: Provide Quick Response Throughout Value Chain

DEVELOPMENT PRODUCTION MARKETING DELIVERY

Reduce Delivery Cycle Times Reduce selection and order processing cycle times Reduce Production cycle time

Reduce development cycle time Supply Chain Engineering MN 799 166# Mass Customization IV: Provide Point of Delivery Customization Mens Warehouse and Restaurants

DEVELOPMENT PRODUCTION MARKETING DELIVERY

Point of delivery customization

Deliver standardize portion

Market customized products or services

Produce standardized portion centrally

Develop products where point of delivery customization is feasible Supply Chain Engineering MN 799 167# Mass Customization V: Modularize Components to Customize End Products

Autos

DEVELOPMENT PRODUCTION MARKETING DELIVERY

Deliver customized product

Market customized products or services

Produce modularized components

Develop modularized products Supply Chain Engineering MN 799 168# Types of Modularity for Mass Customization

Component Sharing Modularity

Cut-to-Fit Modularity

Bus Modularity

Mix Modularity

Sectional Modularity

Supply Chain Engineering MN 799 169# Example of Point of Service Replenishment

• Safety Stock and Re-order point management in Toyota

Another advantage of Toyota‘s new system is that safety stock criteria can be adjusted according to seasonal requirements. Previously, the company had no ability to recognize the seasonality of items such as wiper blades. It worked from one forecast model — a simple moving average — that didn‘t allow for fine-tuning or sudden shifts in consumer taste. Reorder points were recalculated just once a month.

To support the new system, Toyota implemented Exam Inventory, a solution made by Entity Software in Epson, U.K. Exam is an inventory management program that runs on a PC and is fed raw data directly from a computer. As a result, Toyota (GB) was able to fully customize the package to its needs with minimal impact on the company‘s larger computers. The software allows for more sophisticated forecasting and more accurate calculation of reorder points (ROPs), while keeping safety stocks low.

Toyota now has moved to weekly ROP calculations and hopes eventually to carry out that function on a daily basis when the technology permits, Results of the program so far include an improvement in Toyota‘s service level from 94 percent to 96 percent, reduction in the number of manual order changes from 3,000 a day to 50, and reduction in run times from 12 to 3.5 hours.

Supply Chain Engineering MN 799 170# Cautions in Implementing Postponement and Modularity • End products must look suitably different to the consumer • Design and production costs can only be justified over a family of products • Performance and cost of a product can be optimized by eliminating modularity. Do a small set of products provide most of the sales?

Supply Chain Engineering MN 799 171# Summary of Learning Objectives Match Supply & Demand

Reduce Buffer Inventory

Supply / Demand Seasonal Economies of Scale Variability Variability

Cycle Inventory Safety Inventory Seasonal Inventory

•Reduce fixed cost •Quick Response measures •Aggregate across •Reduce Info Uncertainty products •Reduce lead time •Volume discounts •Reduce supply uncertaint •EDLP •Accurate Response measures •Promotion on Sell •Aggregation thru •Component commonalit and postponement Supply Chain Engineering MN 799 172# HOMEWORK

• Page 336 Q4 and Q5

• Provide actual examples of the five types of customization

Supply Chain Engineering MN 799 173# OPTIMUM LEVEL OF PRODUCT AVAILABILITY Exercise: Swimsuit Production Lesson 8 • Fashion items have short life cycles, high variety of competitors • SnowTime Sporting Goods – New designs are completed – One production opportunity – Based on past sales, knowledge of the industry, and economic conditions, the marketing department has a probabilistic forecast – The forecast averages about 13,000, but there is a chance that demand will be greater or less than this • Production cost per unit (C): $80 • Selling price per unit (S): $125 • Salvage value per unit (V): $20 • Fixed production cost (F): $100,000 • Q is production quantity, D demand • Profit = Revenue - Variable Cost - Fixed Cost + Salvage

Supply Chain Engineering MN 799 174# Demand Distribution

Demand Scenarios

28% 30% 22% 25% 18% 20% 11% 11% 15% 10%

Probability 10% 5% 0%

8000 10000 12000 14000 16000 18000 Sales

Supply Chain Engineering MN 799 175# Exercise

• Scenario One: – Suppose you make 12,000 jackets and demand ends up being 13,000 jackets. – Profit = 125(12,000) - 80(12,000) - 100,000 = $440,000 • Scenario Two: – Suppose you make 12,000 jackets and demand ends up being 11,000 jackets. – Profit = 125(11,000) - 80(12,000) - 100,000 + 20(1000) = $ 335,000 • Find order quantity that maximizes weighted average profit. • Average demand is 13,100 (work out – Σp.D) • Question: Will this quantity be less than, equal to, or greater than average demand? • Look at marginal cost Vs. marginal profit – if extra jacket sold, profit is 125-80 = 45 – if not sold, cost is 80-20 = 60 • So we will make less than average

Supply Chain Engineering MN 799 176# Profitability Calculations

Expected Profit

$400,000

$300,000

$200,000 Profit $100,000

$0 8000 12000 16000 20000 Order Quantity

Supply Chain Engineering MN 799 177# Profitability scenarios

100%

80%

60% Q=9000

40% Q=16000 Probability 20%

0%

-300000 -100000 100000 300000 500000 Cost

Supply Chain Engineering MN 799 178# OPTIMAL LEVEL OF PRODUCT AVAILABILITY

• FACTORS AFFECTING OPTIMAL PRODUCT AVAILABILITY – COST OF OVERSTOCKING Co • PROFIT FROM SALES • INVENTORY HOLDING COSTS • OBSELESCENCE – SALVAGE COSTS – COST OF UNDERSTOCKING Cu • LOST SALES • LOST CUSTOMERS • EXAMPLE OF L.L.BEAN (Table 12.1) – For all references New Book 12.xx

Supply Chain Engineering MN 799 179# Parkas at L.L. Bean

Cost per parka = $45 Sale price per parka = $100 Discount price per parka = $50 Holding and transportation cost = $10

• Profit from selling parka = $100-$45 = $55 • Cost of overstocking = $45+$10-$50 = $5 • Expected demand = =1026, ordered 1000 parkas CSL51% • Expected profit from ordering 1000 parkas = $49,900 Di pi • See formula on page 224 – Expected profit =

10 [Di( p  c)  (1000 Di)(c  s)]pi  (1 Pi)1000( p  c) i4

Supply Chain Engineering MN 799 180# Summary

• Tradeoff between ordering enough to meet demand and ordering too much • Several quantities have the same average profit • Average profit does not tell the whole story • Question: 9000 and 16000 units lead to about the same average profit, so which do we prefer? Work out probabilities of profit and loss • The optimal order quantity is not necessarily equal to average forecast demand (13,100) • The optimal quantity depends on the relationship between marginal profit and marginal cost • As order quantity increases, average profit first increases and then decreases • As production quantity increases, risk increases. In other words, the probability of large gains and of large losses increases

Supply Chain Engineering MN 799 181# How much to order? Parkas at L.L. Bean (Table 12.1)

Demand Probabability Cumulative Probability of Probability of demand (00’s) demand being this size or less greater than this size 4 .01 .01 .99 5 .02 .03 .97 6 .04 .07 .93 7 .08 .15 .85 8 .09 .24 .76 9 .11 .35 .65 10 .16 .51 .49 11 .20 .71 .29 12 .11 .82 .18 13 .10 .92 .08 14 .04 .96 .04 15 .02 .98 .02 16 .01 .99 .01 17 .01 1.00 .00

The probability that demand is greater than 1100 is 0.29 but the probability that demand is greater than or equal to 1100 is 0.49. O.51 is the probability that the demand is 1000 or less. Thus, 1-0.51 = 0.49 is the probability that the demand is greater than 1000 = probability that demand is greater than or equal to 1100

Supply Chain Engineering MN 799 182# Parkas at L.L. Bean (Table 12.2) Expected Marginal Contribution of each 100 parkas Fig 9.1

Additional Expected Expected Expected Marginal 100s Marginal Benefit Marginal Cost Contribution 11th 5500.49 = 2695 500.51 = 255 2695-255 = 2440 12th 5500.29 = 1595 500.71 = 355 1595-355 = 1240 13th 5500.18 = 990 500.82 = 410 990-410 = 580 14th 5500.08 = 440 500.92 = 460 440-460 = -20 15th 5500.04 = 220 500.96 = 480 220-480 = -260 16th 5500.02 = 110 500.98 = 490 110-490 = -380 17th 5500.01 = 55 500.99 = 495 55-495 = -440

Supply Chain Engineering MN 799 183# Optimal Order Quantity

1.2

1 0.917 0.8 Prob 0.6 Probability

0.4

0.2

0 4 5 6 7 8 9 10 11 12 13 14 15 16 87 Optimal Order Quantity = 13

Supply Chain Engineering MN 799 184# Optimal level of service (Eqn. 12.1) p = retail sale price; s = outlet or salvage price; c = purchase price;

Co = cost of overstocking by one unit, Co = c - s

Cu = cost of understocking by one unit, Cu = p - c CSL* = Optimal SL. Optimal order size O* If O* +1, expected marginal benefit from increasing order size by 1 = (1- CSL*)(p - c) (understocking cost x prob of understock) If O* -1, Expected Marginal Cost = CSL*(c - s). Thus expected marginal contribution of O* to O* +1 * * (1-CSL )Cu - CSL  Co (or optimally) = 0 * * ) CSL = prob. (dem. =< O = Cu / (Cu + Co) = (p-c) (p-s)

Supply Chain Engineering MN 799 185# Order Quantity for a Single Order (ex 12.1)

Salvage value = $80

Co = Cost of overstocking = c-s = $20

Cu = Cost of understocking CSL*  Prob(Demand  *)  = p – c = $150 R 150 O* = Optimal order size Cu   0.88  150 20 Cu Co O*    zs  3501.18x100  468

Supply Chain Engineering MN 799 186# MANAGERIAL LEVERS TO IMPROVE PROFITABILITY

• How to Estimate Demand Distribution? – Historical data: Time series forecasting – Dependent factors: Regression, causal forecasting – Expert opinion: Buying committee

Key: Forecast must include estimated demand and uncertainty (standard deviation) of demand

Supply Chain Engineering MN 799 187# Levers for Increasing Supply Chain Profitability • Increase salvage value (cost of overstock) or decrease margin lost from stockout – backup sourcing; rain checks.

• As Co/Cu gets smaller, optimal level of product availability (CSL) increases (see Fig 12.2). Companies with high margin have high cost of understocking and so provide high CSL • Improved forecasting to lower demand uncertainty (table 12.3) – CSL is constant. Optimum order size decreases and Expected profit increases • Quick response Reduce replenishment lead time so as to increase number of orders per season (table 12.4, 12.5). With two or more orders: – Possible to provide same CSL with less inventory – Average overstock at end of season is less – Profits higher with second order • If quick response allows multiple orders in the season, profits increase and overstock quantity reduces (Fig 12.4,12.5)

Supply Chain Engineering MN 799 188# Levers for Increasing Supply Chain Profitability

• Postponement of product differentiation – Better match of supply and demand for products not positively correlated and about the same size – Postponment may reduce overall profits, if one product contributes to majority of demand (extra cost of later manufacturing) – Tailored postponement only uncertain part of demand, producing predictable part at lower cost without postponement • Tailored supply sourcing – focus on two sources – One source focus on cost; unable to handle uncertainty – predictable portion – One source focus on flexibility; at a higher cost – unpredictable portion

Supply Chain Engineering MN 799 189# Tailored Sourcing: Multiple Sourcing Sites

Characteristic Primary Site Secondary Site Manufacturing High Low Cost Flexibility High Low (Volume/Mix) Responsiveness High Low Engineering High Low Support

Supply Chain Engineering MN 799 190# Dual Sourcing Strategies

Strategy Primary Site Secondary Site

Volume based Fluctuation Stable demand dual sourcing Product based Unpredictable Predictable, dual sourcing products, large batch Small batch products Model based Newer Older stable dual sourcing products products

Supply Chain Engineering MN 799 191# SUPPLY CHAIN CONTRACTS • DOUBLE MARGINALIZATION (SUBOPTIMIZATION) – BUY BACK (Ex. Mfg cost 10, retailer cost 100, selling 200 – SC profit 190, retailer profit – 100, manuf profit 90). EACH TRY TO MAXIMIZE OWN PROFIT, NOT THE SUPPLY CHAINS) – RETAILER ORDERS LESS AS THE LOSS FROM UNSOLD PRODUCT HIGH (100). Loss to Supply Chain is 10 only – MANUFACTURER IN BUYING BACK UNSOLD PRODUCT, INCREASES SALVAGE VALUE, AND INDUCES RETAILER TO ORDER MORE (table 9.70 – TOTAL SUPPLY CHAIN PROFITS INCREASE • QUANTITY FLEXIBILITY CONTRACTS – MANUFACTURER ALLOWS RETAILER TO CHANGE CONTRACTS AFTER CHANGING DEMAND – INCREASES PROFITABILITY OF ALL AND TOTAL SUPPLY CHAIN • VMI REPLENISHMENT BY MANUFACTURER (Ex. P&G/WALMART) • CONTROL OF REPLENISHMENT MOVES TO MANUFACTURER • CUSTOMER INFORMATION TO MANUFACTURER

Supply Chain Engineering MN 799 192# SETTING OPTIMAL LEVELS OF PRODUCT AVAILABILITY

• USE ANALYTICAL FRAMEWORK TO INCREASE PROFITS – COMPANIES SET TARGETS WITHOUT ANALYSIS • BEWARE OF PRESET LEVELS OF AVAILABILITY – OFTEN SET WITHOUT JUSTIFICATION – WORK ANALYSIS TO MAXIMIZE PROFITS • USE APPROXIMATE COSTS AS PROFIT MAXIMIZING SOLUTIONS ARE ROBUST • ESTIMATE A RANGE FOR STOCKING OUT • ENSURE THAT LEVELS OF PRODUCT AVAILABILITY FIT WITH STRATEGY

• HOME WORK Page 373 Ex. 1 and 3

Supply Chain Engineering MN 799 193# CASE STUDY – OPTIMIZED DEMAND PULL

• HIGHLY VARIABLE, HI TECH, HIGH COST – 12 MONTH ROLLING FORECAST WITH MANUFACTURING LEAD TIME COMMITTED – CHANGE OUTSIDE LEAD TIME LIMITED TO +/- 20% – TWO YEAR FORECAST ON YEAR FORECAST COMMITTED TO, NOT MONTHLY QUANTITIES – INCENTIVES FOR INCREASED FORECAST, DISCOUNTS FOR REDUCED FORECASTS – REPLENISHMENT RATE DRIVEN BY MAX/MIN ON HAND LEVELS – WEEKLY ON HAND – MONTHLY 12 MONTH ROLLING FORECAST

Supply Chain Engineering MN 799 194# SOURCING and PROCUREMENT (CH 14) Lesson 9

• SOURCING – Entire set of business processes to purchase goods and services – Includes: • Selection of supplies • Design of supplier contracts • Product design collaboration • Procurement of material • Evaluation of Supplier performance • PROCUREMENT – Process of purchasing materials, products and services – COGS 50% or more of product cost – Even higher % with outsourcing

Supply Chain Engineering MN 799 195# EFFECTIVE SOURCING • ECONOMIES OF SCALE – ORDERS AGGREGRATED • MORE EFFICIENT PROCUREMENT TRANSACTIONS (LESS) REDUCES OVERALL COST • DESIGN COLLABORATION • IMPROVE FORECASTING • CONTRACTS FOR SHARING RISK • LOWER PURCHASING PRICE

Supply Chain Engineering MN 799 196# IN HOUSE OR OUTSOURCE

• HOW DO THIRD PARTIES INCREASE SUPPLY CHAIN SURPLUS – CAPACITY AGGREGRATION – INVENTORY AGGREGRATION – TRANSPORTATION AGGREGRATION – WAREHOUSING AGGREGRATION – PROCUREMENT AGGREGRATION – INFORMATION AGGREGRATION – RECEIVABLE AGGREGRATION – RELATIONSHIP AGGREGRATION – LOWER COSTS AND HIGHER QUALITY (Table 14.1)

Supply Chain Engineering MN 799 197# RISKS OF USING A THIRD PARTY

• THE PROCESS IS BROKEN – lack control • UNDERESTIMATE COST OF COORDINATION • REDUCED SUPPLIER/CUSTOMER CONTACT • LOSS OF INTERNAL CAPABILITY AND GROWTH IN THIRD PARTY POWER • LEAKAGE OF SENSITIVE DATA AND INFORMATION • INEFFECTIVE CONTRACTS

• THIRD AND FOURTH PARTY PROVIDERS (Table 14-2) – Transportation – Warehousing – Information technology – Reverse Logistics – International – Special skills/handling

Supply Chain Engineering MN 799 198# SUPPLIER SCORING AND ASSESSMENT MUST BE BASED ON IMPACT ON TOTAL COST (Tab14-3) • IN ADDITION TO PRICE • REPLENISHMENT LEAD TIME; • ON TIME PERFORMANCE • SUPPLY FLEXIBILITY • DELIVERY FREQUENCY/ MINIMUM LOT SIZE • SUPPLY QUALITY • INBOUND TRANSPORTATION COSTS • INFORMATION COORDINATION CAPABILITY • DESIGN COST REDUCTION • EXCHANGE RATES, TAXES AND DUTIES • SUPPLIER VISIBILITY • RESPONSIVENESS

Supply Chain Engineering MN 799 199# SOURCING DECISIONS

• SUPPLIER PERFORMANCE BASED ON IMPACT ON TOTAL COST (see Table 14.1) – Ex. Green Thumb gets bearings at $1.00 in lots of 2,000 with a lead time of 2 weeks and a stnd devn of 1 week. New supplier offers $0.97 with lot size of 8000, a lead time of 6 weeks and stnd devn of 4 weeks. Given 1000 bearings needed per week with a stnd devn of 300 and that holding costs are 25% and CSL is 95% which supplier should be selected

Supply Chain Engineering MN 799 200# SOURCING DECISIONS • CONTRACTS – BUYBACK OR RETURN CONTRACTS • LOWERS COST OF OVERSTOCKING – REVENUE SHARING CONTRACTS • REDUCES COST PER UNIT TO RETAILER & COST OF OVERSTOCKING – QUANTITY FLEXIBILITY CONTRACTS – BEST • RETAILER CAN MODIFY ORDER CLOSER TO POINT OF SALE – CONTRACTS TO INDUCE PERFORMANCE IMPROVEMENT • SHARED SAVINGS CONTRACT • DESIGN COLLABORATION – HELPS REDUCE COST, IMPROVE QUALITY AND TIME TO MARKET • PROCUREMENT PROCESS – FOCUS ON IMPROVING DIRECT MATERIALS COORDINATION AND VISIBILITY WITH SUPPLIER – LOOKING SEPARATELY AT DIRECT AND INDIRECT MATERIAL COSTS (14-7) – CLASSIFYING ITEMS PER COST AND CRITICALITY (FIG 14.2) – FOCUS ON IMPROVING INDIRECT MATERIALS BY DECREASING TRANSACTION COST OF ORDER – BOTH SHOULD CONSOLIDATE ORDERS FOR ECONOMIES OF SCALE

Supply Chain Engineering MN 799 201# SOURCING DECISIONS

• SOURCING DECISIONS IN PRACTICE – USE MULTIFUNCTIONAL TEAMS – ENSURE APPROPRIATE COORDINATION ACROSS REGIONS AND BUSINESS UNITS – ALWAYS EVALUATE TOTAL COST OF OWNERSHIP – BUILD LONG TERM RELATIONSHIP WITH KEY SUPPLIERS

Supply Chain Engineering MN 799 202# Make or Buy Decision

– Cost – Time – Capacity Utilization – Control of Production/Quality – Design Secrecy – Supplier Reliability and Technical Expertise – Volume – Workforce Stability

Supply Chain Engineering MN 799 203# Make-or-Buy Decision •Original Data: •Produce 10,000 units Cost Factors Raw material $9,000 Direct labor $12,000 Variable factory overhead $5,000 Fixed factory overhead $24,000 Total Cost to Make $50,000 Make cost per unit = $50,000/10,000 = $5.00/unit Purchase proposal = $4.50/unit Should the product be bought? •Factors to Consider: 1. You only avoid 80% of the variable factory overhead cost 2. And only avoid 10% of the fixed factory overhead cost

Supply Chain Engineering MN 799 204# Cost Avoidance Analysis (Solution)

Solution Cost avoided by purchasing Total cost to make $50,000 Less cost avoided: Raw material $9,000 Direct labor $12,000 Variable factory overhead ($5,[email protected]) $4,000 Fixed factory overhead ($24,[email protected]) $2,400 Total Avoided Cost $27,400 Analysis Cost not avoided $22,600 Plus cost to purchase $45,000 Total cost to purchase $67,600 Compare to cost to make $50,000 Increase in cost to purchase $17,600 Actual cost per purchased item 67500/1000 = $6.75/unit !

Supply Chain Engineering MN 799 205# SUPPLIER PARTNERSHIPS

• QUALIFICATION AND SELECTION – RATIONALIZATION OF SUPPLIER BASE • PARTNERSHIP – WIN-WIN AND TRUST – SHARING OF RISK AND COMMITMENT – PRICE REDUCTIONS AND INCREASES BASED ON FORECAST – RATE REPLENISHMENT • MEAUREMENT AND FEEDBACK – QUALITY, DELIVERY, RESPONSIVENESS – QUARTERLY FEEDBACK – IMPLICATIONS

Supply Chain Engineering MN 799 206# HOMEWORK

• Exercises 1 & 2

Supply Chain Engineering MN 799 207# MANAGING TRANSPORTATION IN A SUPPLY CHAIN (Chap 13) – Lesson 10

• Key modes of transport and major issues • Transportation System Design • Tradeoffs in transportation design – costs vs. responsiveness – Transportation and inventory: Choice of mode – Transportation and inventory: Consolidation

Supply Chain Engineering MN 799 208# LOGISTICAL PROCESSES • TRANSPORTATION – PALLETIZATION AND CONTAINERIZATION – FREIGHT FORWARDERS AND CUSTOMS – TRADE-OFF IN TRANSPORTATION TYPES & TRANSITONS • WAREHOUSING AND DISTRIBUTION – CENTRALIZED OR REGIONAL – REPLENISHMENT STRATEGIES • DRP • POINT OF USE – CROSS DOCKING • DELIVERY • GLOBAL SUPPLY CHAINS

Supply Chain Engineering MN 799 209#

Principle: Leverage World-Wide Logistics

This principle is about Variability.

Supply Chain Engineering MN 799 210# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. Fundamental Logistics Tradeoffs

Supply Chain Inventory Units

Landed Cost

Transit Time Variability

Supply Chain Engineering MN 799 211# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. Tailored Logistics • Transportation costs in 1996 - $455 billion (6% GNP). In 2005 744b 10% GDP • E-com and home delivery of small loads makes transport more significant – Wal-Mart – low inventory, frequent replenish, cross dock – Amazon – centralized , package carriers and postal system – Dell – centralized assembly, package carriers (Airborne) • Each Logistically Distinct Business (LDB) will have distinct requirements in terms of – Inventory – Transportation – Facility – Information Key: How to gain efficiencies while tailoring logistics?

Supply Chain Engineering MN 799 212# FACTORS AFFECTING TRANSPORTATION DECISIONS • CARRIER – VEHICLE RELATED COST – cost of vehicle – FIXED OPERATING COST – terminals, labor – TRIP RELATED COST – fuel, labor – QUANTITY RELATED COST - weight – OVERHEAD COST – planning, dispatching • SHIPPER – TRANSPORTATION COST – cost per Ton mile – INVENTORY COST – holding – FACILITY COST - storage – PROCESSING COST – loading unloading – SERVICE LEVEL COST – not making delivery

Supply Chain Engineering MN 799 213# Transportation Modes (See Table 13.1 )

• Trucks – TL – LTL – Carload – Intermodal • Rail • Air • Package Carriers • Water • Pipeline DISCUSS USES AND ISSUES

Supply Chain Engineering MN 799 214# AIR

• Freight Revenue 777b 2002 (96.7% change from 1993) • Average revenue / ton-mile (1996) = 58.75 cents • Average haul = 1,260 miles • Average load = 10.5 tons • 1998 Freight expense $22.678b • Key Issues – Location/Number of hubs – Location of fleet bases / crew bases – Schedule optimization – Fleet assignment – Crew scheduling – Yield management • Best Use

Supply Chain Engineering MN 799 215# Truckload (TL)

• Freight Revenue 6,660b (42.2% change from 1993) • Average revenue per ton mile (1996) = 9.13 cents • Average haul = 274 miles • Average Capacity = 42,000 - 50,000 lb. • 1998 Freight expense $ 401.68billion • Low fixed and variable costs • Major Issues – Utilization (Idle and empty travel) – Consistent service – Backhauls • Best Use?

Supply Chain Engineering MN 799 216# Less Than Truckload (LTL)

• Average revenue per ton-mile (1996) = 25.08 cents • Average haul = 646 miles • 1998 Freight expense with TL • Higher fixed costs (terminals) and low variable costs • Major Issues – Location of consolidation facilities – Utilization – Vehicle routing – Customer service (delivery time and reliability) • Best Use?

Supply Chain Engineering MN 799 217# Rail

• Freight Revenue 388b (39.2% change from 1993) • Average revenue / ton-mile (1996) = 2.5 cents • Average haul = 720 miles • Average load = 80 tons • 1998 Freight expense $35.35billion • Key Issues – Scheduling to minimize delays / improve service – Off track delays (at pick up and delivery end) – Yard operations, transitions – Variability of delivery times • Best Use?

Supply Chain Engineering MN 799 218# Other Modes

• Water – 0.73c per ton mil – Freight Revenue 867b (39.9% change from 1993) – average haul miles 500 internal to 1500 coast – 1998 Freight expense $ 25.35b – Cheapest mode for global shipping – Issues: delays at ports, customs, management of containers • Pipe – 1.40c per ton mile – Freight Revenue 285b (-8.7% change from 1993) – Average haul 400 products to 760 crude – 1998 Freight expense $ 8.74b – Issues: Infrastructure • Intermodal – Freight Revenue 1,111b (67% change from 1993) – Combination – most common truck/rail – Very useful in global trade – Issues: exchange of information to facilitate transfer

Supply Chain Engineering MN 799 219# Tradeoffs in Transportation Design

• Transportation, facility, and inventory cost tradeoff – Choice of transportation mode – Inventory aggregation • Transportation cost and responsiveness tradeoff • Ranking of Transportation Modes in terms of Supply Chain performance – Table 13-3

Supply Chain Engineering MN 799 220# DESIGN OPTIONS FOR TRANSP NETWORK • DIRECT SHIP NETWORK (fig 13.2) – IF REPLENISHMENT LARGE ENOUGH FOR TL • DIRECT SHIP WITH MILKRUNS (fig 13.3) – SINGLE SUPPLIER TO MULTIPLE RETAILER OR VICE VERSA – ELIMINATE INTERMEDIATE WAREHOUSES – LOWER TRANSPORTATION COSTS • ALL SHIPMENTS VIA CDC (FIG 13.4, 13.5) – DC STORE INVENTORY OR TRANFER LOCATION – CROSS DOCKING – SHIP VIA DC WITH MILK RUN • TAILORED NETWORK (FIG 13.5)

EXERCISE: ADVANTAGES AND DISADVANTAGES OF EACH – next slide

Supply Chain Engineering MN 799 221# PROS AND CONS OF TRANP. NETWORKS (Tab 13.2)

Network Structure Pros Cons

Direct Shipping *No intermediate Whse *High inventories * Simple to coordinate *Significant Receiving expense

Direct Shipping with milk runs *Lower transp costs small lots * More coordination *Lower inventories complexity

All shipments via CDC with *Consolidation less inbound *Increased Inventory inventory storage transp cost *Increased handling

Ship via CDC with cross *Very low inventory * More coordination docking *Consolidation-less trans Cost complexity

Shipping via DC using milk * Lower outbound trans cost for *Further increase in runs small lots coordin complexity Tailored network *Match trans choice with needs *Highest coordin complexity

Supply Chain Engineering MN 799 222# TRADE OFFS IN TRANSPORTATION DESIGN TRANSPORTATION AND INVENTORY COST TRADE-OFF

• Choice of Transport Mode: Eastern Electric Corp (Ex 13.1)

• Annual demand = 120,000 motors Traditional lot size 3000

• Cost per motor = $120 Weight 10lbs

• Current order size = See Table 13.4

• Safety stock carried = 50% of demand during delivery lead time

• Holding cost =25%. Annual holding cost =120 x 0.25 =$30/motor

• Lead times – 1 day to process, transit time days - rail 5, road 3

• Work out the total cost for each transport proposal See Table 13.5

• Proposal Quantity over 250cwt $4/cwt to $3/cwt and shipment batch size 4000. What should plant do

Total Costs = Inventory costs (include Cycle, Safety) + Transportation costs (depend on weight and form of transport)

Supply Chain Engineering MN 799 223# Eastern Electric Corporation (Table 13.5)

Alternative Transport Cycle Safety Transit Inventory Total (Lot size) Cost Inventory Inventory Inventory Cost Cost AM Rail $78,000 1,000 986 1,644 $108,900 $186,900 (2,000) Northeast $90,000 500 658 986 $64,320 $154,320 Trucking (1,000) Golden $96,000 250 658 986 $56,820 $152,820 (500) Golden $86,400 1,250 658 986 $86,820 $173,220 (2,500) Golden $78,000 1,500 658 986 $94,320 $172,320 (3,000) Golden $67,500 2,000 658 986 $109,320 $176,820 (4,000)

Supply Chain Engineering MN 799 224# Inventory Aggregation at HighMed Ex 13.2 (Table 13.6) Highval (cost $200/unit, 0.1 lbs/unit) demand in each territory

H = 2, sH = 5, CSL= 0.997, Holding cost = 25% Lowval (cost $30/unit, 0.04 lbs/unit) demand in each territory

L = 20, sL = 5 UPS rate: $0.66 + 0.26x {for replenishments} FedEx rate: $5.53 + 0.53x {for customer shipping} where x is quantity shipped in lbs Factory 1 week replenish, local inventory 4 wks replenish Average customer order – 1 Highval & 10 Lowval Option A – Replenish weekly instead of every 4 weeks Option B – Elimin inventory in territories, aggregate all inven in one warehouse, replenish warehouse once a week

Supply Chain Engineering MN 799 225# Inventory Aggregation at HighMed (13.6)

Current Option 1 Option 2 Scenario # Locations 24 24 1 Reorder Interval 4 weeks 1 week 1 week Inventory Cost $54,366 $29,795 $8,474

Shipment Size(dltxlt) 8 H + 80 L 2 H + 20 L 1 H + 10 L Transport Cost $530 $1,148 $14,464 Total Cost $54,896 $30,943 $22,938

If shipment size to customer is 0.5H + 5L, total cost of option 2 increases to $36,729.

Supply Chain Engineering MN 799 226# Physical Inventory Aggregation: Inventory vs. Transportation cost • Firms can significantly reduce SS by physically aggregating inventory in one location • As a result of physical aggregation – Inventory costs decrease – Inbound transportation cost decreases – one destination DC – Outbound transportation cost increases – several deliveries • Advantageous when inventory and facility costs form a large fraction of supply chain costs – Large value to weight ratio (ex PC‘s) – High demand uncertainty and large value (ex designer dresses) – Large customer orders to cover economies of scale on outbound transportation

Supply Chain Engineering MN 799 227# Tailored Transportation (Table 13.9)

• Factors affecting tailoring – Optimizing response vs cost – Customer distance and density » Short distance Med distance Long distance Hi Density Private fleet milk runs Crossdock, milk runs Crossdock, milk runs Med Dens Third party milk runs LTL carrier LTL or package carrier Low Dens Third party milk runs or LTL LTL or package carr Package carrier – Customer size • Large can use a TL; medium and small LTL use LTL or milk runs – Product demand and value (Table 13.10) • Product Hi value Lo value • High demand Disaggreg cycle inven Disaggreg all inven, use inexpen trans » Aggregate safety stock, for replen inven » inexpen transp for replen, cycle & » fast mode for safety inventory • Low demand Aggregate all inven. Use fast Aggregate Safety inven only. Use inexpen » trans for filling cust orders trans for replen cycle inven

Supply Chain Engineering MN 799 228# ROUTING AND SCHEDULING IN TRANSPORTATION Chapter 5) • Framework for Network Design Decisions (Table 5.2) – Phase I : Define a supply chain strategy – Phase II: Define regional facility configuration – Phase III: Select a set of desirable potential sites – Phase IV: Location Choices – Exercise Sun Oil Fig 5-3 • Phase II Network Optimization Models: Capacitated Plant Location Model – Decide on Network design that maximizes profits • Phase III: Gravity Location Models (Table 5-1) – Work out manually – Identify the distance matrix – Identify the savings matrix – Assign customers to vehicles or routes – Sequence customers within routes

Supply Chain Engineering MN 799 229# RISK MANAGEMENT IN TRANSPORTATION

• RISK THAT SHIPMENT IS DELAYED • RISK THAT SHIPMENT DOES NOT REACH ITS FINAL DESTINATION, BECAUSE INTERMEDIATE NODES DISRUPTED • RISK OF HAZARDOUS MATERIAL

Supply Chain Engineering MN 799 230# MAKING TRANSPORTATION DECISIONS IN PRACTICE

• ALIGN TRANSPORTATION STRATEGY WITH COMPETITIVE STRATEGY • CONSIDER BOTH IN HOUSE AND OUTSOURCED TRANSPORTATION – STRATEGIC IMPORTANCE AND PROFITABILITY • DESIGN A TRANSPORTATION NETWORK THAT CAN HANDLE E- COMMERCE – DECREASE IN SHIPMENT SIZE & INCREASE IN HOME DELIVERY • USE TECHNOLOGY TO IMPROVE TRANSPORTATION PERFORMANCE – IDENTIFY LOCATION AND SHIPMENT IN VEHICLE • DESIGN FLEXIBILITY INTO THE TRANSPORTATION NETWORK – TAKE INTO ACCOUNT UNCERTAINTYIN DEMAND AND IN AVAILABILITY OF TRANSPORTATION

Supply Chain Engineering MN 799 231# HOMEWORK

• EXERCISE 13.1 Coal and MRO • Ex 13.2 Work out single location and 1 week replenishment • EXAMPLE HIGHMED (Ex 13.2) – WORK OUT OPTION A & IF SHIPMENT SIZE IS 0.5H + 5.0L – WHAT ARE YOUR CONCLUSIONS?

Supply Chain Engineering MN 799 232# FACILITY DECISIONS: Network Design Decisions Lesson 11 (Chap 4) • FACILITY ROLE – What processes are performed • FACILITY LOCATION – Where should facilities be located • CAPACITY ALLOCATION – How much capacity should be allocated to each facility • MARKET & SUPPLY ALLOCATION – What markets should each facility serve – What supply sources should feed each facility

Supply Chain Engineering MN 799 233# Factors Influencing Network Design Decisions

• Strategic – Cost or Responsiveness focus • Technological – Fixed costs and flexibility determine consolidation • Macroeconomic – Tariffs and Tax incentives. Stability of currency • Political stability - clear commerce & legal rules • Infrastructure – sites, labor, transportation, highways, congestion, utilities • Competition • Logistics and facility costs

Supply Chain Engineering MN 799 234# The Cost-Response Time Frontier

Low Local FG Mix Regional FG

Local WIP Cost Central FG

Central WIP

Central Raw Material and Custom production

Custom production with raw material at suppliers Hi

Low (QUICK) Response Time Hi (LONG)

Supply Chain Engineering MN 799 235# LOGISTICS AND FACILITIES COSTS

• INVENTORY COSTS • TRANSPORTATION COSTS – INBOUND AND OUTBOUND • FACILITY (SETUP AND OPERATING) COSTS • TOTAL LOGISTICS COSTS

SEE SUCCEEDING CHARTS

Supply Chain Engineering MN 799 236# Service and Number of Facilities

AS THE NUMBER OF FACILITIES INCREASE, RESPONSE TIME REDUCES, AND COST INCREASES

Response Costs Time Response Time Costs

Number of Facilities

Supply Chain Engineering MN 799 237# Costs and Number of Facilities

Inventory

Costs Facility costs

Transportation Frequent inbound trans

Number of facilities

Supply Chain Engineering MN 799 238# Cost Build-up as a function of facilities

Total Costs

Percent Service Level Within Promised Time

Facilities Inventory

Transportation Cost of Operations Cost of Labor

Number of Facilities

Supply Chain Engineering MN 799 239# FRAMEWORK FOR NETWORK DESIGN DECISIONS • DEFINE A SUPPLY CHAIN STRATEGY – COMPETITIVE STATEGY, COMPETITION, SWOT • DEFINE A REGIONAL FACILITY STRATEGY – LOCATION, ROLES AND CAPACITY • SELECT DESIRABLE SITES – HARD INFRASTURCTURE – TRANSPORT, UTILITIES, SUPPLIERS, WAREHOUSES – SOFT INFRASTRUCTURE – SKILLED WORKFORCE, COMMUNITY • CHOOSE LOCATION – PRICE LOCATION AND CAPACITY ALLOCATION SEE FRAMEWORK NEXT

Supply Chain Engineering MN 799 240# A Framework for Global Site Location (107)

Competitive STRATEGY GLOBAL COMPETITION PHASE I Supply Chain INTERNAL CONSTRAINTS Strategy TARIFFS AND TAX Capital, growth strategy, INCENTIVES existing network

PRODUCTION TECHNOLOGIES REGIONAL DEMAND Cost, Scale/Scope impact, support PHASE II Size, growth, homogeneity, required, flexibility Regional Facility local specifications Configuration COMPETITIVE ENVIRONMENT POLITICAL, EXCHANGE RATE AND DEMAND RISK

PHASE III Desirable Sites AVAILABLE INFRASTRUCTURE PRODUCTION METHODS Skill needs, response time

FACTOR COSTS PHASE IV LOGISTICS COSTS Labor, materials, site specific Location Choices Transport, inventory, coordination

Supply Chain Engineering MN 799 241# Tailored Network: Multi - Echelon Finished Goods Network

Local DC Cross-Dock Store 1 Regional Customer 1 Finished DC Goods DC Store 1 Local DC Cross-Dock National Store 2 Customer 2 Finished DC Goods DC Local DC Store 2 Cross-Dock Regional Finished Store 3 Goods DC

Store 3

Supply Chain Engineering MN 799 242# Network Optimization Models • Allocating demand to production facilities • Locating facilities and allocating capacity – Speculative Strategy • Single sourcing – Hedging Strategy • Match revenue and cost exposure – Flexible Strategy Key Costs: • Excess total capacity in multiple plants • Flexible technologies •Fixed facility cost •Transportation cost •Production cost •Inventory cost •Coordination cost

Which plants to establish? How to configure the network?

Supply Chain Engineering MN 799 243# Gravity Methods for Location – Min. cost of transportn 316,116) ASSUMPTION: TRANSPORT COSTS GROW LINEARLY WITH SHIPMENTS • Ton Mile-Center Solution • (Table 11.29, 5.1) – x,y: Warehouse Coordinates 2 2 Coordinates of delivery location n   – xn, yn : d n (xxn) (yyn) – dn : Distance to delivery location n n xi F i – Fn : Cost per ton mile to delivery location n  i1 – Dn Quantity to be shipped x  d i – Fi = Dn Fn n F i i1 d i 2 n y Min 2 i F i  Fi (x x) (y  y)  i i i1 Reiterate x,y calculation till x,y values close y  d i k n F i Total Cost TC= Dnd nFn i1 d i n1 Supply Chain Engineering MN 799 244# Demand Allocation Model (pp319) (Table 5.2) n m • Which market is served by which plant? Min • Which supply sources are used by a plant? cij xij i1 j1 xij = Quantity shipped from plant site i to customer j st. Cij = cost to produce & ship one unit from factory i to market j n n = no. of factory locations  m = no. of markets  xij D j i1 Dj = Annual demand from market j Allm mkt demand satisfied K = Annual capacity of factory i i   xij K i j1 No factory capacity exceed  0 xij

Supply Chain Engineering MN 799 245# NETWORK DESIGN DECISIONS IN PRACTICE

• DO NOT UNDERESTIMATE THE LIFE SPAN – LONG LIFE HENCE LONG TERM CONSEQUENCES – ANTICIPATE EFFECT FUTURE DEMANDS, COSTS AND TECHNOLOGY CHANGE – STORAGE FACILITIES EASIER TO CHANCE THAN PRODUCTION FACILITIES • DO NOT GLOSS OVER CULTURAL IMPLICATIONS – LOCATION – URBAN, RURAL, PROXIMITY TO OTHERS • DO NOT IGNORE QUALITY OF LIFE ISSUES – WORKFORCE AVAILABILITY AND MORALE • FOCUS ON TARIFFS& TAX INCENTIVES WHEN LOCATING FACILITIES – PARTICULARLY IN INTERNATIONAL LOCATIONS

Supply Chain Engineering MN 799 246# HOMEWORK

• Page 330– Exercise 2

Supply Chain Engineering MN 799 247# BEER GAME Lesson 12

• Beer Game • HOMEWORK – • WRITE UP A SUMMARY OF THE LESSONS FROM THE BEER GAME • GIVE AN EXAMPLE OF THIS PHENOMENA IN REAL LIFE • WHAT WOULD YOU DO TO CORRECT IT

Supply Chain Engineering MN 799 248# DISCUSSION OF BEER GAME

• GET INTO SAME TEAMS • FORMULATE TWO OR LEARNINGS – WHAT IS THE EFFECT; WHY IS IT CAUSED; HOW CAN IT BE REDUCED? – FROM THE GAME – FROM YOUR INTUITION – FROM YOUR KNOWLEDGE OR INDUSTRY • PRESENT THEM TO CLASS FOR DISCUSSION

Supply Chain Engineering MN 799 249# SUPPLY CHAIN COORDINATION (Chap 16) Lesson 13

• The role of Information Technology – What is coordination? Take action to increase total SC profits – Obstacles to coordination: • The Bull-Whip Effect –every trading partner must understand effect of its actions on other trading partners – Effect of lack of coordination • Increased costs – Manufacturing, Inventory, Transportation, labor • Increased Replenishment lead time • Lower level of Product availability – Countermeasures to achieve coordination – The role of information technology in a supply chain

Supply Chain Engineering MN 799 250# As Information Moves Thru A Supply Chain

Demand uncertainty

Customer Retailer becomes more

Distributor AND MORE distorted Manufacturer

Supplier Supply Chain Engineering MN 799 251# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. Bullwhip Effect

The magnification of variability in orders in the supply-chain.

Retailer‘s Orders Wholesaler‘s Orders Manufacturer‘s Orders

Time Time Time

A lot of retailers …can lead to …can lead to even each with little greater variability for greater variability variability in their a fewer number of for a single orders…. wholesalers, and… manufacturer. Supply Chain Engineering MN 799 252# Information Coordination: The Bullwhip Effect

Consumer Sales at Retailer Retailer's Orders to Wholesaler 1000 1000

900 900

800 800 700 700 600 600 500 500 400 400 300 300

200 Order Retailer 200 Consumer demand Consumer 100 100

0

0

1 3 5 7 9

1 3 5 7 9

11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41

11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41

Wholesaler's Orders to Manufacturer Manufacturer's Orders with Supplier

1000 1000

900 900

800 800 700 700 600 600 500 500 400 400 300

300 Wholesaler Order Wholesaler

200 Order Manufacturer 200 100 100

0

3 5 7 9

1 0

11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41

1 4 7

10 13 16 19 22 25 28 31 34 37 40 Supply Chain Engineering MN 799 253# Impact of the Bullwhip Effect Performance Measure Impact on Performance Manufacturing Cost Inventories Lead Time Transport Cost Shipping & Receiving Cost Customer Service Level Profitability

Supply Chain Engineering MN 799 254# Bull Whip Effect - Incentive Obstacles

• Contributing factors – Incentives based on sell-in leading to forward buy – Localized optimization Ex Transportation Mgr linked to lowest transport cost – even if inventory cost increased – Sales Force incentives – quantity sold to next stage, not final customer – Buying policies based on max profits at one stage of supply chain

• Counter Measures – Align goals and incentives across functions – Price for coordination - – Focus sales force on increasing sell-thru to customer – Incentives based on rolling horizon – Sales force do not compete with each other but with the competition

Supply Chain Engineering MN 799 255# The Bullwhip Effect: Information Processing Obstacles

• Contributing factors – No visibility of end demand – Multiple forecasts, based on orders received not customer demand (magnifies incr/decr) – Long lead-time – Lack of information sharing • Counter Measures – Collaborative forecasting and planning (CFAR, CPFR) – Access sell-thru or POS data. Sharing POS data – Direct sales (natural on web) – Single control of replenishment – continuous replenishment and VMI – Leadtime reduction • State of Practice – Sell-thru data in contracts (e.g., HP, Apple, IBM) – CFAR, CPFR, CRP, VMI (P&G and Walmart) – Quick Response Mfg. Strategy – Dell direct supply to customer

Supply Chain Engineering MN 799 256# Bull Whip Effect - Operational Obstacles (Batching)

• Contributing factors – High Order Cost – Ordering large lots – Large replenishment times – Full TL economies – Random or correlated ordering • Counter Measures – Reduce replenishment lead time – EDI, manuf techniques, Advanced Shipping notices (ASN), & Computer Assisted Ordering (CAO) – Reduce Lot sizes – reduce fixed costs to (order, manuf, transport, receive) – Discounted on Assorted Truckload, consolidated by 3rd party logistics – Regular delivery appointment, milk runs, mixing deliveries – Volume and not lot size discounts • State of Practice – McKesson, Nabisco, ... – 3rd party logistics in Europe, emerging in the U.S. – P & G

Supply Chain Engineering MN 799 257# Bull Whip Effect - Operational Obstacles (Rationing Game)

• Contributing factors – Rationing and Shortage gaming (inflating order rewarded) – Proportional rationing scheme – Ignorance of supply conditions – Unrestricted orders & free return policy • Counter Measures – Allocation based on past sales. – Shared Capacity and Supply Information – Flexibility Limited over time, capacity reservation • State of Practice – Saturn, HP – Schedule Sharing (HP with TI and Motorola) – HP, Sun, Seagate

Supply Chain Engineering MN 799 258# Bull Whip Effect - Pricing Obstacles

• Contributing factors – Lot size based quantity discounts – High-Low Pricing leading to forward buy – Delivery and Purchase not synchronized • Counter Measures – Lot size based to Volume based quantity discounts – EDLP (Every day low pricing) – Limited purchase quantities – Scan based promotions • State of Practice – P&G (resisted by some retailers) – Scan based promotion

Supply Chain Engineering MN 799 259# Managerial Implications of the Bull Whip Effect - Behavioral Factors

• Contributing factors – Lack of trust – Local reaction – to current local condition – Each stage sub –optimizes – Each stage blames each other for fluctuations • Counter Measures – Building trust and partnership – Aligning incentives and objectives – co-identification – Sharing information – sales and production – Eliminating duplication (Inspection) • State of Practice – Wal-Mart and P&G with CFAR

Supply Chain Engineering MN 799 260# How Should A Middle Link Behave?

IF: The Middle Link makes an independent decision to increase production

THEN: Finished goods inventory increases for the Middle Link

THEN: Return On Assets are reduced for the Enterprise, and there is no improvement in end-to-end throughput!

IF: The Middle Link makes an independent decision to decrease production

THEN: The system constraint moves to the Middle Link

THEN: There is no reduction in operational costs for the Enterprise, and profit margins are lowered for every trading partner!

THEREFORE: The Middle Link should stay synchronized to the demand signal from the system constraint

Supply Chain Engineering MN 799 261# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. ACHIEVING COORDINATION IN PRACTICE

• QUANTIFY THE BULLWHIP EFFECT • GET TOP MANAGEMENT COMMITMENT • DEVOTE RESOURCES FOR COORDINATION - DEDICATED • FOCUS ON COMMUNICATION WITH OTHER STAGES • TRY TO ACHIEVE COORDINATION IN THE ENTIRE SUPPLY CHAIN NETWORK • USE TECHNOLOGY TO IMPROVE CONNECTIVITY IN THE SUPPLY SIDE - INCREASING VISIBILITY&COMMUNICATION • REDUCE TIME TO – ORDER, MAKE, TRANSPORT, REPLENISH • SHARE BENEFITS OF COORDINATION EQUITABLY

Supply Chain Engineering MN 799 262# Principle: Synchronize Supply With Demand

This principle is about Vocalization.

Supply Chain Engineering MN 799 263# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. ROLE OF INFORMATION IN SUPPLY CHAIN SUCCESS Information is the glue that binds the other three drivers, to create an integrated, coordinated supply chain. Provides facts to give visibility of whole supply chain and make sound decisions to improve performance * TYPES – Supplier, Manufacturing, Distribution & Retailing, and Demand * CHARACTERISTICS –Accurate, Timely, Accessible, Appropriate * OPTIMIZING – Inventory, Transportation, Facilities

Information Global Coordinated Supply Chain Scope Decisions Success

Global scope enables decisions to maximize the total supply chain profit

Supply Chain Engineering MN 799 264# USE OF INFORMATION

• INVENTORY – SETTING OPTIMUM INVENTORY POLICIES • DEMAND PATTERNS, CARRYING COSTS, STOCK OUT COSTS, ORDERING COSTS, SERVICE LEVEL, LEAD TIMES ETC • TRANSPORTATION – DECIDING NETWORKS, ROUTINGS, MODES, SHIPMENTS AND VENDORS • COSTS, CUSTOMER LOCATIONS, SHIP COSTS & LOCATIONS • FACILITY – DETERMINING LOCATION, CAPACITY AND SCHEDULE • TRADE OFFS EFFICIENCY VS FLEXIBILITY; DEMAND, EXCHANGE RATES, TAXES ETC

Supply Chain Engineering MN 799 265# Information Technology in a Supply Chain: Legacy Systems THERE ARE IT SYSTEMS ACROSS ENTIRE SUPPLY CHAIN Strategic

Planning

Operational

Supplier Manufacturer Distributor Retailer Customer

STRATEGIC – HIGH ORGANIZATIONAL LEVEL, LONG TIME FRAME, LITTLE LOW LEVEL DETAIL, HIGHLY ANALYTICAL, TOP MANAGERS LEGACY – ONE FUNCTION OR ONE STAGE OF SUPPLY CHAIN, TRANSACTIONAL ABILITY, DIFFICULT TO MODIFY, NO ANALYTICAL Supply Chain Engineering MN 799 266# Information Technology in a Supply Chain: ERP Systems ERP SYSTEMS – BROAD INFORMATION AVAILABILITY, REAL TIME, CAN USE ENABLING TECHNOLOGY LIKE INTERNET – WEAK ANALYTICAL Strategic

Planning

Potential ERP ERP Potential ERP Operational

Supplier Manufacturer Distributor Retailer Customer

Supply Chain Engineering MN 799 267# Information Technology in a Supply Chain: Analytical Applications

Strategic

SCM Planning APS Transport & Inventory Dem Plan Planning Supplier Apps CRM/SFA MES Transport execution & Operational WMS

Supplier Manufacturer Distributor Retailer Customer

Supply Chain Engineering MN 799 268# The Least Common Denominator Of Information Technology For orders, replenishment, payment, returns loops... Advanced Planning & Scheduling Enterprise Resource Planning Data Warehousing

DRP Legacy System MRP II Legacy System Electronic Data Interchange

LCD Internet Browser Electronic Mail Voicemail

Supply Chain Trading Partners

Retail

Factory Supplier

Supply Chain EngineeringCustomer MN 799 269# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation.Wholesale All Rights Reserved. Information Technology in a Supply Chain: Future Trends and Issues

• Best of breed versus single integrator • Shifts in Platform Technology – Client server – Browser based internet – Application service providers (ASP) – owns and hosts software and charges for third party use of software • The role of the Internet and B2B exchanges – Exchanges create efficient market • AUCTIONS, REVERSE AUCTIONS, FIXED PRICE, BID/ASK – Collaboration between buyer and seller essential – Convergence between B2B and Supply Chain

What do you see? Teams – come up with three major trends - present Supply Chain Engineering MN 799 270# SUPPLY CHAIN INFORMATION TECHNOLOGY IN PRACTICE • SELECT AN IT SYSTEM THAT ADDRESSES THE COMPANY‘S KEY SUCCESS FACTORS – COMPUTERS – INVENTORY LEVEL, – OIL REFINERY - UTILIZATION • ALIGN LEVEL OF SOPHISTICATION WITH NEED FOR SOPHISTICATION - KISS • USE IT SYSTEMS TO SUPPORT DECISION MAKING, NOT TO MAKE DECISIONS • THINK ABOUT THE FUTURE – WEB-BASED APPLICATIONS – FLEXIBILITY OF SYSTEMS TO ACCOMMODATE CHANGE

Supply Chain Engineering MN 799 271# Which E-Business is Right for Your Supply Chain?

What is different about e-commerce?

What are some potential opportunities in a supply chain?

Implications of e-business in different industries

Supply Chain Engineering MN 799 272# Applying the Framework to e-commerce:What is e-commerce?

• Commerce transacted over the Internet – Is product information displayed on the Internet? – Is negotiation over the Internet? EBay – Is the order placed over the Internet? Amazon – Is the order tracked over the Internet? – Is the order fulfilled over the Internet? – Is payment transacted over the Internet? • Information publicly available, no dedicated connection required • B to C and B to B • Expected to reduce prices, increase productivity, lower labor costs

Supply Chain Engineering MN 799 273# Existing Channels for Business

• Product information – Physical stores, EDI, catalogs, face to face, … • Negotiation – Face to face, phone, fax, sealed bids, … • Order placement – Physical store, EDI, phone, fax, face to face, … • Order tracking – EDI, phone, fax, … • Order fulfillment – Customer pick up, physical delivery

Supply Chain Engineering MN 799 274# Potential Revenue Opportunities from E-Business

• Direct sales to customers • 24 hour access for order placement • Accessibility to all customers • Information aggregation • Personalization and Customization of Information • Information sharing in supply chain • Flexibility on pricing and promotion • Price and service discrimination • Faster time to market • Efficient funds transfer - reduce working capital • Disadvantage: Takes longer to deliver, transport costs and shipping time

Supply Chain Engineering MN 799 275# Potential Cost Opportunities from E-Business • Direct customer contact for manufacturers (no handoffs) • Coordination in the supply chain • Customer participation • Postpone product differentiation to after order is placed • Downloadable product • Reduce product handling with shorter supply chain • Reduce facility and processing costs • Geographical centralization and resulting reduction in inventories • Improving supply chain coordination thru information sharing

Supply Chain Engineering MN 799 276# POTENTIAL COST DISADVANTAGES

• INCREASED TRANSPORTATION COSTS – INVENTORY AGGREGRATION – SMALLER, MORE FREQUENT ORDERS • INCREASED HANDLING COSTS – COMPANY HAS TO PICK, PACK AND SHIP • LARGE INITIAL INVESTMENT in INFORMATION INFRASTRUCTURE – PROGRAMMING – WEB SERVERS • SECURITY ?? CASH AND PRODUCT

Supply Chain Engineering MN 799 277# Basic evaluation framework

• How does going on line impact revenues? • How does going on line impact costs? – Facility (site + personnel) – Inventory – Transportation – Information • Should the e-commerce channel position itself for efficiency or responsiveness? • Who in the supply chain can extract most value? • Is the value to existing players or new entrants?

Supply Chain Engineering MN 799 278# The Computer Industry: Dell on-line

Customer Order and Manufacturing Cycle

Customer Order and Procurement cycle Manufacturing Cycle

Procurement Cycle

PUSH PROCESSES PULL PROCESSES

Customer Order Arrives Dell Supply Chain Cycles

Supply Chain Engineering MN 799 279# Potential opportunities exploited by Dell

• Revenue opportunities – 24 hour access for order placement – Direct sales – Providing customization and large selection information – Flexibility on pricing and promotion – Faster time to market – Efficient funds transfer –Negative working capital • Revenue negatives – Longer response time than store and no help with selection

Supply Chain Engineering MN 799 280# Potential opportunities exploited by Dell

• Cost opportunities – Geographical Centralization and reduced inventories (aggregated) – Reduce facility costs – no physical distribution or retail – Direct sales eliminating intermediary – Customer participation: Call center & catalog costs – Information sharing in supply chain – Postpone product differentiation to after order is placed using product platforms and common components • Outbound transportation costs increase

Supply Chain Engineering MN 799 281# Opportunities

• Significant, but must be combined with component commonality, and build to order. Must move product customization to pull phase of supply chain and hold inventories as common components during the push phase • Opportunity most significant for new, hard to forecast products • Complements strength of existing retail channels

Supply Chain Engineering MN 799 282# Retailing: Amazon.com

Customer Customer Pull Pull Amazon Retail Store

Distributor Warehouse (?)

Publisher Publisher

Amazon Supply Chain Bookstore Supply Chain

Supply Chain Engineering MN 799 283# Potential opportunities exploited by Amazon

• Revenue opportunities – 24 hour access for order placement – Providing large selection and other information – Attract customers who do not want to go to store – Flexibility on pricing – Efficient funds transfer • Revenue negatives – Intermediary (distributor) reduces margin – Longer response time than bookstore – Cannot browse

Supply Chain Engineering MN 799 284# Potential opportunities exploited by Amazon

• Cost opportunities – Geographical centralization and reduced inventories: Most effective for low volume, hard to forecast books, least effective for high volume best sellers – Reduce facility costs • Cost increases – Outbound transportation costs increase – Handling cost increase

Supply Chain Engineering MN 799 285# Opportunities

• Going on-line, by itself, offers lower cost advantages (may be some disadvantages) than in Dell model given current form of books • Cost and availability advantages are more significant for low volume books • On-line channel has significant cost benefit if books are downloadable

Supply Chain Engineering MN 799 286# How should bookstore chains react?

• An on line channel allows it to match Amazon‘s revenue advantages • Use a hybrid approach in stocking and pricing – High volume books for local storage – Low volume books for browsing and purchase on line – Pricing varies by delivery and pick up option

Supply Chain Engineering MN 799 287# Grocery on-line

Customer Customer

Supermarket

Online Grocer Warehouse (?)

Manufacturer Suppliers

On-Line Supply Chain Supermarket Supply Chain Ex. Fresh Direct (NY) Supply Chain Engineering MN 799 288# Key Messages

• Some supply chains are better suited to exploit the cost benefits of going on-line – Ability to increase processes in pull phase – Ability to delay product differentiation – Big inventory benefit from geographical centralization – Significant facility cost reduction on centralization – Transport to customer is a small fraction of product cost

All are achieved if product is downloadable

Supply Chain Engineering MN 799 289# B2B: Free Markets

• The worldwide market for direct materials procurement is approximately $5 trillion, with the U.S. segment at approximately $1 trillion Morgan Stanley Dean Witter Internet Industry Research

FreeMarkets is a B2B Internet company that creates online auctions for procurers of direct materials

• MSDW Claim: FreeMarkets’ clients typically achieve savings of 2% to 25%

Supply Chain Engineering MN 799 290# B2B: Matching Base Demand and Capacity

• Potential opportunities – Ability to reach more bidders and get lower unit price – E Bay and Price Line (price set by customer) • Key questions – What does it do to total cost of material? – How many bidders do you need to achieve this? – How does this impact cooperative relationships within supply chain? – Does intermediary provide any value?

Supply Chain Engineering MN 799 291# B2B: Matching Demand Shortage and Surplus Capacity

• Potential opportunities – Ability to aggregate and display all available surplus capacity – Better match of surplus capacity and unmet demand Best provided by an intermediary • Key issue – Total cost (product + transportation + …) must be accounted for in the auction

Supply Chain Engineering MN 799 292# Key Messages

• Significant B2B opportunity to use Internet to reduce cost and improve efficiency of existing processes • Significant B2B opportunity to improve collaboration within existing supply chains • Auction opportunity for B2B is primarily for matching demand shortage with surplus capacity, not for base load

Supply Chain Engineering MN 799 293# USING E-BUSINESS TO CREATE MARKETS

• INTERNET EXCHANGES, MARKETPLACES or PORTALS – – ELECTRONIC MARKETPLACES AND COMMUNITIES OF INTEREST, WHERE COMPANIES/INDIVIDUALS CAN OBTAIN INFORMATION AND BUY AND SELL PRODUCTS. CAN AGGREGRATE DEMAND AND SUPPLY – BUYERS CAN USE EXCHANGES BY: • USING THIRD PARTY TO FACILITATE TRANSACTIONS • CONDUCTING AUCTIONS BETWEEN MANY BUYERS AND SELLERS – ADVANTAGES FOR BUYERS: • REDUCE TRANSACTION COSTS, IMPROVE PERFORMANCE AND COLLOBORATIVE PLANNING WITHIN THE SUPPLY CHAIN • OFFER BUYERs ABILITY TO SEARCH ACROSS MULTIPLE SUPPLIERS • DOWNWARD PRESSURE ON SELLING PRICES – ADVANTAGES FOR SELLERS: • REDUCE REPLENISHMENT LEAD TIME AND BETTER SUPPLY DEMAND MATCH THROUGH IMPROVED COORDINATION • USEFUL IN SELLING SURPLUS INVENTOY & CAPACITY

Supply Chain Engineering MN 799 294# SETTING UP E-BUSINESS IN PRACTICE

• INTEGRATE THE INTERNET WITH THE EXISTING PHYSICAL NETWORK – CLICKS AND MORTAR – SUCCESS CLOSELY LINKED TO DISTRIBUTION CAPABILITIES OF EXISTING SUPPLY CHAIN NETWORK • DEVISE SHIPPING STRATEGIES THAT REFLECT COSTS – MUST INCLUDE SIZE AND WEIGHT CONSIDERATIONS • OPTIMIZE E-BUSINESS LOGISTICS TO HANDLE PACKAGES NOT PALLETS – NEED TO CONSOLIDATE OR BUNDLE, WITH OTHER SUPPLIERS • DESIGN THE E-BUSINESS SUPPLY CHAIN TO HANDLE RETURNS EFFICIENTLY – LIKELY TO BE INCREASED RETURNS – IDEALLY TO ONE LOCATION • KEEP CUSTOMERS INFORMED THROUGHOUT THE ORDER FULFILLMENT CYCLE – STATUS ON LINE

END

Supply Chain Engineering MN 799 295# FINAL EXAM

Supply Chain Engineering MN 799 296# Factory Cash-To-Cash Cycle Time 1. Arrange the trading partner nodes from supplier to customer.

2. Start with a negative number to SUPPLIER represent the time a factory FACTORY has to pay a supplier’s invoice. WHOLESALE 3. Work in a complete, closed loop. RETAIL

CUSTOMER 4. Add the incremental time(s) to send the factory invoice down the chain to the next paying trading partner.

5. Add the incremental time(s) for each node to send the payment back up the chain to the factory.

6. Sum the negative time of step #2 with the positive loop time of step #4, #5.

Supply Chain Engineering MN 799 297# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. Continuously Stocked Items: Optimal Safety Inventory Levels (Eq 11.6)

For each order cycle – Benefit of increasing safety stock by one unit =

(1-CSL)Cu – Cost of increasing safety stock by one unit = HQ*/R where – CSL = probability of not stocking out in a cycle with current level of safety stock = Cycle Service Level – H = cost of holding one unit for one year – R = Annual demand – Q* = Economic order quantity

Supply Chain Engineering MN 799 298# Optimal Safety Inventory Levels (Ex 9.3)

* CSL = 1-(HQ /CuR)

R = 100 gallons/week; sR= 20; H = $0.6/gal./year L = 2 weeks; Q = 400; ROP = 300.

What is the imputed cost of stocking out?

Supply Chain Engineering MN 799 299# Postponement Adds Value Within Logistics By Trading Information For Inventory ―Postponement is delaying product differentiation until the customer demand is known.‖ Corey Billington, Hewlett-Packard Strategic Planning and Modeling

FGI Orders Without Postponement: None

Trading Trading Trading Partner Partner Partner

With Postponement: FGI Orders Trading Trading Postponement Partner Partner None

Design for generic production Postpone to an actual order Supply Chain Engineering MN 799 300# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. Customer Order-To-Delivery Cycle Time

1. Arrange the trading partner nodes from customer to supplier.

2. Work in a complete, closed loop. Customer Order-To-Delivery Cycle Time 3. Add the incremental time(s) to send CUSTOMER the order from the customer to the first node with product inventory. RETAIL WHOLESALE 4. Add the incremental time to pick FACTORY the product from inventory. SUPPLIER 5. Add the incremental time(s) to transport the product to the customer.

Supply Chain Engineering MN 799 301# C 1999. William T. Walker, CFPIM, CIRM with the APICS Educational & Research Foundation. All Rights Reserved. Amazon vs Barnes and Noble

• The effect of Barnes and noble Responsive supply chain strategies today, the company is enhancing its original system by transitioning the back-end services fulfillment systems to an on-line, real-time, Microsoft BackOffice- based shipping, order management, and financial reporting system called PRISM—or Pod Receiving and Integrated Shipping Management System. PRISM allows Barnes and Noble to ship products much faster and deliver higher service levels to customers

Amazon is going to become a market leader because of its early start in Web enabled low-cost access to an infinite number of customers. Treating every customer the same, with limited choice of access, is an unwise Barnes and Noble approach. Amazon has several advantages over Barnes and Noble, which could provide significant competitive leverage, such as: •Real-time customer information and transaction data, •Direct customer "dialog" opportunities, and •Low-cost channel operations

Supply Chain Engineering MN 799 302# Amazon vs Barnes and Noble

• Both have some unpredictable demand and some predictable demand. Yes basically Amazon is efficient and B&N responsive (to a point). Both try and influence demand by suggesting (and discounting) what they have stock in and want purchased. Amazon stocks what it presumes or knows will be best sellers

I see the future bringing down the price of books further (particularly text books) by even more outsourcing. I also see inventory in supply chain reducing by print on demand, especially for books not commonly popular. There will also be a lot more on line books, and condensed books, that one can read or review

The key question is how will Amazon compete with a Chinese or Indian on line supplier with similar products. I do not think it can compete. I see Amazon partnering with a major Chinese and/or Indian company.

As for Barnes and Noble, they have to also move more to print on demand and outsource more (they are already doing a lot of that). They provide a social function that they are emphasizing, so there will be some need for them, but not as a major book supplier

Supply Chain Engineering MN 799 303# Amazon

• The company‘s management has started to expand the business geographically, as well as into new product areas. Amazon now has a U.K. subsidiary, headquartered in Slough, west of London, employing around 500 people — Amazon.co.uk — as well as a slightly smaller German one, Amazon.de, headquartered in Regensburg, Germany. It resoled in increasing the overall sales of the company. Amazon is currently achieving a run rate of $280m a year.

Amazon.co.uk started offering same-day delivery, at least within London... So, provided that customers order within a given time window, they are offered the option of same day delivery as a free upgrade. It resulted in better and efficient customer service than any other online stores.

Identifying desirable global locations for new distribution centers is one use Amazon will make of new supply-chain software from Manugistics of Rockville, Md. It would install Manugistics‘ NetWORKS solutions to support its global expansion and operational improvement initiatives. It will use NetWORKS Strategy to model fixed and variable network costs, taking into consideration such factors as varying transportation and supplier lead times, and global constraints such as tariffs and taxes. The model will then be used to design an optimal global network

Supply Chain Engineering MN 799 304#