MIS 3537: Internet and Supply Chainscommunity.mis.temple.edu/mis3537beaver2016/files/2016/04/Wk-14... · MIS 3537: Internet and Supply Chains ... Global Supply Chain Management Simulation

© Enspire Learning and Harvard Business School

1 © Enspire Learning and Harvard Business School (revised Dec 2010)

Week 14:

MIS 3537: Internet and Supply Chains

Global Supply Chain Simulation

Review



End of Class Schedule

•  Today: –  Extra Credit Assignment Due –  Global Supply Chain Simulation Due –  Global SC Simulation Debrief –  Summary Lecture – What did you learn? –  Some Personal Insights (Free? Advice)

•  April 28: Exam 2 –  Similar in format to Exam 1 –  Focus on content since Exam 1 –  Not Open Book – 6 pages of notes allowed



Global SC Sim: Learning Objectives

•  Real World (uncertain) like simulation of Supply Chain Decisions

•  Evaluate forecasting methods and interpret dynamics of a forecasting team

•  Learn trade-offs of Supply Chain flexibility, cost, benefits and profitability

•  Evaluate and learn from process performance measures



Grading

•  Thoughtful Decision Making

•  Integration of Lessons Learned from the Course

•  Continual learning, Improvement over 4 year span of the simulation

•  Long Term Results (Profitability)



Global Supply Chain Management Simulation

Debrief Slides



What did you learn from the Global Supply Chain Simulation?


7 © Enspire Learning and Harvard Business School (revised Dec 2010) 7

Board Members’ Objectives

Member Objective

Betty Forecasting: choice of options (consensus vs. mean)

Doug Forecasting: choice of options (role of risk)

Yvonne Stocking Levels: Weighing the costs of over/understocking

Meryl Production flexibility: accurate response/ sourcing strategy (focus on flexibility)

Paul Production flexibility: accurate response/ sourcing strategy (focus on demand uncertainty)



1. Betty?



1. Betty: Forecasting Room Choices •  Consensus forecasts can be

problematic: –  Can be skewed by interpersonal

dynamics: e.g. person with power or “squeaky” wheel can dominate

–  Can lose valuable information about variance in opinions

•  Betty believes that using the mean of the forecasters for your point estimate is a better choice than the consensus.

•  Betty withholds her vote if you choose an option that has: –  Consensus forecast á, –  Mean forecast â, and –  No change in profitability



The Details: Betty’s Criteria

Betty withholds her vote if you choose a High Consensus/Low Mean option.

There were 6 such options (Model A):

Year Option Margin Cons. Mean Std Dev1 Color $0 1 -4 92 Battery $0 2 -3 83 Battery $0 2 -3 63 Anti-Theft $0 3 -2 64 Anti-Theft $0 2 -2 74 DVD $0 3 -2 6

Demand EstimatesHigh Consensus/Low Mean



2. Doug?



2. Doug: Forecasting Room Choices

•  It is critical to consider forecast variance when making product design decisions and production planning decisions.

•  High variance among forecasters is often a sign of demand uncertainty. Doug believes the slight increase in demand may not be worth the associated risk.

•  Doug withholds his vote if you choose an option that has: –  High risk (high standard deviation

among forecasters) –  Low (or no) increase in demand –  No change in profitability



The Details: Doug’s Criteria

Doug withholds his vote if you choose a High Variance/Low Mean option

There were 4 such options (Model A):

Year Option Margin Cons. Mean Std Dev1 SmartWifi $0 1 0 132 Voice Dial $0 0 0 113 Voice Dial $0 0 0 134 Slim $0 3 -1 9

High Variance/Low Mean Demand Estimates



Full Option Detail (Model A) Year Option Margin Cons. Mean Std Dev1 SmartWifi $0 1 0 132 Voice Dial $0 0 0 113 Voice Dial $0 0 0 134 Slim $0 3 -1 9

Year Option Margin Cons. Mean Std Dev1 Color $0 1 -4 92 Battery $0 2 -3 83 Battery $0 2 -3 63 Anti-Theft $0 3 -2 64 Anti-Theft $0 2 -2 74 DVD $0 3 -2 6

Year Option Margin Cons. Mean Std Dev1 Style $5 -2 -1 21 Infrared $3 0 -1 32 Style $9 -3 -1 22 Infrared $3 -1 -1 33 Speakers $5 2 1 24 Speakers $5 2 1 2

Demand Estimates

Demand Estimates

Demand Estimates

High Consensus/Low Mean

High Variance/Low Mean

Positive Margin/Low Variance



3. Yvonne?



3. Yvonne: Risks of Over- and Underproduction •  When planning production levels, it is

important to weigh all costs. •  “Indirect costs” such as stockout and

markdown or liquidation costs are often not obvious on a P & L, but can be significant.

•  “Newsvendor problem” in complex setting

•  Yvonne looks at your expected ending inventory. You get her vote if you choose to:

–  Overproduce when the markdown cost < stockout cost

–  Underproduce when the markdown cost > stockout cost



The Details: Production Levels In year 1, the cost structures and demand forecasts (assuming no options are):

Assuming there is no chance to adjust production levels later, For Model A, Cu ($70) > Co ($13), suggesting we should

stock above expected demand (60) for Model A For Model B, Cu ($90) < Co ($105), suggesting we should

below expected demand (30) for Model B

Cost Structure Model A Model BSelling Price 200$ 240$ Cost 130$ 150$ Liquidation Value 117$ 45$ Expected Monthly Demand 60 30

Cu = Selling Price - Cost 70$ 90$ Co* = Cost - Liquidation Value 13$ 105$

*Ignoring inventory carrying costs



Simplification: Planning for One Month For example, if we were planning only for one month – December, with no opportunity to replenish, a Newsvendor approach* would suggest the following stocking levels:

*Ignoring inventory carrying costs

As expected, we stock above the mean for A and below the mean for B.

Underage/Overage Costs Model A Model BCu = Selling Price - Cost 70$ 90$ Co = Cost - Liquidation Value 13$ 105$ Monthly Demand ForecastMean 60 30Standard Deviation 4 9

Newsvendor AnalysisNewsVendor Ratio: Cu/(Co+Cu) 84% 46%NewsVendor Stocking Level 64 29



The Full Complexity

The simulation problem is much more difficult than a simple “newsvendor” problem analysis:

1.  There is an opportunity to raise or lower production quantities for a $2 million charge.

2.  Capacity constraints must be incorporated. 3.  Lead times, which vary by supplier, must be incorporated. 4.  Month to month, the overage cost is only the inventory

carrying cost, since the liquidation cost is not realized until the end of the season. Thus, we are induced to carry higher inventories on a month-to-month basis than the newsvendor analysis suggests to avoid stock-outs, and can issue a production order later to avoid liquidations.



4. Meryl?



4. Meryl: Accurate Response/Sourcing Strategy •  When demand is uncertain, a hybrid

production strategy using a combination of slow, low-cost capacity and fast, more expensive capacity can increase profits by decreasing indirect costs (markdowns and stockouts) while keeping direct costs (e.g. labor costs) relatively low.

•  Meryl believes it is worth investing in production flexibility and adjusting production after real demand patterns are observed

•  Meryl gives her vote if: –  You source some, but not all, of your

production with the more responsive reactive suppliers and

–  You issue a change order after some demand is observed, but early enough to make an impact large enough to justify the cost



5. Paul?



5. Paul: Accurate Response/Sourcing Strategy

•  Expensive reactive suppliers should be used to adjust to the fluctuating portion of demand.

•  Suppliers with long lead times and lower direct costs should be used to produce goods for which demand is more predictable.

•  Paul gives his vote if: –  In the early months of production

before change orders are issued, the reactive supplier produces a greater percentage of the product with the less certain demand (usually model B)



-

100

200

300

400

500

600

700

800

May Jun Jul Aug Sep Oct Nov Dec

Month

Units

M odel A Forecasts:Mean + Std. Dev.

Mean - Std. Dev.

Mean

M odel B Forecasts:Mean + Std. Dev.

Mean - Std. Dev.

Mean

Model B Actual

Model A Actual

MODELS A - Y1 B - Y1Fcst Avg 60 30 Act Avg 54 35

Act Over Fcst 89% 117%

Demand Analysis, Year 1



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100

200

300

400

500

600

700

800


Month

Units


Mean - Std. Dev.

Mean


Mean - Std. Dev.

Mean

Model B Actual

Model A Actual

MODELS A - Y2 B - Y2Fcst Avg 57 34

Actual Avg 68 24 Act Over Fcst 119% 70%




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100

200

300

400

500

600

700

800


Month

Units


Mean - Std. Dev.

Mean


Mean - Std. Dev.

Mean

Model B Actual

Model A Actual






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100

200

300

400

500

600

700

800


Month

Units


Mean - Std. Dev.

Mean


Mean - Std. Dev.

Mean

Model B Actual

Model A Actual






Other Simulation Data

(optional)



SFF: Student Feedback Forms

•  Value v Your feedback already (after test, etc.) has

already helped me improve the class v Better class for subsequent students and to FOX MIS

in total

•  Request v  Have you received the e-SFF e-mail?? v  Take 10-15 minutes to complete – NOW! v  http://esff.temple.edu



Event Data

Year 1 Year 2 Year 3 Year 4

Jan

Feb

Mar Celldex Celldex Celldex Celldex

Apr

May

Jun

Jul Price war Senior citizens

AugHigh end gadgets

take off Cancer scare

SepMultiple phone

sales -- stockouts

OctBacklash leads to cell phone bans

NovBack-to-basics

Xmas Technophobe cults

Dec



Basic Models: Demand Data; Cost Structure MODELS A - Y1 B - Y1 A - Y2 B - Y2 A - Y3 B - Y3 A - Y4 B - Y4

Name Model A Model B Model A Model B Model A Model B Model A Model BPrice 200 240 200 240 200 240 200 240Cost 130 150 130 150 130 150 130 150Tim 63 36 60 40 67 34 65 31

Stacey 54 18 51 22 58 16 56 33Joe 64 38 61 42 68 36 66 13

Isabelle 59 28 56 32 63 26 61 23Ruth 64 38 61 42 68 36 66 33

Yi 56 22 53 26 60 20 58 17Consensus 63 33 56 36 66 32 60 28CelldexEst 54 35 69 26 63 25 54 36

May 53 34 67 24 64 26 54 34Jun 55 39 67 29 60 24 51 33Jul 55 36 65 24 65 26 53 31

Aug 55 32 70 22 65 25 53 37Sep 54 36 69 23 65 21 53 39Oct 51 38 70 24 60 19 53 39Nov 54 34 67 23 60 18 54 39Dec 52 32 67 22 57 16 55 46

Mkdwn% 90% 30% 90% 30% 90% 30% 90% 30%InvCarry% 2% 2% 2% 2% 2% 2% 2% 2%

OptDemAmp 100% 150% 100% 150% 100% 150% 100% 150%CelldexCost 2,000 2,000 2,000 2,000 2,000 2,000 2,000 2,000 EstAverage 60 30 57 34 64 28 62 25 ActAverage 54 35 68 24 62 22 53 37 ActOverEst 89% 117% 119% 70% 97% 78% 86% 149%



Option Data : Demand Data; Cost Structure

OPTIONS O1 -Y1 O2-Y1 O3-Y1 O4-Y1 O1-Y2 O2-Y2 O3-Y2 O4-Y2 O1-Y3 O2-Y3 O3-Y3 O4-Y3 O1-Y4 O2-Y4 O3-Y4 O4-Y4

Name Wifi Color Stylish Infrared Stylish InfraredExtra Battery

Voice Dial

Extra Battery

Voice Dial

AntiTheft

Speakers

AntiTheft

Speakers

Super-slim

Mini-DVD

Type 3 2 1 1 1 1 2 3 2 3 2 1 2 1 3 2PriceAdj 30 15 10 5 12 5 20 15 14 11 40 15 35 12 25 50

CostAdjust 30 15 5 2 3 2 20 15 14 11 40 10 35 7 25 50Tim 10 4 -2 -3 -3 -1 7 10 -13 12 -12 -1 -10 -1 10 -12

Stacey -12 6 2 2 3 1 5 -12 4 -13 6 4 6 6 13 6Joe 13 -14 -4 -4 -4 -3 -13 -8 -9 11 -10 -2 6 -4 -12 -10

Isabelle -8 12 -3 -4 -2 -2 -11 13 8 -7 8 0 -10 0 -8 8Ruth -5 1 -3 -1 -2 -3 -8 -5 -8 -5 -7 -1 -7 -1 -5 -7

Yi 2 -9 4 4 2 2 2 2 0 2 3 6 3 6 -4 3Consens 1 1 -2 0 -3 -1 2 0 2 0 3 2 2 2 3 3

ActAverage 0 -4 -1 -1 -1 -1 -3 0 -3 0 -2 1 -2 1 0 -2EstAverage 0 0 -1 -1 -1 -1 -3 0 -3 0 -2 1 -2 1 -1 -2



Supplier Data

FarFarAway FarAway Pretty Close Ve-Ri-FasSet-up Cost 1,000,000$ 2,000,000$ 1,000,000$ 2,000,000$

Incremental Unit Cost - - 10$ 10$ Leadtime (months) 4 3 0 0Monthly Capacity 60,000 60,000 35,000 40,000

Min Prod'n Level 60% 60% 60% 60%Prod'n Change Cost 2,000 2,000 2,000 2,000

Documents

MIS 3537: Internet and Supply Chainscommunity.mis.temple.edu/mis3537beaver2016/files/2016/04/Wk-14... · MIS 3537: Internet and Supply Chains ... Global Supply Chain Management Simulation