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Applichem Case OM 888 Supply Chain Modeling and Analysis

Applichem Case OM 888 Supply Chain Modeling and Analysis

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Page 1: Applichem Case OM 888 Supply Chain Modeling and Analysis

Applichem Case

OM 888

Supply Chain Modeling and Analysis

Page 2: Applichem Case OM 888 Supply Chain Modeling and Analysis

Applichem

• Produces Release-ease, a specialty chemical• 6 plants that manufacture Release-ease

– Gary, Indiana– Frankfurt, Germany– Mexico– Canada– Venezuela– Japan (Sunchem)

• Competitive Situation– Applichem = Market Leader,

Revenues $ 75 Million (1982)• Main competitor has one large plant

Page 3: Applichem Case OM 888 Supply Chain Modeling and Analysis

What is the Objective?

– Minimize cost?• What costs?

– Transportation

– Manufacturing

– Fixed versus variable?

• What are appropriate measures?– How to incorporate exchange rate changes?

– What about different sizes and capabilities of plants?

Page 4: Applichem Case OM 888 Supply Chain Modeling and Analysis

Compare PlantsFactor Gary Canada Frankfurt Mexico Venezuela Sunchem,

Japan Plant Design, Size, Maintenance, etc

1905+ Capacity 18.5M lbs

1955+ Cap. = 3.7M lbs

1960s Cap. = 47M lbs

‘68, similar to Gary Cap. = 22M lbs

‘64, no frills design Cap. = 4.5M lbs

1957 Cap = 5M lbs

Product Variety & Packaging

20 product families 8 formulations (of Release-ease) & 80 package sizes

5 product families Only 50 kg packages

13 products 2 formulations bulk shipments; 50 kg packages

7 products 50 kg packages

2 products 50 kg bags

2 products many ½ kg, 1 kg, etc., packages

Sales Volume & Utilization (1982)

14M lbs or 75.7 %

2.6M lbs or 70.3 %

38M lbs or 80.9 %

17.2M lbs or 78.2 %

4.1M lbs or 91.1 %

4M lbs or 80.0 %

Product Cost $/CWT

102.93 97.35 76.69 95.01 116.34 153.80

Raw Mat’l A Yield & % Active Ingredient

90.4 % & 84.6 91.1 % & 84.7 98.9 % & 84.4 94.7 % & 85.6 91.7 & N/A 98.8 % & 85.4

Others (Labor, etc.)

1000 non-union workers, loyal

Non-union workers, quality conscious

600 workers, two different processes, computer control

Low worker education, serves Far East + local mkt

Low worker education, old equipment

Technically excellent, have test labs, no union but more workers.

Page 5: Applichem Case OM 888 Supply Chain Modeling and Analysis

What measurement should we use?

• What is a fair comparison? (economies of scale, different technologies)– Cost per pound to manufacture? (different costs)– Total labor/volume? (labor costs, packaging issues)– Capital/volume? (capacity issues)– Cost before packaging per pound?

Page 6: Applichem Case OM 888 Supply Chain Modeling and Analysis

Costs at different plants

Total Before PackagingMexico 95.01 92.63Canada 97.35 93.25

Venezuela 116.34 112.31Frankfurt 76.69 73.34

Gary 102.93 89.15Sunchem 153.8 149.24

Cost (1982 $ per cwt)

Total Before PackagingMexico 121.88 118.82Canada 66.31 63.51

Venezuela 67.16 64.83Frankfurt 66.81 63.89

Gary 64.27 55.67Sunchem 119.95 116.39

Cost (1977 $ per cwt)

Page 7: Applichem Case OM 888 Supply Chain Modeling and Analysis

Volume versus Yield

0.88

0.9

0.92

0.94

0.96

0.98

1

0 10 20 30 40

Production Volume

Yie

ld o

n R

aw M

at'l

A

Frankfurt

Mexico

Gary

Sunchem

Venezuela

Canada

Page 8: Applichem Case OM 888 Supply Chain Modeling and Analysis

Too Much Capacity?

Production Idle CapacityMexico 17.2 4.8Canada 2.6 1.1

Venezuela 4.1 0.4Frankfurt 38 9

Gary 14 4.5Sunchem 4 1

Should we close a plant?

Which one?

Might there be reasons for having excess capacity or keeping allplants open?

Total Demand = 79.9 M lbs; Total Capacity = 100.7 M lbs

Safety problems (chemical), transport costs/time, hedging

Page 9: Applichem Case OM 888 Supply Chain Modeling and Analysis

One Approach: LP Model

Purpose Conduct “what-if” analysis to find better network supply chain

structure

ObjectiveMinimize costs measured in some common form (1982 U.S. $)

Decision Variables How much to make at each plant; how much to ship between regions

ConstraintsCapacity constraints, demand limitations, non-negativity (import restrictions, etc.)

DataCosts, import tariffs, exchange rates, capacity/demand info

Page 10: Applichem Case OM 888 Supply Chain Modeling and Analysis

How to Solve?

• Basic “what if” analysis– Trial-and-error– Inefficient, not guaranteed to get optimal solution

• Excel Solver

Still, is this necessarily the best (or even a good) solution?

Things change (exchange rates, inflation, etc.)

http://www.oanda.com/convert/classic

http://www.sunshinecable.com/~eisehan/V80-10en.htm

International Monetary Fund: International Financial Statistics Yearbook.

Page 11: Applichem Case OM 888 Supply Chain Modeling and Analysis

Is there a better way to solve?

S h o w D is trib u tio n o f S im u la tio n R e su lts

G e t G lo b a l A fte r-T a x P ro fit

R u n O p tim iza tio n o f S u p p ly C h a in N e tw o rk

R e ca lcu la te S pre a d sh ee t In p u t

S im u la te S po t E xch a n g e R a tes & D e m a nd

S ta rt

Page 12: Applichem Case OM 888 Supply Chain Modeling and Analysis

What’s the Point?

• Conclusion:

Recourse actions from excess capacity can improve expected profit while reducing risk!

Recourse actions – capacity decisions made before demand realized; production decisions made after demand realized.

Page 13: Applichem Case OM 888 Supply Chain Modeling and Analysis

Other Actions Spadaro Could Take?

• Sharing technology and innovations across plants – Improve Gary’s yield– Reduce costs in Venezuela– Sunchem is high-cost, but also extremely efficient

• What is impact of closure?

– Changing management structure• Ensure technology and improvements transfer• If we close our most technologically advanced plant, what

does this tell others about priorities?

Page 14: Applichem Case OM 888 Supply Chain Modeling and Analysis

Just Can’t Get Enough Applichem…

• Check out:

Lowe et al. “Screening Location Strategies to Reduce Exchange Rate Risk.” European Journal of Operations Research. 2002.

Cohen and Huchzermeier. “Global Supply Chain Management: A Survey of Research and Applications.” Chapter 21 in Quantitative Models for Supply Chain Management. Eds. S. Tayur, R. Ganeshan, M. Magazine. 1999.