Planning Demand and Supply in a Supply Chain

1
Planning Demand and Supply in a Supply Chain

• Forecasting and Aggregate Planning
• Chapters 8 and 9

2
Learning Objectives

• Overview of forecasting
• Forecast errors
• Aggregate planning in the supply chain
• Managing demand
• Managing capacity

3
Phases of Supply Chain Decisions

• Strategy or design Forecast
• Planning Forecast
• Operation/Execution Actual demand
• Since actual demands differ from the forecasts,
  
• so does the execution from the plans.
• E.g. Supply Chain degree plans for 40 students
  per year whereas the actual is ??

4
Characteristics of forecasts

• Forecasts are always wrong. Include expected
  value and measure of error.
• Long-term forecasts are less accurate than
  short-term forecasts.
• Too long term forecasts are useless Forecast
  horizon
• Forecasting to determine
• Raw material purchases for the next week
  Ericsson
• Annual electricity generation capacity in TX for
  the next 30 years Texas Utilities
• Boat traffic intensity in the upper Mississippi
  until year 2100 Army Corps of Engineers
• Aggregate forecasts are more accurate than
  disaggregate forecasts
• Variance of aggregate is smaller because extremes
  cancel out
• Two samples 3,5 and 2,6.
• Averages 4 and 4.
• Totals 8 and 8.
• Variance of sample averages/totals0
• Variance of 3,5,2,65/2
• Several ways to aggregate
• Products into product groups Telecom switch
  boxes
• Demand by location Texas region
• Demand by time April demand

5
Forecasting Methods

• Qualitative
• Expert opinion
• E.g. Why do you listen to Wall Street stock
  analysts?
• What if we all listen to the same analyst? S/He
  becomes right!
• Time Series
• Static
• Adaptive
• Causal Linear regression
• Forecast Simulation for planning purposes

6
Components of an observation

• Observed demand (O)
• Systematic component (S) Random component (R)
• A touch of philosophy
• Is the world random or everything is
  pre-determined?
• Pragmatic answer
• Everything we cannot afford to study in detail
  is random!

Level (current deseasonalized demand)
Trend (growth or decline in demand)
Seasonality (predictable seasonal fluctuation)
7
Time Series Forecasting
Forecast demand for the next four quarters.
8
Time Series Forecasting
9
Master Production Schedule (MPS)

• MPS is a schedule of future deliveries. A
  combination of forecasts and firm orders.

10

• Aggregate Planning
• Chapter 8

11
Aggregate Planning (Ag-gregate Past part. of
Ad-gregare Totaled)

• If the actual is different than the plan, why
  bother sweating over detailed plans
• Aggregate planning General plan for our
  frequency decomposition
• Combined products aggregate product
• Short and long sleeve shirts shirt
• Single product
• AC and Heating unit pipes pipes at Lennox Iowa
  plant
• Pooled capacities aggregated capacity
• Dedicated machine and general machine machine
• Single capacity
• E.g. SOM has 100 instructors
• Time periods time buckets
• Consider all the demand and production of a given
  month together
• When does the demand or production take place in
  a time bucket?
• Increase the number of time buckets decrease the
  bucket length.

12
Fundamental tradeoffs in Aggregate Planning

• Capacity Regular time, Over time, Subcontract?
• Inventory Backlog / lost sales, combination
  Customer patience?
• Basic Strategies
• Chase (the demand) strategy produce at the
  instantaneous demand rate
• fast food restaurants
• Level strategy produce at the rate of long run
  average demand
• swim wear
• Time flexibility high levels of workforce or
  capacity
• machining shops, army
• Deliver late strategy
• spare parts for your Jaguar

13
Matching the Demand
- Which is which? Level Deliver
late Chase Time flexibility
Adjust the capacity to match the demand
Demand
Use capacity
Demand
Demand
Use inventory
Use delivery time
Demand
14
Capacity Demand Matching Inventory/Capacity
tradeoff

• Level strategy Leveling capacity forces
  inventory to build up in anticipation of seasonal
  variation in demand
• Chase strategy Carrying low levels of inventory
  requires capacity to vary with seasonal variation
  in demand or enough capacity to cover peak demand
  during season

15
Case Study Aggregate planning at Red Tomato

• Farm tools
• Shovels
• Spades
• Forks
• Aggregate by similar characteristics

Same characteristics?
Generic tool, call it Shovel
16
Aggregate Planning at Red Tomato Tools
17
Aggregate Planning
What is the cost of production per tool? That is
materials plus labor. Overtime production is
more expensive than subcontracting. What is the
saving achieved by producing a tool in house
rather than subcontracting?
18
1. Aggregate Planning (Decision Variables)

• Wt Number of employees in 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 units of shovels in month t, t
  1, ..., 6
• It Inventory at the end of month t, t 1, ...,
  6
• St Number of units backordered 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
• Did we aggregate production capacity?

19
2. Objective Function

• 3. Constraints
• Workforce size for each month is based on hiring
  and layoffs

• Production (in hours) for each month cannot
  exceed capacity (in hours)

20
3. Constraints

• Inventory balance for each month

Period t1
Period t
Period t-1
21
3. Constraints

• Overtime for each month

22
Execution

• Solve the formulation, see Table 8.3
• Total cost422.275K, total revenue640K
• Apply the first month of the plan
• Delay applying the remaining part of the plan
  until the next month
• Rerun the model with new data next month
• This is called rolling horizon execution

23
Aggregate Planning at Red Tomato Tools
This solution was for the following demand
numbers
What if demand fluctuates more?
24
Increased Demand Fluctuation
Total costs432.858K. 16000 units of total
production as before why extra cost? With
respect to 422.275K of before.
25

• Manipulating the Demand
• Chapter 9

26
Matching Demand and Supply

• Supply Demand
• Supply lt Demand gt Lost revenue opportunity
• Supply gt Demand gt Inventory
• Manage Supply Productions Management
• Manage Demand Marketing

27
Managing Predictable Variability with Supply

• Manage capacity
• Time flexibility from workforce (OT and
  otherwise)
• Seasonal workforce, agriculture workers
• Subcontracting
• Counter cyclical products complementary products
• Similar products with negatively correlated
  demands
• Snow blowers and Lawn Mowers
• AC pumps and Heater pumps
• Flexible capacities/processes Dedicated vs.
  flexible

a
d
d
a
a,b, c,d
c
c
b
b
Similar capabilities
One super facility
28
Managing Predictable Variability with Inventory

• Component commonality
• Remember fast food restaurant menus
• Component commonality increase the benefit of
  postponement.
• More on this later
• Build seasonal inventory of predictable products
  in preseason
• Nothing can be learnt by procrastinating
• Keep inventory of predictable products in the
  downstream supply chain

29
Managing Predictable Variability with
PricingRevisit Red Tomato Tools

• Manage demand with pricing
• Original pricing
• Cost 422,275, Revenue 640,000,
  Profit217,725
• Demand increases from discounting
• Market growth
• Stealing market share from competitors
• Forward buying
• stealing your own market share from the future
• Discount of 1 in a period increases that
  periods demand by 10 (market and market share
  growth) and moves 20 of next two months demand
  forward
• Can you gather this information price
  sensitivity of the demand- easily? Does your
  company have this information?

30
Off-Peak (January) Discount from 40 to 39
Cost 421,915, Revenue 643,400, Profit
221,485
31
Peak (April) Discount from 40 to 39
Cost 438,857, Revenue 650,140, Profit
211,283 Discounting during peak increases the
revenue but decreases the profit!
32
Demand Management

• Pricing and Aggregate Planning must be done
  jointly
• Factors affecting discount timing and their new
  values
• Consumption 100 increase in consumption instead
  of 10 increase
• Forward buy, still 20 of the next two months
• Product Margin Impact of higher margin. What if
  discount from 31 to 30 instead of from 40 to
  39.)

33
January Discount 100 increase in consumption,
sale price 40 (39)
Off peak discount Cost 456,750, Revenue
699,560 Profit242,810
34
Peak (April) Discount 100 increase in
consumption, sale price 40 (39)
Peak discount Cost 536,200, Revenue
783,520 Profit247,320
35
Performance Under Different Scenarios
Use rows in bold to explain Xmas discounts. The
product, with less (forward buying/market growth)
ratio, is discounted more. What gift should you
buy on the special days (peak demand) when
retailers supposedly give discounts? E.g. Think
of flowers on valentines day. How about
diamonds? For flowers, what is (forward
buying/market growth) due to discounting? How
about for diamonds? Need empirical data. What
is available?
36
Empirical Data Who spends / How much on
Valentines day

• The average consumer spends 122.98 on 2008
  Valentines Day, similar to 119.67 of 2007.
  Total US spending on Valentines Day is 17.02 B
  by 18.
• Spending
• by gender
• Men again dishes out the most in 2008, spending
  an average of 163.37 on gifts and cards,
  compared to an average of 84.72 spent by women.
• by age
• Adults 25-34 spend 160.37.
• Young adults 18-24 spend 145.59.
• Upper Middle age 45-54 spend 117.91.
• Lower Middle age 35-44 spend 116.35.
• Elderly 55-64 spend 110.97.
• Gifts
• 56.8 of all consumers give a greeting card.
• 48.2 plan a special night out.
• 48.0 buy candy.
• 35.9 buy flowers.
• 12.3 give a gift card.
• 11.8 buy clothing.
• ??.? buy diamonds
• Source National Retail Federation www.nrf.com

Where is forward buy or market growth due to
discounting?
37
Factors Affecting Promotion Timing
38
Aside Continuous Compounding

• If my 1investment earns an interest of r per
  year, what is my interestinvestment at the end
  of the year?
• Answer (1r)
• If I earn an interest of r/2 per six months, what
  is my interest investment at the end of the
  year?
• Answer (1r/2)2
• If I earn an interest of (r/m) per (12/m) months,
  what is my interestinvestment?
• Answer (1r/m)m
• Think of continuous compounding as the special
  case of discrete-time compounding when m
  approaches infinity.
• What if I earn an interest of (r/infinity) per
  (12/infinity) months?

See the appendix of scaggregate.pdf for more on
continuous compounding.
39
Deterministic Capacity Expansion Issues

• Single vs. Multiple Facilities
• Dallas and Atlanta plants of Lockheed Martin
• Single vs. Multiple Resources
• Machines and workforce or aggregated capacity
• Single vs. Multiple Product Demands
• Have you aggregated your demand when studying the
  capacity?
• Expansion only or with Contraction
• Is there a second-hand machine market?
• Discrete vs. Continuous Expansion Times
• Can you expand SOM building capacity during the
  spring term?
• Discrete vs. Continuous Capacity Increments
• Can you buy capacity in units of 2.313832?
• Resource costs, economies of scale
• Penalty for demand-capacity mismatch
• Recallable capacity Electricity block outs vs
  Electricity buy outs
• Happens in Wisconsin Electricity market
• What if American Airlines recalls my ticket
• Single vs. Multiple decision makers

40
A Simple Model

• No stock outs. x is the size of the capacity
  increments.
• d is the increase rate of the demand.

41
Infinite Horizon Total Discounted Cost

• f(x) is expansion cost of capacity increment of
  size x

• C(x) is the long run (infinite horizon) total
  discounted
• expansion cost

42
Solution of the Simple Model
Solution can be Each time expand capacity by an
amount that is equal to 30-week demand.
43
Shortages, Inventory Holding, Subcontracting

• Use of Inventory and subcontracting to delay
  capacity expansions

44
Stochastic Capacity Planning The case of
flexible capacity
y1A1, y2A1, y3A0
y1B0, y2B0, y3B1
Products

• Plant 1 and 2 are tooled to produce product A
• Plant 3 is tooled to produce product B
• A and B are substitute products
• with random demands DA DB Constant

45
Capacity allocation

• Say capacities are r1r2 r3100
• Suppose that DA DB 300 and DA gt100 and DB gt100

With plant flexibility y1A1, y2A1, y3A0,
y1B0, y2B0, y3B1.
Scenario DA DB X1A X2A X3A X1B X2B X3B Shortage
1 200 100 100 100 100 0
2 150 150 100 50 100 50 B
3 100 200 100 0 100 100 B
If the scenarios are equally likely, expected
shortage is 50.
46
Capacity allocation with more flexibility

• Say capacities are r1r2 r3100
• Suppose that DA DB 300 and DA gt100 and DB gt100

With plant flexibility y1A1, y2A1, y3A0,
y1B0, y2B1, y3B1.
Scenario DA DB X1A X2A X3A X1B X2B X3B Shortage
1 200 100 100 100 0 100 0
2 150 150 100 50 50 100 0
3 100 200 100 0 100 100 0
Flexibility can decrease shortages. In this
case, from 50 to 0.
47
A Formulation with Known Demands Djdj

• i denotes plants
• j denotes products, not necessarily substitutes
• cij tooling cost to configure plant i to produce
  j
• mj contribution to margin of producing/selling a
  unit of j
• ri capacity at plant i
• Djdj product j demand
• yij1 if plant i can produce product j, 0 o.w.
• xijunits of j produced at plant i

Solutions depend on scenarios
- If DA200 and DB100, then y1Ay2Ay3B1.
- If DA100 and DB200, then y1Ay2By3B1.
48
Unknown Demands Djdjk with probability pk

• Djdjk product j demand
• under scenario k
• xijk units of j produced
• at plant i if scenario k
• happens
• yij1 if plant i can produce
• product j, 0 o.w.
• Does yij differ under
• different scenarios?
• Should my variable depend on scenarios? (Yes /
  No)
• Anticipatory variable and Nonanticapatory
  variable

49
Reality Check How do car manufacturers assign
products to plants?

• With the last formulation, we treated the problem
  of assigning products to plants.
• This type of assignment called for
  tooling/preparation of each plant appropriately
  so that it can produce the car type it is
  assigned to.
• These tooling (nonanticipatory) decisions are
  made at most once a year and manufacturers work
  with the current assignments to meet the demand.
  
• When market conditions change, the
  product-to-plant assignment is revisited.
• Almost all car manufacturers in North America are
  retooling their previously truck manufacturing
  plants to manufacture compact cars as consumer
  demand basically disappeared for trucks with high
  gas prices.
• Also note that the profit margin made from a
  truck sale is 2-5 times more than the margin made
  from a car sale. No wonder why manufacturers
  prefer to sell trucks!
• In the following pages, you will find the product
  to plant assignment of major car manufacturers in
  the North America. These assignments were
  updated in the summer of 2008 just about the time
  when manufacturers started talking about
  retooling plants to produce compact cars.

50
All of Toyota Plants in the North America
Toyota. Cambridge Corolla, Matrix, Lexus, Rav4
Toyota-Subaru. LaFayette Camry
Nummi Toyota-GM. Freemont. Corolla, Tacoma,
Pontiac Vibe
Toyota. Princeton Tundra, Suquoia, Sienna
Toyota. Georgetown Avalon, Camry, Solara
Toyota. Long Beach Hino
Toyota. Blue Springs Highlander
Toyota. Tijuana, Mexico Tacoma
Toyota. San Antonio Tundra
51
All of Honda Plants in the North America
Honda. Alliston, Ca. Civic, Acura, Odyssey,
Pilot, Ridgeline
Honda. Decatur TBO in 2008
Honda. Marysville Accord, Acura
Honda. Lincoln Odyssey, Pilot
Honda. El Salto, Me Accord
52
All of Nissan Plants in the North America
Nissan. Smyrna Frontier, Xterra, Altima, Maxima,
Pathfinder
Nissan. Canton Quest, Armada, Titan, Infiniti,
Altima
53
All of Hyundai-Kia Plants in the North America
Kia. LaGrange TBO in 2009
Hyundai. Montgomery Sonata, Santa Fe
54
All of Mercedes and BMW Plants in the North
America
BMW. Spartanburg Z4, X5, X6 M roadster, coupes
Mercedes. Tuscaloosa M, R classes
55
All of Ford Plants in the North America
Ford. Oakville, Ca. Edge, Lincoln MKX
Ford. Dearborn F-150, Lincoln Mark LT
Ford. Saint Paul Ranger, Mazda B series
Ford. Saint Thomas, Ca. Crown Victoria, Grand
Marquis
Ford. Flat Rock Mustang, Mazda 6
Ford. Wayne Focus, Expedition, Lincoln Navigator
Ford. Chicago Taurus, Mercury Sable
Ford. Avon Lake E Series
Ford. Kansas City Escape, Escape Hybrid, Mazda
Tribute, Mercury Mariner, F-150
Ford. Louisville F-250, F-550, Explorer, Mercury
Mountaineer
Ontario, Michigan, Illinois, Indiana, Ohio in
Focus
Ford. Hermosillo, Mex. Ford Fusion, Lincoln MKZ,
Mercury Milan
Ford. Cuatitlan, Mex. F-150, 250, 350, 450,
550,Ikon
56
All of Chrysler Plants in the North America
Chrysler. Sterling Heights Dodge Avenger,
Chrysler Sebring
Chrysler. Brampton, Ca Chrysler 300, Dodge
Challenger, Dodge Charger
Chrysler. Warren Dodge Ram, Dakota, Mitsubishi
Raider
Chrysler. Detroit-Jefferson North Jeep Grand
Cherokee and Commander
Chrysler. Detroit-Conner Ave. Dodge Viper, SRT 10
Roadster
Chrysler. Windsor, Ca Dodge Grand Caravan,
Chrysler Town
Chrysler. Newark Dodge Durango, Chrysler
Aspen Will close in 2009
Chrysler. Belvidere Dodge Caliber, Jeep Compass,
Jeep Patriot
Chrysler. Toledo Jeep Liberty, Dodge Nitro
Chrysler. Fenton-North Dodge Ram
Chrysler. Fenton-South Grand Voyager, Grand
Caravan, Cargo Van
Ontario, Michigan, Illinois, Indiana, Ohio in
Focus
Chrysler. Saltillo, Mex. Dodge Ram
Chrysler. Toluca, Mex. Chrysler PT Cruise, Dodge
Journey
57
All of GM Plants in the North America
GM. Oshawa, Ca Chevy Impala, Buick Allure, Chevy
Silverado, GMC Sierra. Trucks will stop in 2009.
GM. Orion Pontiac G6, Chevrolet Malibu
GM. Lansing-Grand River Cadillac E-SRX
GM. Lansing-Delta Township Buick Enclave, Saturn
Outlook, GMC Acadia
GM. Flint GMC Sierra, Chevy Silverado, Chevy -
GMC medium trucks.
GM. Pontiac Chevy Silverado, GMC Sierra
GM. Detroit Buick Lucerne, Cadillac DTS
GM. Janisville Chevy Tahoe, Suburban, GMC
Yukon Will stop in 2010
GM. Wilmington Saturn L series, Pontiac Solstice
GM. Fort Wayne Chevy Silverado, GMC Sierra
GM. Fairfax Chevy Malibu, Malibu Maxx, Saturn Aura
GM. Bowling Green Cadillac XLR, Chevy Corvette
GM. Moraine Chevy Trailblazer, GMC Envoy,
Oldsmobile Bravada, Isuzu Ascender, Saab
9-7X Will stop in 2010
GM. Wentzville Chevy Express, GMC Savana
GM. Lordstown Chevy Cobalt, Pontiac Pursuit, G4,
G5
GM. Spring Hill Saturn Ion and Vue Currently down
GM. Doraville Chevy Uplander, Pontiac Montana
GM. Arlington Chevy Tahoe, Suburban, GMC Yukon,
Cadillac Escalade
Ontario, Michigan, Illinois, Indiana, Ohio in
Focus
GM. Shreveport Chevy Colorado, GMC Canyon, Isuzu
brands, Hummer H3
GM. Ramos Arizpe, Mex. Pontiac Aztek, Chevy
Cavalier, Chevrolet Checy, Pontiac Sunfire, Buick
Rendezvous
GM. Silao, Mex. Chevrolet Suburban, Chevrolet
Avalanche, GMC Yukon, Cadillac Escalade
GM. Toluca, Mex. Chevrolet Kodiak Truck Stopping
in 2008
58
Summary of Learning Objectives

• Forecasting
• Aggregate planning
• Supply and demand management during aggregate
  planning with predictable demand variation
• Supply management levers
• Demand management levers
• Capacity Planning

59
Material Requirements Planning

• Master Production Schedule (MPS)
• Bill of Materials (BOM)
• MRP explosion
• Advantages
• Disciplined database
• Component commonality
• Shortcomings
• Rigid lead times
• No capacity consideration

60
Optimized Production Technology

• Focus on bottleneck resources to simplify
  planning
• Product mix defines the bottleneck(s) ?
• Provide plenty of non-bottleneck resources.
• Shifting bottlenecks

61
Just in Time production

• Focus on timing
• Advocates pull system, use Kanban
• Design improvements encouraged
• Lower inventories / set up time / cycle time
• Quality improvements
• Supplier relations, fewer closer suppliers,
  Toyota city
• JIT philosophically different than OPT or MRP, it
  is not only a planning tool but a continuous
  improvement scheme