Planning Demand and Supply in a Supply Chain

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Planning Demand and Supply in a Supply Chain
????(1) Planning Demand and Supply in a Supply
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Outline

• Part I Aggregate planning
• Part II Managing predictable variability

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Manage Predictable Variability

• Predicable variability is change in demand that
  can be forecasted.
• A firm must choose two broad options
• Manage supply (manage capacity and manage
  inventory)
• Manage demand
• Often companies divide the task
• Marketing manages demand ? maximize revenue
• Operations manage supply ? minimize cost
• Separating the supply and demand decisions makes
  it difficult to coordinate the supply chain
• Designing product flexibility
• Lawn mower manufacturers also make snowblowers

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Managing Predictable Variability- Managing
Supply -

• Managing capacity

• Time flexibility from workforce
• Use of seasonal workforce
• Use of subcontracting
• Use of dual facilities dedicated and flexible
• Designing product flexibility into the production
  processes

• Managing inventory

• Using common components across multiple products
• Building inventory of high demand or predictable
  demand products

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Managing Predictable Variability- Managing
Demand -

• Demand can be influenced using pricing and other
  forms of promotions.

• Four key factors influence the timing of a trade
  promotion

• Impact of the promotion on demand
• Product margins
• Cost of holding inventory
• Cost of changing capacity

• Demand increase from promotion results from three
  factors

• Market growth
• Stealing market share
• Forward buying

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Scenario 4 Aggregate Planning and Promotion at
Red Tomato

• Discounting a unit from 40 to 39 results in the
  period demands increasing by 10 percent because
  of increased consumption or substitution.
  Further, 20 percent of each of the two following
  months demand is moved forward.

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• Consider the discount offering in off-peak month
  of January.
• The demand forecast is shown below

Month Demand Forecast
January 3,000
February 2,400
March 2,560
April 3,800
May 2,200
June 2,200
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Scenario 4 Aggregate Planning and Promotion at
Red Tomato

• Discounting a unit from 40 to 39 results in the
  period demands increasing by 10 percent because
  of increased consumption or substitution.
  Further, 20 percent of each of the two following
  months demand is moved forward.

• Consider the discount offering in off-peak month
  of January.
• The demand forecast is shown below

Month Demand Forecast
January 3,000
February 2,400
March 2,560
April 3,800
May 2,200
June 2,200
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Optimal Aggregate Plan for Scenario 4

• Total cost over planning horizon 421,915
• Revenue over planning horizon 643,400
• Profit over planning horizon 221,485

Period t No. Hired Ht No. Laid Off Lt Workforce Size Wt Overtime Ot Inventory It Stockout St Subcontract Ct Total Production Pt
0 0 0 80 0 1,000 0 0
1 0 15 65 0 610 0 0 2,610
2 0 0 65 0 820 0 0 2,610
3 0 0 65 0 870 0 0 2,610
4 0 0 65 0 0 320 0 2,610
5 0 0 65 0 90 0 0 2,610
6 0 0 65 0 500 0 0 2,610
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Conclusions based on Scenarios 1, 4 5
Scenario 1 Scenario 4 Scenario 5
Cost 422,275 421,915 438,857
Revenue 640,000 643,400 650,140
Profit 217,725 221,485 211,283
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Scenario 5 Aggregate Planning and Promotion at
Red Tomato

• Discounting a unit from 40 to 39 results in the
  period demands increasing by 10 percent because
  of increased consumption or substitution.
  Further, 20 percent of each of the two following
  months demand is moved forward.
• Consider the discount offering in peak month of
  April.
• The demand forecast is shown below

Month Demand Forecast
January 1,600
February 3,000
March 3,200
April 5,060
May 1,760
June 1,760
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Demand fluctuation has increased relative to the
profile in scenario 1.
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Scenario 5 Aggregate Planning and Promotion at
Red Tomato

• Discounting a unit from 40 to 39 results in the
  period demands increasing by 10 percent because
  of increased consumption or substitution.
  Further, 20 percent of each of the two following
  months demand is moved forward.
• Consider the discount offering in peak month of
  April.
• The demand forecast is shown below

Month Demand Forecast
January 1,600
February 3,000
March 3,200
April 5,060
May 1,760
June 1,760
Demand fluctuation has increased relative to the
profile in scenario 1.
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Optimal Aggregate Plan for Scenario 5

• Total cost over planning horizon 438,857
• Revenue over planning horizon 650,140
• Profit over planning horizon 211,283

Period t No. Hired Ht No. Laid Off Lt Workforce Size Wt Overtime Ot Inventory It Stockout St Subcontract Ct Total Production Pt
0 0 0 80 0 1,000 0 0
1 0 14 66 0 2,047 0 0 2,647
2 0 0 66 0 1,693 0 0 2,647
3 0 0 66 0 1,140 0 0 2,647
4 0 0 66 0 0 1,273 0 2,647
5 0 0 66 0 0 387 0 2,647
6 0 0 66 0 500 0 0 2,647
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Conclusions based on Scenarios 1, 4 5
Scenario 1 Scenario 4 Scenario 5
Cost 422,275 421,915 438,857
Revenue 640,000 643,400 650,140
Profit 217,725 221,485 211,283
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Conclusions based on Scenarios 1, 4 5

• A price promotion in January (scenario 4) results
  in a higher profit than no promotion (scenario
  1). A promotion in April (scenario 5) results in
  a lower profit than no promotion (scenario 1).
• Even though revenues are higher when promotions
  is offered in April, the increase in operating
  costs makes it a less profitable option.
• Red Tomato should offer the discount in the
  off-peak month of January.
• The above conclusions could be different if Red
  Tomato were in a situation in which most of the
  demand increase comes from market growth or
  stealing market share rather than forward buying
  (see scenarios 6 7)
• It is not appropriate for a firm to leave pricing
  decisions solely in the domain of marketing and
  aggregate planning solely in the domain of
  operations. It is crucial that forecasts,
  pricing, and aggregate planning be coordinated in
  the supply chain.

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Scenario 6 Aggregate Planning and Promotion at
Red Tomato

• Discounting a unit from 40 to 39 results in the
  period demands increasing by 100 percent because
  of increased consumption or substitution.
  Further, 20 percent of each of the two following
  months demand is moved forward.
• Consider the discount offering in off-peak month
  of January.
• The demand forecast is shown below

Month Demand Forecast
January 4,440
February 2,400
March 2,560
April 3,800
May 2,200
June 2,200
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Scenario 6 Aggregate Planning and Promotion at
Red Tomato

• Discounting a unit from 40 to 39 results in the
  period demands increasing by 100 percent because
  of increased consumption or substitution.
  Further, 20 percent of each of the two following
  months demand is moved forward.
• Consider the discount offering in off-peak month
  of January.
• The demand forecast is shown below

Month Demand Forecast
January 4,440
February 2,400
March 2,560
April 3,800
May 2,200
June 2,200
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Optimal Aggregate Plan for Scenario 6

• Total cost over planning horizon 456,750
• Revenue over planning horizon 699,560
• Profit over planning horizon 242,810

Period t No. Hired Ht No. Laid Off Lt Workforce Size Wt Overtime Ot Inventory It Stockout St Subcontract Ct Total Production Pt
0 0 0 80 0 1,000 0 0
1 0 0 80 0 0 240 0 3,200
2 0 11 69 0 140 0 0 2,780
3 0 0 69 0 360 0 0 2,780
4 0 0 69 0 0 660 0 2,780
5 0 0 69 0 0 80 0 2,780
6 0 0 69 0 500 0 0 2,780
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Conclusions based on Scenarios 1, 6 7
Scenario 1 Scenario 6 Scenario 7
Cost 422,275 456,750 536,200
Revenue 640,000 699,560 783,520
Profit 217,725 242,810 247,320
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Scenario 7 Aggregate Planning and Promotion at
Red Tomato

• Discounting a unit from 40 to 39 results in the
  period demands increasing by 100 percent because
  of increased consumption or substitution.
  Further, 20 percent of each of the two following
  months demand is moved forward.
• Consider the discount offering in peak month of
  April.
• The demand forecast is shown below

Month Demand Forecast
January 1,600
February 3,000
March 3,200
April 8,480
May 1,760
June 1,760
Demand fluctuation has increased relative to the
profile in scenario 1.
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Optimal Aggregate Plan for Scenario 7

• Total cost over planning horizon 536,200
• Revenue over planning horizon 783,520
• Profit over planning horizon 247,320
• When forward buying is a small part of the
  increase in demand from discounting, Red Tomato
  should offer the discount in the peak demand
  month of April.

Period t No. Hired Ht No. Laid Off Lt Workforce Size Wt Overtime Ot Inventory It Stockout St Subcontract Ct Total Production Pt
0 0 0 80 0 1,000 0 0
1 0 0 80 0 2,600 0 0 3,200
2 0 0 80 0 2,800 0 0 3,200
3 0 0 80 0 2,800 0 0 3,200
4 0 0 80 0 0 2,380 100 3,200
5 0 0 80 0 0 940 0 3,200
6 0 0 80 0 500 0 0 3,200
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Conclusions based on Scenarios 1, 6 7
Scenario 1 Scenario 6 Scenario 7
Cost 422,275 456,750 536,200
Revenue 640,000 699,560 783,520
Profit 217,725 242,810 247,320
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Performance Under Different Scenarios
Regular Price Promotion Price Promotion Period Percent Increase in Demand Percent Forward Buy Profit Average Inventory
40 40 NA NA NA 217,725 895
40 39 January 20 20 221,485 523
40 39 April 20 20 211,283 938
40 39 January 100 20 242,810 208
40 39 April 100 20 247,320 1,492
31 31 NA NA NA 73,725 895
31 30 January 100 20 84,410 208
31 30 April 100 20 69,120 1,492
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Conclusions Regarding Promotions

• Pricing and aggregate planning must be done
  jointly.
• Average inventory increases if a promotion is run
  during the peak period and decreases if run
  during off-peak period.
• Promotion during the peak period may decrease
  overall profitability if a significant fraction
  of the demand increase results from a forward
  buy.
• Promotion during the peak period may increase
  overall profitability if forward buying becomes a
  smaller fraction of the demand increase.
• As product margin declines, promotion during the
  peak period becomes less profitable.

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Summary of Impact on Promotion Timing
Factor Favored timing
High forward buying Low demand period
High stealing market share High demand period
High growth of market High demand period
High margin High demand period
Low margin Low demand period
High holding costs Low demand period
High cost of changing capacity Low demand period
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