gupta tea co. amanda miller kent mckimmy cole hunstad kevin angell chad wellsted

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  • Slide 1
  • Gupta Tea Co. Amanda Miller Kent McKimmy Cole Hunstad Kevin Angell Chad Wellsted
  • Slide 2
  • Background Tea company based in Dallas Texas First started growing selling tea Moved into food retail with increased competition Purchase grow and produce most of products
  • Slide 3
  • Background Four plants located throughout U.S.A Five Consolidated Metropolitan Statistical Area (CMSA) New York, St. Louis, Chicago, Miami, Los Angeles Shipping warehouses in each CSMA for distribution
  • Slide 4
  • Background Four small plants with fixed design layout Each plant has capacity of 6000 units This years sales demand of 20000 Four plants currently only producing 5000 units
  • Slide 5
  • Background on Case Increase in health tea food competition Despite marketing efforts sales still declining Underutilized/inefficient plants cause increased tea prices Used Delphi method to consider next move
  • Slide 6
  • Detail on case Market analyst showed decrease in forecasted sales Projected sales in 2 years of 15000 Shut down one plant = 20000-5000=15000 keep prices competitive Takes 2 years to officially close plant CSMAs have relative same decrease in sales Which Plant to Close???
  • Slide 7
  • Sales Forecast Data
  • Slide 8
  • Shipping Cost Data
  • Slide 9
  • Total Shipping Costs & Averages Plant Average Shipping Costs($) Plant 132.4 Plant 236 Plant 335.2 Plant 428.6 Average Shipping costs= Total shipping costs (NY)+(STL)+(LA)+(CH)+(Miami) /5 Total Shipping Costs for all demand = (45*3350)+(30*2650)+. For each plant and CMSA Plants New YorkSt. LouisLos AngelesChicagoMiami Total Cost Plant 11507507950019000117250157500524000 Plant 2117250742009690083750153750525850 Plant 31239505300010640093800131250508400 Plant 41072003180072200110550105000426750
  • Slide 10
  • Recommendation Using Average Due to high ASC, shut down Plant 2 What if we didnt use average? PlantTotal Forecasted Trans. Costs($)Average forecasted Trans. Costs($) Plant 152400032.4 Plant 252585036 Plant 350840035.2 Plant 442675028.6 PlantAverage Shipping Costs($) Plant 132.4 Plant 236 Plant 335.2 Plant 428.6
  • Slide 11
  • Recommendations for Plants Deeper analysis of shutting down plant two Shipping costs at capacity of 5000 PlantProducingShipping toTotal Trans. Costs Plant 15000LA1900 Chicago 3100127500 Plant 35000St Louis 2650 Chicago 250 NY 2100137700 Plant 45000Miami 3750 NY 1250145000 Total shipping cost 410200
  • Slide 12
  • Shut Down Plant 1? Shutting down plant one yields highest shipping costs PlantProducingShipping toTotal Trans. Costs Plant 25000Chicago 3350 NY 1650141500 Plant 35000St. Louis 2650 NY 1700 LA 650152300 Plant 45000Miami 3750 LA 1250152500 Total shipping costs 446300
  • Slide 13
  • Shut Down Plant 3? Shutting down plant three yields $393400 of shipping costs Lower than shutting down plant one PlantProducingShipping toTotal Trans. Costs Plant 15000LA 1900 Miami 1900 NY 1700154300 Plant 25000Chicago 3350 1650 NY141500 Plant 45000St. Louis 2650 Miami 235097600 Total shipping costs 393400
  • Slide 14
  • Shut Down Plant 4? Higher than shutting down plant three Lower than shutting down plant one Shut down plant three not plant two PlantProducingShipping toTotal Trans. Costs Plant 15000LA 1900 Miami 1400 NY 1700154300 Plant 25000Chicago 3350 NY 1650141500 Plant 35000St. Louis 2650 Miami 2350135250 Total shipping costs 431050
  • Slide 15
  • What else should be considered? Relationship between management and employees Business climate Labor and production quality Location of suppliers
  • Slide 16
  • New Consolidated Metropolitan Statistical Area Shipping costs to new area Total Population Cost of living index Average wage/income tax Warehouse prices Climate Demographics
  • Slide 17
  • Impact of New CMSA If new Demand over 18000 open new plant Reallocate supply from plants Recalculate deeper analysis of shipping costs
  • Slide 18
  • Questions? Quiz! What plant should be shut down? Which plant had the lowest average transportation costs? What was a piece of data we could have used?