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					Demand Management
    Dr. Ron Lembke
        SCM 461
Role of Demand Management
   Collect information from all demand
    sources
       Customers
       Spare parts
 Negotiate and Confirm shipping dates,
  quantities
 Confirm order status, communicate
  changes
Different Environments
 Factory to customers – plant very aware
  of customer needs
 Factory to DC – stable replenishment plan
 Plan vs. Forecast:
       Forecast is what you think demand will be like
       Plan is how you will respond to demand
       “A manager cannot be held responsible for not getting a
        forecast right.”
       How are you going to respond to changes in demand?
       You have control over the plan and execution, not
        demand
       Rain forecasted? You decide to bring umbrella or not.
       Planning a BBQ: 300 people? 500? Somebody decides
Independent vs. Dependent Demand
   Feeding manufacturing, demand for parts is
    dependent on manufacturing plan
   Sales to customers are independent of our
    (production) activities. # snowboards
       # tops depends on # boards to be made
   Customer order decoupling point: when control of
    timing passes from customer to us
       Make to stock – Finished goods
       Assemble to Order – WIP
       Make to Order – Raw Materials
       Engineer to Order - suppliers
Make to Stock
   Customers buy finished, generic product
       McDonalds’ heat lamp days
 Triggers signal to make more
 Use warehouses, DCs to fulfill demand
 Maybe VMI?
Assemble to Order
   Define customer’s order in terms of alternative
    components and options
       Subway, In-N-Out
   Configuration management: combine options
    properly into a buildable final product
   Flexibility in combining components, options, and
    modules
   Combinations:
   31 ice cream * 4 sauces * 12 sprinkles = 1,488
Homework
 Figure out the total number of
  combinations of some (one) thing you like
  to eat or drink:
 Go there, write up # of options, and spell
  it all out for me, how many there are
       # lattes: soy, decaf, etc.
       Ice cream
       Pizza
       Beer samplers
       Burritos
       Burgers
Make/Engineer to Order
   No stock components to assemble
       Cooking at home – could make any of the
        standard things you usually make: burger,
        pizza, chili, etc., etc.
   Include Engineer to Order
       Tell me what you’d like – wedding dinner
 Significant design element in order
  creation
 Don’t know possibilities of what customers
  might buy
What do you think?
 Which method is best?
 What kinds of uncertainty are involved in
  each?
 What determines customer service in
  each?
 What is the decoupling point in each
  system?
 What kinds of capacity do we need in
  each?
Communication with Depts.
   SOP – give forecasts, get prod. Plans
       Capacity: material (MTS), labor (MTO)
       Timing of deliveries & production
   Master Production Scheduling
       Detailed order info to MPS
       Status of each order
   Figs 2.5, 2.6
                         Sales and
          Resource       Operations        Demand
          Planning       Planning          Management



                       Master Production
                       Scheduling
Information Use
   Make to Knowledge
       Use EDI, POS data to know what your
        customers are going to be ordering
       (Not forecasting)
 Wal-Mart and Philips
 Forecast based on:
       Sales?
       Demand?
       Shipments?
Forecasting Framework
   Fig. 2.7, p. 30
Aggregating Demand
   Long-term, or product-line forecasts more
    accurate than short term or detailed
    forecasts
       Monthly: Avg = 20, std dev =2
            95%: 16-24 which is +/- 20%
       Annual: Avg = 20 * 12 = 240
       Std. Dev = 2 * sqrt(12) = 6.9
            95%: 226-254, which is +/- 5.8%
       Easier to forecast demand for components
        than for sales of particular car configurations.
Aggregating Demand
 Individual item forecasts must add up to
  correct total
 Individual item percentage of total
  probably constant
 Pyramid forecasting – bring things into
  alignment
       Force people to accept higher targets without
        “owning” them
Predicting
Demand
Shared components

     Grand   Grand   Grand
     Prix    Am      Prix
End of Pontiac




   Last American-produced Pontiac G6
    – Nov. 25, 2009
   Canadian market-G3 Wave, GM
    Daewoo, S. Korea, Dec. 2009

				
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posted:6/12/2012
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