Measuring schedule variability A problem that is all too familiar to suppliers in the automotive…

Measuring schedule variability

A problem that is all too familiar to
suppliers in the automotive industry is that of schedule variability. A vehicle
assembler issues delivery schedules to specify how many parts_of_
each_ type_ are_ required_ each_day_for_
the_following_month._And_ each_day_ a_
call-off_quantity_is_issued,_which_specifies_how_many_the_vehicle_assembler_actually_
wants. The two sets of figures are not necessarily the same, although usually
they add up_ to_ the_same_cumulative_numbers_for_
the_month_as_a_whole._In_other_words,_
the_ total_scheduled_quantities_and_the

Measuring schedule variability

A problem that is all too familiar to
suppliers in the automotive industry is that of schedule variability. A vehicle
assembler issues delivery schedules to specify how many parts_of_
each_ type_ are_ required_ each_day_for_
the_following_month._And_ each_day_ a_
call-off_quantity_is_issued,_which_specifies_how_many_the_vehicle_assembler_actually_
wants. The two sets of figures are not necessarily the same, although usually
they add up_ to_ the_same_cumulative_numbers_for_
the_month_as_a_whole._In_other_words,_
the_ total_scheduled_quantities_and_the_total_call-off_quantities_are_the_same._So_what_is_the_
problem? The_problem_is_that_the_supplier_has_to_cope_with_the_variability_of_call-off_quantities_that_
create_huge_problems_for_the_suppliers_process._Let_S_=_Scheduled_demand,_and_A_=
Actual call-off_quantity._Then_the_difference_D_between_schedule_and_actual_is_given_by_D_=_S_
A. If_the_supplier_produces_to_schedule,_there_are_two_possible_scenarios_that_follow:

_ S_ A, so the supplier
will over-produce the part and end up with excess stock; or

_ S__A_and_S_< a)="" therefore="" have="" different="" logistics="" implications.="" figure="" 1.8="" shows="" that="" actual="" demand,="" totalled="" across="" four="" different="" parts="" at="" pressco="" (a_supplier_of_pressed_metal_components),_may_be_up_to_1,600_units_above_schedule,_="" or="" 2,200="" below="" schedule="" when="" supplying="" the="" vehicle="" assembler="" westco.="" this="" range="" has="" been_divided_up_into_intervals_of_100_units._the_mode_(099)_indicates_that_s_="A" for="" a="" Assuming_that_the_distribution_is_roughly_normal,_the_standard_deviation_(SD)_is_573,_ which is characteristic of the flat, wide spread of data. Figure 1.9 shows the distribution of_S__A_for_four_similar_parts_from_the_same_supplier,_PressCo,_but_for_a_different_vehicle_ assembler,_EastCo._This_time,_the_SD_for_the_distribution_is_95,_representing_a_much_narrower spread of differences than for the assembler, WestCo. Questions 1 What are the logistics implications for PressCo to ensure high delivery reliability to customers_WestCo_and_EastCo? 2 What steps will the supplier need to take in order to satisfy call-off orders from WestCo? 3 If_separate_parts_of_the_PressCo_factory_were_dedicated_to_production_for_WestCo_and_ for_EastCo,_which_would_be_the_more_efficient_in_terms_of_labour_costs_and_inventory_ holding?