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UID:af23d6bd1dab86257085fc065dc0d9af
DTSTAMP:20241104T222838Z
SUMMARY:Kandrika Pritularga\, PhD\, University of Lancaster\, United Kingdo
 m 
DESCRIPTION: \n\nTITLE: Forecast congruence: a quantity to align forecasts 
 and\ninventory decisions\n\nABSTRACT: Forecasting is a step undertaken in 
 many business decisions.\nFor instance\, in inventory management\, demand 
 forecasts are the\ncornerstone of inventory decisions\, namely how much an
 d when to order.\nIt is widely recognised that accurate demand forecasts l
 ead to\neffective and efficient inventory decisions. However\, in practice
  the\nforecasts are produced in isolation\, ie\, the models are selected a
 nd\nevaluated on accuracy metrics that do not account for important\naspec
 ts of inventory management. Even though there are good reasons in\nsupport
  of this practice\, for the alternative approach\, to help\nmanagers calib
 rate their forecasting process from a decision\nstandpoint\, we lack appro
 priate measures of forecast quality. We\naddress this limitation by introd
 ucing the quantity of forecast\ncongruence\, which measures thejitteriness
 ’ of forecasts over the\ndecision period. We investigate its characteris
 tics and connection to\naccuracy and demonstrate with simulations and a re
 al case on an FMCG\nmanufacturer that congruence is connected with the vol
 atility of\ninventory decisions. We show that accounting for congruence in
 \nforecast design and selection can achieve favourable inventory\nperforma
 nce\, without necessitating evaluations that rely on complex\ninventory si
 mulations. We conclude by discussing its connection with\nestimation uncer
 tainty and the bullwhip effect.\n 
DTSTART:20241206T160000Z
DTEND:20241206T170000Z
LOCATION:https://drexel.zoom.us/j/89275577804
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