[1] It has been observed within operations research that "every company has the challenge of matching its supply volume to customer demand.
"[2] In contrast to the traditional "binge and purge" inventory cycle in which companies over-purchase product to prepare for possible demand spikes and then discard extra product, inventory optimization seeks to more efficiently match supply to expected customer demand.
[3] American Productivity and Quality Center (APQC) Open Standards data shows that the median company carries an inventory of 10.6 percent of annual revenues as of 2011[update].
[5] When Wall Street analysts look at a company's performance to make earnings forecasts and buy and sell recommendations, inventory is always one of the top factors they consider.
[8] At the same time, planning frequencies and time-buckets are moving from monthly/weekly to daily and the number of managed stocking locations from dozens in distribution centers to hundreds or thousands at the points of sale (POS).
[13] Stochastic optimization also accounts for demand volatility which is a top priority among the challenges faced by supply chain professionals.
[16] A sequential single-echelon approach forecasts demand and determines required inventory for each echelon separately.
It should be clear that the amount of stock needed at the outlets is a function of the service received from the distribution center.
They note growing interest in their use and application in specific inventory fields, such as plant operations, assembly lines, and within transportation.