Page 165 - DMGT523_LOGISTICS_AND_SUPPLY_CHAIN_MANAGEMENT

Logistics and Supply Chain Management

Notes Third, the number of orders is divided into the relevant time period (e.g., fifty-two for weeks or
twelve for months) to express the order quantity in time periods.
To illustrate, let’s work with an EOQ of 300 and a forecast of 2,400. To adjust to a twelve-period
year, the POQ technique would be as follows:
EOQ = 300
Forecast = 2400

Orders per Year = 2400/300
= 8.00
Order Interval = 12/8.00
= 1.5 Months
Under the POQ application, orders are planned approximately every six weeks. The typical
order is 300 units unless usage deviates from planned quantity and requires a “catch-up” or
“light” re supply order.

The main advantage of the POQ approach is that it considers inventory-carrying cost and thereby
minimizes inventory carryover. The disadvantage is that similar to the basic EOQ, POQ also
requires stable demand to realize its full potential.

Time-series Lot Sizing
The fundamental objective of time-series lot sizing is to combine requirements over several
periods to arrive at procurement logic. The time-series approach is dynamic because the order
quantity is adjusted to meet current requirement estimates. This is in contrast to basic EOQ,
which is static in the sense that once the order quantity is computed, it continues unchanged for
the demand-planning horizon.

The key to dynamic lot sizing is that requirements are expressed in varying quantities across
time rather than in usage rates per day or week, as is typical of the basic EOQ. Given substantial
usage fluctuation, fixed order quantities are replaced by a lot sizing system that can calculate an
economical order given changing and intermittent usage. Three such techniques are widely
discussed in the literature and are briefly reviewed here: least unit cost, least total cost, and part
period balancing.

Least Unit Cost

It seeks to identify a combination of requirements over a number of periods resulting in the
lowest cost per SKU. Starting with initial period net requirements, each future period’s per unit
requirements are evaluated to determine a combined quantity for a given number of periods in
which the unit cost is minimized. The least-unit-cost approach essentially evaluates purchasing
requirements in incremental number of weeks of supply into the future.
The first week considers one week of supply. The analysis then considers adding a second week.
Unit cost-including quantity discounts, ordering cost, inventory-carrying cost, and transportation
cost-is evaluated for each option.
While the discount, ordering, and transportation costs will cause average unit cost to decline as
more periods are added, inventory-carrying cost will increase as more time periods are added
because of the additional inventory. Thus, order quantities and order frequency will vary
substantially under the least-unit-cost technique. While this approach does provide a way to
overcome the static features of EOQ and POQ, the technique may cause unit costs to vary widely
between time periods.

160 LOVELY PROFESSIONAL UNIVERSITY