Page 309 - DMGT523_LOGISTICS_AND_SUPPLY_CHAIN_MANAGEMENT

Logistics and Supply Chain Management

Notes examples of software applications exist that utilize analytic techniques to determine optimum
inventory management parameters.
The advantage of analytic inventory techniques is the ability to directly determine optimum
inventory parameters given certain assumptions regarding operating environment. On the
other hand, analytic inventory techniques are limited in terms of accuracy when assumptions
are not met.

Example: Since most analytic inventory techniques assume normally distributed demand
and performance cycles, the techniques lose accuracy when the shape of actual demand or
performance cycles deviates from the normality assumption.
Nevertheless, analytical inventory techniques are often a good place to start when attempting to
determine optimum inventory parameters.

Simulation Inventory Techniques

The inventory simulation approach creates a mathematical and probabilistic model of the
logistics operating environment as it actually exists. The simulation approach is similar to
creating a laboratory testing environment for the logistics network and operating policies.
Simulation is similar to the analytic approach except the roles of the inventory parameters and
service levels are reversed.

In simulation, inventory parameters such as the order quantities and the reorder points that are
to be tested become the simulation inputs. These inputs define the environment to be tested. The
major simulation outputs are the service level and inventory performance characteristics of the
testing environment. The simulation, in effect, evaluates the performance of a specific situation.
If the reported performance does not achieve desired objectives, the inventory parameters must
be changed and a new environment is simulated.

!

Caution It is sometimes necessary to complete a number of simulations to identify the
combination of inventory parameters that yields optimum performance.
The major benefit of inventory simulation techniques is the ability to model a wide range of
logistics environments without requiring simplifying assumptions. It is possible to accurately
simulate virtually any logistics environment by incorporating characteristics and operating
policies. The major shortfall of simulation techniques is their limited ability to search for and
identify optimum solutions. While there are inventory simulation examples that incorporate
search algorithms, they are limited in capability and scope. There are indications that simulation
is becoming more popular as firms attempt to understand inventory dynamics in the logistics
channel.
Inventory decision support applications are increasing in importance because of the emphasis
on streamlining inventory levels to reduce the logistics asset base. The demand for more refined
inventory parameters has increased the need for more sophisticated inventory analysis
techniques. Software firms have responded by developing both stand-alone and integrated
applications.

13.2.6 Transportation Decisions

Transportation analyses focus on routing and scheduling of transportation equipment to optimize
vehicle and driver utilization while meeting customer service requirements. Transportation

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