What's New Table of Contents |
What's New in SAS Inventory Optimization 1.3
Overview
The SAS Inventory Replenishment Planning product has a new name, SAS Inventory Optimization. SAS Inventory Optimization also has a new version numbering scheme. SAS Inventory Optimization 1.3 provides more features and greater functionality than SAS Inventory Replenishment Planning 1.2 and SAS 9.1.2 Inventory Replenishment Planning.
SAS Inventory Optimization enables you to calculate periodic-review
inventory replenishment policies using information about
demand, lead time, costs, and desired service measures.
SAS Inventory Replenishment Planning 9.1.2 included the experimental MIRP procedure for calculating inventory control parameters in multiechelon supply chains. The MIRP procedure is designed to help users better understand how network topologies, cost structures, and service level requirements, among other factors, impact the inventory investment and allocation across a supply chain.
SAS Inventory Replenishment Planning 1.2 included
- new options for the IRP procedure to give the user more control over calculating policies
- improvements in the IRP algorithms
- production-level MIRP procedure, which replaces the experimental MIRP procedure
- the new SAS Inventory Policy Studio solution, which provides a user-friendly interface to the IRP procedure
SAS Inventory Optimization 1.3 includes
- new features in the MIRP procedure
- the production-level version of SAS Inventory Policy Studio, which provides a user-friendly interface to the IRP procedure
PROC IRP
PROC IRP can calculate four types of replenishment policies. These policies are determined through a number of algorithms that are controlled by user-specified options. PROC IRP can accommodate both single-location and two-echelon distribution inventory systems.
The input data set to PROC IRP specifies information about lead time, demand, and costs, as well as options to control the policy. The output data set produced by PROC IRP gives the policy parameters for each item. In addition, estimates of measures such as fill rate, ready rate, and average inventory, among others, are included in the output data set.
With SAS Inventory Replenishment Planning 1.2 and SAS Inventory Optimization 1.3, PROC IRP includes new and improved algorithms. In addition, new options give the user more control over optimization of policies:
- ALGORITHM= option
- QGRID= option
- DIST= option
PROC MIRP
SAS Inventory Replenishment Planning 1.2 and higher includes the production-level MIRP procedure. PROC MIRP can calculate inventory control parameters for all stock-keeping locations in general supply chain networks, which may consist of any combination of serial, assembly, and distribution subnetworks. These parameters ensure that service requirements are satisfied at minimum inventory cost for every supply chain. PROC MIRP gives users flexibility in modeling their supply chain networks. These functionalities include:
- two replenishment policies: base-stock policy and min-max policy
- four service-level measures: ready rate, fill rate, backorder ratio, and waiting time probability
- order constraints: minimum size, maximum size, and fixed lot size
- multiple-period replenishment planning
- backlog and lost sales options
- intermittent demand
The input data sets to PROC MIRP specify information about lead times, holding costs, service levels, and demand of stock-keeping location in the networks, as well as information about the structure of the networks. The output data set produced by PROC MIRP gives the inventory control parameters, along with estimates of measures such as order quantities, backlogs, and service levels, for each stock-keeping location and each period in a planning horizon. PROC MIRP can also be used to evaluate the performance of users' own inventory policies.
In SAS Inventory Optimization 1.3, PROC MIRP includes support for random lead time. This new functionality enables users to capture uncertainties in lead times between locations within a supply chain network, and from external suppliers to any locations in the network. Users specify the minimum, average, and maximum values for lead times. PROC MIRP uses these values in a triangular distribution to model the lead time uncertainty.
SAS Inventory Policy Studio
SAS Inventory Optimization 1.2 included a preproduction version of SAS Inventory Policy Studio. SAS Inventory Optimization 1.3 includes production-level SAS Inventory Policy Studio, a graphical user interface designed to support the use of PROC IRP for users new to SAS or unfamiliar with the SAS language. In addition to supporting the optimization of inventory policies, Inventory Policy Studio
- facilitates the creation and management of projects, enabling users to plan inventory policies for specific categories of products
- enables users to create "what if" scenarios using different parameters or forecasts, and determine the impact on policies, customer service levels, and costs
- provides a graphical sensitivity analysis to assist users in quickly gauging the impact that changes in specific parameters will have on policies, customer service levels, and costs
- provides reporting capabilities
- provides the SAS Inventory Optimization Script Runner, which enables users to write and run or schedule batch scripts for certain SAS Inventory Policy Studio tasks
After creating scenarios, and calculating, evaluating, and promoting policies, the user can export the project table for use in other operational systems.
SAS Inventory Policy Studio does not support all of the capabilities of PROC IRP. For example, SAS Inventory Policy Studio
- does not support the use of backorder penalty costs as input to policy calculations
- does not support policy calculation for two-echelon systems
For information about SAS Inventory Policy Studio, see the SAS Inventory Optimization 1.3: Inventory Policy Studio User's Guide
.