Knowledge Base for Supply App

Simulation parameters: Details & good practices

Table of contents


This article provides more details regarding simulation parameters as well as good practices on how to use them.

Number of simulations for patient treatment

Number of simulations for patient treatment

This is the number of simulations that are run on the recruitment and demand parameters. This will notably simulate the buffer levels at sites (only if they are not fixed) and will recommend you the most appropriate levels based on the worst case scenario (see “Safety Stock Confidence Level” below for more details) observed.

Number of simulations for supply and risk management

These simulations are again run on the recruitment/demand parameters, as well as on the supply parameters (productions and shipments), to estimate the risk associated between both. This will notably simulate the buffer levels at depots and will recommend you the most appropriate levels based on the worst case scenario (see “Safety Stock Confidence Level” below for more details) observed.

Prediction window multipliers (PWM) at sites

This parameter decides upon your prediction length at site level. Within your IRT setup, you defined a prediction window at sites (Resupply management tab) that will be multiplied by the number you enter as PWM. For example, if you entered 7 as the number of days for your prediction window at sites and you choose a PWM of 2, the simulations will be run with 14 days (7×2) of prediction window at sites.

You can run simulations with multiple PWMs at sites by clicking on Add new (see screenshot below).

run simulations with multiple PWMs at sites

Prediction window multipliers (PWM) at depot

This parameter works the same as the PWM at sites. It multiplies your prediction window at depots by the number you entered as PWM.

Safety Stock Confidence Level

The level of risk covered by the minimum buffer levels, called the safety stock confidence level (SSCL). This parameter is a percentage : 0% meaning that no worst case scenario is covered and 100%* that you cover all worst case scenarios.

Example : Let’s take a simple example where we have 100 simulations for “patient treatment” and 200 simulations for “supply and risk management” and we choose a 95% SSCL.

The buffer levels at sites (“patient treatment” simulations) will be computed on : 100 simulations – 5 (5% worst cases) = 95 simulations.

The buffer levels at depots (“supply and risk management” simulations) will be computed on : 200 simulations – 10 (5% worst cases) = 190 simulations.

However, the risk will be estimated for the 200 “supply and risk management” simulations using all buffer levels defined above (i.e. sites and depots). Therefore, there is no removed worst cases when the risk is estimated. This allows to quantify how buffer levels are covering (or not) the variability observed during simulations.