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Generate Inventory Analysis using Consumption and Stock on hand data to determine Inventory Turnover and Coefficient of Variance of Consumption.

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##Inventory Analysis Tool

Instructions

Detailed usage instructions can be found in the User Guide

Background

The Inventory Analysis Tool is designed to examine supply chain patterns over time and flag priority facilties and products for action. Two metrics, inventory turnover and the Coefficient of Variance for the consumption are calculated and used together to categories facilities/products into risk categories.

Method

Both metrics are calculated on a rolling basis over a given period of months (typically 12 months) for a given facility/product combination

Inventory Turn Rate

Inventory Turn Rate = sum(consumption) / avg(stock on hand) Unit - times stock turned over per period (typically 12 months)

COV Consumption

CoV Consumption = std(consumption) / avg(consumption) Interpretation - the lower the COV the less variability there is. < .7 is low, > 1.5 is high

Tool overview

The tool has been designed to work on any country's data that meets certain data requirements. The user inputs dataset-specific information which map to required arguments for the tool

Data requirements

Excel or csv data containing product, facility, consumption, stock on hand, date

Input - excel or csv User interface - python gui using pysimplegui Analysis - python script Ouput - txt tables Visualization - excel dashboard, csv output connected via Power Query

To run

Unzip LMIS_Anaysis_report.zip (this contains the excel dashboard - too large to upload on Github)

pip install requirements.txt

python inventory_analysis.gui

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Generate Inventory Analysis using Consumption and Stock on hand data to determine Inventory Turnover and Coefficient of Variance of Consumption.

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