A Root Cause Analysis of Stock-outs in the Pharmaceutical Industry Benny Sun Bangqi Yin May 22, 2014

Agenda Background Research Area Methodology Data Analysis and Results Recommendations Q&A

Source: SSP Stockouts National Survey, Nov 2013 Background 2.4M people on HIV treatment 21.4% facilities reported stock-out 30 Days average length of stock-out Source: SSP Stockouts National Survey, Nov 2013

Research Area Problem Identification: 16,000+ stock-out incidents within 6 months Manufacturing quality issue was suspected as a major root cause Research focus area: Test the hypothesis of manufacturing quality issue Diagnose root causes of stock-outs Identify possible solutions

Definition of Stock-out Eh… we only have 50 packs… I need 100 packs… Primary Manufactory Secondary Manufactory Distribution Center First-Point Customers Stock-outs

Sample of Dataset

Limitation of Data Vague default stock-out categories Stock-out category not matched with comments Blank comments

Methodology – Manual Coding

New Defined Stock-out Cause Categories

Methodology – RCA Matrix High Frequency Frequency  the total number of each cause reported Predictability  Odds Ratio of new defined cause categories Explain: Any incident includes cause and outcome; cause can be measured by Predictability and Frequency How to quantify the influence of cause on outcome?  RCA Matrix Low Low High Predictability Image Source: edp24.co.uk, blog.kerrygaynormethod.com

Methodology – Odds Ratio Odds of a female being successful: 200/100 = 2 Odds of a male being successful: 50/150 = 0.33 Odds Ratio: 2/0.33 = 6 (Females were six times more likely than males to succeed in the program) Mention that Odds Ratio was generated by Logistic Regression

Distribution of Odds Ratio and Frequency

Results High Frequency Lack of regulatory approval to release product Interface / Data Error Lack of regulatory approval to release product Forecast Error Transportation/Distribution Issues Manufacturing Quality Issues Low Product Changes Customs Clearance Issues Warehouse Quality Issues Low High Predictability

Recommendations Further research on Regulatory Issues Employee Training Improvement on stock-out management system

Questions?

Quantitative Root Cause Assessment Map

Sample of Regulatory Issues

Logistic Regression

Logistic Regression