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

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

3. 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

4. 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

5. 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

6. Sample of Dataset

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

8. Methodology – Manual Coding

9. New Defined Stock-out Cause Categories

10. 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

11. 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

12. Distribution of Odds Ratio and Frequency

13. 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

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

15. Questions?

16. Quantitative Root Cause Assessment Map

17. Sample of Regulatory Issues

18. Logistic Regression

19. Logistic Regression