How to avoid being fooled by percent changes
•Als PPTX, PDF herunterladen•
1 gefällt mir•1,025 views
A fictional tractor building company looks to understand why sales have decreased in the past year. Comparing the performance of two sales guys based on control charts yields very different results than a traditional "year-over-year" percent change analysis.
Empfohlen
Empfohlen
Weitere ähnliche Inhalte
Mehr von Ben Jones
Mehr von Ben Jones (20)
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
How to avoid being fooled by percent changes
- 1. What the board room can learn from the shop floor or, how to avoid being fooled by percent changes By Ben Jones http://dataremixed.com
- 2. Meet Jim
- 4. Jim runs a company selling…tractors.
- 5. Tractor Sales are down 3.6% this year -3.6%
- 7. Meet Jim’s two sales guys, Joe and Larry Joe Larry
- 8. Larry’s numbers are up 2.9%… +2.9% Larry
- 9. Joe’s numbers are…not. -8.3% Joe
- 10. What should Jim do?
- 11. (Jim is polishing up his resume…)
- 12. but what if it was all just a big misunderstanding?
- 13. Instead of just looking at % change “Year Over Year”… -3.6%
- 14. …what if we plotted units sold by month?
- 15. and what if we applied some brand new techniques? Walter Shewhart written in 1939 http://amzn.to/dOWKBw
- 16. to understand the variation in the data: “Special Cause” variation UCL – Upper Control Limit “Common Cause” variation x-bar (or average) LCL – Lower Control Limit “Special Cause” variation
- 17. So wait, only LAST month is a “down” month…
- 18. …and WHO do you think caused THAT? Joe Larry
- 19. Probably Joe, right? -8.3% Joe
- 20. But if we look at Joe’s numbers over time… 2009: 96 Units -8.3%
- 21. But if we look at Joe’s numbers over time… 2010: 88 Units -8.3%
- 22. We see no statistically significant change! “Common Cause” variation Joe
- 23. But Larry can’t be the reason, his numbers are up, right? +2.9% Larry
- 24. Let’s look at Larry’s numbers over time… 2009: 69 Units
- 25. Let’s look at Larry’s numbers over time… 2010: 71 Units
- 26. Looks like Larry has some explaining to do about December… “Special Cause” variation Larry
- 27. These two approaches tell two very different stories… Percent Change Control “YOY” Charts
- 28. Blaming Joe would be mistaking NOISE for a SIGNAL
- 29. Rewarding Larry would be missing the opportunity to identify a SIGNAL
- 30. Either way, Jim’s business loses an opportunity to LEARN and GROW…
- 31. …and the fate of our sales guys’ careers hangs in the balance… Joe Larry
- 32. The Morals of the Story: • DON’T just compare % change • DON’T assume a % change is statistically significant just because you don’t like it. • DO use a Control Chart to filter out noise in a data set and identify signals • NEVER adjust the y-axis to cross the x-axis at anything other than 0 (did you catch that trick? The column charts grossly over-exagerate the changes)
- 33. For bar charts, always set the y-axis to 0 y-axis starts at 157 y-axis starts at 0 Appears to be 4X less
- 34. Got all that, Jim?
- 35. More about Control Charts (in business) • Understanding Variation – Donald J. Wheeler Presentation by Ben Jones http://dataremixed.com