The history of retail forecasting
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From the beginning of retail forecasting to today, explore the technology as it evolves through retail history.
![In the early days… Highly skilled mathematicians created complex models for different forecasting problems Most were based around time series forecasting Models: Box-Jenkins, Holt-Winters, Croston Algorithms could help develop: ,[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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The history of retail forecasting
- 1. The history of retail forecasting… 1 Entire contents © 2008, Quantum Retail Technology, Inc.
- 6. Used “profiles” to govern forecasts
- 7. Good for predictable environments:
- 9. Profiles difficult to get right
- 11. The 80s: Retail technology became faster… New models started to go outside of time series forecasting Retailers built automation components around INFOREM More robust tools became available: E3: The next generation of INFOREM was released SAS: Enterprise time series (ETS) Retailers still working with hierarchy levels, product groups and averaging
- 12. Automation made forecasting easier, and it was good.
- 14. Bench-marking became common
- 15. Pick best / best fit
- 16. Retek: RDF, SAS: HPF, Teradata/Sterling
- 17. Automation and optimization components were enhanced
- 19. Retailers were:
- 20. Constantly redoing seasonal profiles
- 21. Manually managing lead times
- 22. Cheating by manually imputing parameters
- 23. And it still took a lot of computing power to:
- 27. Profiles miss changing behavior
- 28. Aggregating data
- 29. Very expensive
- 30. Not learning from mistakes
- 33. Manage slow selling inventory
- 34. Maximize your profitability
- 36. Forecast accurately without the manual work
- 38. Yay! Yay! Yay!
- 39. Q, the solution for your happily ever after.
- 40. Q, the solution for your happily ever after.