Setting targets
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The document discusses using trend and seasonal forecasting models to set targets and measure performance at Amsterdam Airport Schiphol. It analyzes passenger data from 1992 to 2010 to create a trend forecasting model and seasonal forecasting model using 2008 to 2010 data. The seasonal model forecast for 2011 was compared to the trend model forecast to set a practical target passenger number for 2011.
Setting targets
- 1. Setting Goals And Targets Case Study: Amsterdam- Airport Schiphol By: Mohammed Salem Awad Consultant Yemen 0
- 2. Outline - Introduction - Forecasting –Trend vs Seasonal - Model Fairness. - Case Study - Amsterdam- Airport Schiphol - Input Data - Trend Forecast - period 1992-2010 - Seasonality Model period 2008-2010 – Optimum Solution - Seasonality Model period 2008-2010 – Practical Solution - Summary 2
- 3. Introduction Targets: Most of the companies working on achieving goals, targets, and evaluate their achievements by comparing the current achieved results to results of previous week, month, or year i.e looking backward to analysis current situation. 2
- 4. Introduction But for setting targets we have to look forward, forecast, develop a plan for current situation, to achieved these targets in future in most efficient way, so we can compare the current achievement by the target one, here we can measure our performance & KPI. 3
- 5. Introduction Classical System Planning System Comparing with Past Values Comparing with Planned Targets 4
- 6. Forecasting –Trend vs Seasonal Trend Forecasting Tell us in which direction (Growth) of the historical data, and usually is a long term forecast. Seasonal Forecasting Tell us the Seasonal, Cyclic shocks, we used it to define the forecasting Pattern Trend vs Seasonal Forecasting Forecasted Year of TREND = Sum of 12 forecasted Seasonal Months for same year, 5
- 7. Model Fairness Two Main factors: Evaluation Forecasting R2 = Coef. Of Determination T. S. = Tracking Signal 6
- 8. Model Fairness Two Main factors: R2 > 80% AND -4 < T.S.< 4 R2 = Coef. Of Determination T. S. = Tracking Signal 7
- 9. Case Study Amsterdam - Airport Schiphol 8
- 10. Amsterdam- Airport Schiphol Input Data: 1992 - 2011 ( October) 9
- 11. Amsterdam- Airport Schiphol Input Data – Passengers Total – Column 6 in slide no. 9 Trend Analysis y = 1E+07Ln(x) + 1E+07 R2 = 0.9319 Result: Forecast (2011) = 46,801,687 Pax 10
- 12. Amsterdam- Airport Schiphol Input Data – Trend Analysis 11
- 13. Amsterdam- Airport Schiphol Results: R2 = 0.9319 Forecast (2011) = 46,801,687 Pax 12
- 14. Amsterdam- Airport Schiphol Input Data – Seasonal Model 2008, 2009, 2010 13
- 15. Amsterdam- Airport Schiphol 1- Optimum. Solution Seasonal Model (Pax2010 > Pax2011 Forecast) i.e 45,136,967 > 41,626,027 is not Practical) 14
- 16. Amsterdam- Airport Schiphol 2- Practical Case – Seasonal Model 2011(Forecast) = 46,801,687 Pax 15
- 17. Amsterdam- Airport Schiphol 2- Practical Case – Seasonal Model 2011(Forecast) = 46,801,687 Pax n12 i 1 Monthi 46,801,687 Pax 2011 Forecast 46,801,687 16
- 18. Amsterdam- Airport Schiphol 17
- 19. Amsterdam- Airport Schiphol Comparison of Results 18
- 20. Summary Most of the companies practice the classical methods, they evaluate their current performance based on the past results, they just only looking to the back only for one Year ( or same period as month). While this study explore the effect of historical data in terms of trends forecast, in which direction the company business moves, and the second part is addressing the short term impacts of seasonality (here months) based on three (3) years monthly data base, keeping in minds the model fairness constrains i.e (R 2) and (T.S.) to minimise the forecasting errors, then compare the forecasted/planned figures by the actual one. The new constrain for this model is to match the accumulated forecasted months by (Seasonal Model – 3 years data base) with the proposed forecasted year of Trend analysis (Trend Model – 19 years data base). Results: By Planning method the accuracy is high in terms of Standard Deviation i.e 0.037 and Classical method is 0.092. 19
- 21. Set Your Targets ( 1 ) 20
- 22. Set Your Targets ( 2 ) 21
- 23. Contact Further Information: Mohammed Salem Awad www.slideshare.net/wings_of_wisdom/ Tel: 00967 736255814 www.freewebs.com/wingsofwisdom/ Email: smartdecision2002@yahoo.com www.freewebs.com/art-of-knowledge/ 22