Setting Targets

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This analysis, decribe a new method to set targets, by using two forecasting models, the first model is trend, while the second is seasanlity model

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Setting Targets

  1. 1. Setting Goals And TargetsCase Study:Amsterdam- AirportSchipholBy: Mohammed Salem AwadConsultantYemen 0
  2. 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 1
  3. 3. IntroductionTargets:Most of the companies workingon achieving goals, targets, andevaluate their achievements bycomparing the current achievedresults to results of previousweek, month, or year i.e lookingbackward to analysis currentsituation. 2
  4. 4. IntroductionBut for setting targets we haveto look forward, forecast,develop a plan for currentsituation, to achieved thesetargets in future in most efficientway, so we can compare thecurrent achievement by thetarget one, here we can measureour performance & KPI. 3
  5. 5. IntroductionClassical System Planning SystemComparing with Past Values Comparing with Planned Targets 4
  6. 6. Forecasting –Trend vs SeasonalTrend ForecastingTell us in which direction (Growth) ofthe historical data, and usually is along term forecast.Seasonal ForecastingTell us the Seasonal, Cyclic shocks,we used it to define the forecastingPatternTrend vs Seasonal ForecastingForecasted Year of TREND= Sum of 12 forecasted SeasonalMonths for same year, 5
  7. 7. Model Fairness Two Main factors: Evaluation Forecasting R2 = Coef. Of Determination T. S. = Tracking Signal 6
  8. 8. Model Fairness Two Main factors: R2 > 80% AND -4 < T.S.< 4 R2 = Coef. Of Determination T. S. = Tracking Signal 7
  9. 9. Case StudyAmsterdam - Airport Schiphol 8
  10. 10. Amsterdam- Airport SchipholInput Data: 1992 - 2011 ( October) 9
  11. 11. Amsterdam- Airport SchipholInput Data –Passengers Total –Column 6 in slide no. 9Trend Analysisy = 1E+07Ln(x) + 1E+07R2 = 0.9319Result:Forecast (2011) = 46,801,687 Pax 10
  12. 12. Amsterdam- Airport SchipholInput Data – Trend Analysis 11
  13. 13. Amsterdam- Airport SchipholResults:R2 = 0.9319Forecast (2011)= 46,801,687 Pax 12
  14. 14. Amsterdam- Airport SchipholInput Data –Seasonal Model2008,2009,2010 13
  15. 15. Amsterdam- Airport Schiphol1- Optimum. Solution Seasonal Model (Pax2010 > Pax2011 Forecast)i.e 45,136,967 > 41,626,027 is not Practical) 14
  16. 16. Amsterdam- Airport Schiphol2- Practical Case – Seasonal Model 2011(Forecast) = 46,801,687 Pax 15
  17. 17. Amsterdam- Airport Schiphol2- Practical Case – Seasonal Model 2011(Forecast) = 46,801,687 Pax  n12    i 1 Monthi  46,801,687 Pax   2011 Forecast   46,801,687 16
  18. 18. Amsterdam- Airport Schiphol 17
  19. 19. Amsterdam- Airport Schiphol Comparison of Results 18
  20. 20. Summary Most of the companies practice the classical methods, theyevaluate their current performance based on the past results, theyjust only looking to the back only for one Year ( or same period asmonth). While this study explore the effect of historical data interms of trends forecast, in which direction the company businessmoves, and the second part is addressing the short term impacts ofseasonality (here months) based on three (3) years monthly database, keeping in mind the model fairness constrains i.e (R 2) and(T.S.) to minimise the forecasting errors, then compare theforecasted/planned figures by the actual one. The new constrain for this model is to match the accumulated forecastedmonths by (Seasonal Model – 3 year data base) with the proposed forecasted year ofTrend analysis (Trend Model – 19 years data base).Results:By Planning method the accuracy is high in terms of Standard Deviation i.e 0.037and Classical method is 0.092. 19
  21. 21. Forecasting 20
  22. 22. Forecasting 21
  23. 23. ContactFurther Information:Mohammed Salem Awad www.freewebs.com/wingsofwisdom/Tel: 00967 736255814 www.freewebs.com/art-of-knowledge/Email: smartdecision2002@yahoo.com www.standout-from-the-crowds.webs.com 22

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