Northcutt Bikes Case Answers

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Presentation transcript:

Northcutt Bikes Case Answers

Q1: Demand Data Plot

Q1: Plot Shows There is seasonality There is a trend Forecast should take into account both

Construction of base indices Year: 2008 2009 2010 2011 Mean Base January 0.53 0.72 0.59 0.61 February 0.74 0.95 1.09 0.88 March 0.84 0.79 0.98 0.87 April 1.00 1.18 0.92 1.05 May 1.10 1.16 1.15 1.27 1.17 June 1.60 1.57 1.39 1.51 1.52 July 1.29 0.94 1.35 1.56 1.28 August 1.19 1.30 1.43 0.71 September 1.13 0.91 1.08 1.03 October 0.96 0.77 0.89 November 0.73 0.99 0.78 December 0.51 0.67 0.70 Mean Demand: 818.42 990.50 1032.08 1181.25

Multiple Regression Results: X is Period and Base Regression Statistics Multiple R 0.982917071 R Square 0.966125969 Adjusted R Square 0.964620456 Standard Error 59.82147676 Observations 48 ANOVA df SS MS F Regression 2 4592970.404 2296485.202 641.7256395 Residual 45 161037.4087 3578.609082 Total 47 4754007.813 Coefficients t Stat P-value Intercept -219.4209094 35.31667659 -6.212954633 1.50687E-07 Period 8.730540524 0.623285303 14.00729407 5.12015E-18 Base 1011.295853 30.74315604 32.89499139 4.07081E-33

Q2: Forecasting Methods Multiple regression or MR (Y is forecast, X’s are period and base) MAD ≈ 45.096 Simple regression or SR (deseasonalize demand, seasonalize forecast, X is period) MAD ≈ 32.403 Exponential Smoothing or ES (adjusted for trend and seasonality) MAD ≈ 13.258

Q2: Forecast for January – April 2012 Month Mean Base Period MR SR ES January 0.61 49 825.27 745.12 720.56 February 0.88 50 1107.05 1082.68 1039.50 March 0.87 51 1105.66 1078.04 1027.69 April 1.05 52 1296.43 1310.32 1240.31

Q3: Best Forecast: Exponential smoothing forecast has lowest MAD Disadvantages: the exponential smoothing forecast should be updated frequently (say once a month).

Q4: Additional Information Jan’s knowledge of market could be used to: - Add additional independent variable to multiple regression - Be used to adjust other forecasts (caution should be used, however) Monthly increments best as forecast can react to latest information, provided this is not costly

Q5: Ways to Improve Operations Quicker response: reduce manufacturing lead times; possibly implement online ordering Suppliers: reduce lead times; set contracts Improve information systems Work force: increase flexibility; temps

Q6: Recommendations Operation is likely not too large - Jan can control operation effectively if she: delegates improves information system reduces lead times implements lean (to be discussed) uses different modes of operation for different style bikes Information needed on costs of above

Questions ? ???