Chapt 16 case forecasting sales

Chapt 16 case forecasting sales - T t = 169.499 1.02 t 3...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
Chapter 16 Chapter 16 Forecasting Case Problem 1: Forecasting Sales 1. Graph of the time series: 2. Analysis of seasonality: Month Seasonal-Irregular Component Values Seasonal Index January 1.445 1.441 1.44 February 1.301 1.297 1.30 March 1.344 1.343 1.34 April 1.047 1.034 1.04 May 1.044 1.054 1.05 June .779 .801 .80 July .882 .834 .83 August .857 .848 .85 September .618 .638 .63 October .725 .675 .70 November .843 .862 .85 December 1.137 1.180 1.16 CP - 74 - * SALES - - * * - * * 240+ * * * * - * * - * - * * - ** 180+ ** * - * * * - * * * * * - ** * * - * * * 120+ * - * - +---------+---------+---------+---------+---------+----MONTH 0.0 7.0 14.0 21.0 28.0 35.0
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Chapter 16 The deseasonalized time series is shown below: t Deseasonalized Sales t Deseasonalized Sales 1 168.06 19 189.16 2 180.77 20 189.41 3 173.13 21 193.65 4 171.15 22 185.71 5 175.24 23 196.47 6 175.00 24 198.28 7 174.70 25 195.83 8 178.82 26 196.15 9 174.60 27 197.76 10 185.71 28 197.12 11 178.82 29 200.00 12 177.59 30 200.00 13 182.64 31 200.00 14 183.08 32 204.71 15 184.33 33 200.00 16 185.58 34 211.43 17 183.81 35 203.53 18 186.25 36 202.59 The trend line fitted to the deseasonalized time series is
Background image of page 2
Background image of page 3
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: T t = 169.499 + 1.02 t 3. Sales forecasts Forecast for Year 4 Using T t = 169.499 + 1.02 t Month Trend Forecast Seasonal Index Monthly Forecast January 207.239 1.44 298.424 February 208.259 1.30 270.737 March 209.279 1.34 280.434 April 210.299 1.04 218.711 May 211.319 1.05 221.885 June 212.339 .80 169.871 July 213.359 .83 177.088 August 214.379 .85 182.222 September 215.399 .63 135.701 October 216.419 .70 151.493 November 217.439 .85 184.823 December 218.459 1.16 253.194 4. Forecast error = $295,000 - $298,424 = -$3,424 The forecast we developed over predicted by $3,424; this represents a very small error. 5. The analysis can be easily updated each month, especially if a computer software package is used to perform the analysis. CP - 75 Solutions to Case Problems CP - 76...
View Full Document

{[ snackBarMessage ]}

Page1 / 3

Chapt 16 case forecasting sales - T t = 169.499 1.02 t 3...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online