Forecasting 4 2014 Pearson Education Inc 2014 Pearson Education Inc 4 1 Learning Objectives When you complete this chapter you should be able to 1 Understand the three time horizons and which models 2 Explain when to use each of the four qualitative apply for each use models 3 Apply the naive moving average exponential smoothing and trend methods 4 Compute three measures of forecast accuracy 5 Develop seasonal indexes 6 Conduct a regression analysis 7 Use a tracking signal 2014 Pearson Education Inc 4 2 What is Forecasting Process of a Underlying basis of all business decisions 2014 Pearson Education Inc 4 3 Forecasting Time Horizons range forecast Up to 1 year generally less than 3 months Purchasing job scheduling workforce levels job assignments production levels range forecast 3 months to 3 years Sales and production planning budgeting range forecast 3 years New product planning facility location research and development 2014 Pearson Education Inc 4 4 Distinguishing Differences Medium long range forecasts deal with more issues and support management decisions regarding planning and products plants and Short term forecasting usually employs different than longer term forecasting Short term forecasts tend to be than longer term forecasts 2014 Pearson Education Inc 4 5 Influence of Product Life Cycle Introduction Growth Maturity Decline and require longer forecasts than maturity and decline As product passes through life cycle forecasts are useful in projecting levels levels Factory 2014 Pearson Education Inc 4 6 Types of Forecasts forecasts Address business cycle inflation rate money supply housing starts etc forecasts Predict rate of technological progress Impacts development of new products forecasts Predict sales of existing products and services 2014 Pearson Education Inc 4 7 Strategic Importance of Forecasting Hiring training laying off workers Capacity shortages can result in undependable delivery loss of customers loss of market share Good supplier relations and price advantages 2014 Pearson Education Inc 4 8 Seven Steps in Forecasting 1 Determine the of the forecast 2 the items to be forecasted forecast 3 Determine the of the 4 Select the forecasting 5 Gather the data 6 Make the forecast 7 and implement results 2014 Pearson Education Inc 4 9 The Realities Forecasts are seldom perfect unpredictable outside factors may impact the forecast Most techniques assume an underlying stability in the system Product family and aggregated forecasts are more accurate than individual product forecasts 2014 Pearson Education Inc 4 10 Forecasting Approaches Methods Used when situation is vague and little data exist New New Involves experience e g forecasting sales on Internet 2014 Pearson Education Inc 4 11 Forecasting Approaches Methods Used when situation is and historical data exist products Current technology Involves techniques e g forecasting sales of color televisions 2014 Pearson Education Inc 4 12 Overview of Qualitative Methods 1 of executive opinion Pool opinions of high level experts sometimes augmented by statistical models 2 method Panel of experts queried iteratively 2014 Pearson Education Inc 4 13 Overview of Qualitative Methods 3 Sales force Estimates from individual salespersons are reviewed for reasonableness then aggregated 4 Consumer Survey Ask the customer 2014 Pearson Education Inc 4 14 Jury of Executive Opinion Involves small group of high level experts and managers Group estimates demand by working together Combines managerial experience with statistical models Relatively quick disadvantage 2014 Pearson Education Inc 4 15 Decision Makers Evaluate responses and make decisions Delphi Method group process continues until consensus is reached 3 types of participants Decision makers Staff Respondents 2014 Pearson Education Inc Staff Administering survey Respondents People who can make valuable judgments 4 16 Sales Force Composite Each salesperson projects his or her sales at district and national levels Sales reps know customers wants Tends to be overly 2014 Pearson Education Inc 4 17 Consumer Market Survey customers about purchasing plans What consumers say and what they actually do are often different Sometimes difficult to answer 2014 Pearson Education Inc 4 18 Overview of Quantitative Approaches 1 Naive approach 2 Moving averages 3 Exponential smoothing 4 Trend projection 5 Linear regression time series models associative model 2014 Pearson Education Inc 4 19 Time Series Forecasting Set of evenly spaced numerical data Obtained by observing response variable at regular time periods Forecast based only on past values no other variables important that factors influencing past and present will influence in future 2014 Pearson Education Inc 4 20 Time Series Components Trend Cyclical Seasonal Random 2014 Pearson Education Inc 4 21 Components of Demand Seasonal peaks i e c v r e s r o t c u d o r p r o f d n a m e D 1 Random variation 2 Time years 3 2014 Pearson Education Inc Trend component Actual demand line Average demand over 4 years 4 Figure 4 1 4 22 Trend Component Persistent overall or pattern Changes due to population technology age culture etc Typically several years duration 2014 Pearson Education Inc 4 23 Seasonal Component Regular pattern of up and down Due to weather customs etc Occurs within a single unit NUMBER OF SEASONS IN PATTERN PERIOD LENGTH Week Month Month Year Year Year SEASON LENGTH Day Week Day Quarter Month Week 7 4 4 5 28 31 4 12 52 2014 Pearson Education Inc 4 24 Cyclical Component Repeating up and down movements Affected by business cycle political and economic factors years duration Often causal or associative relationships 2014 Pearson Education Inc 0 5 10 15 20 4 25 Random Component Erratic unsystematic residual fluctuations Due to variation or unforeseen events Short duration and nonrepeating 2014 Pearson Education Inc M T F W T 4 26 Overview of Quantitative Approaches 1 Naive approach 2 Moving averages 3 Exponential smoothing 4 Trend projection 5 Linear regression time series models associative model 2014 Pearson Education Inc 4 27 Naive Approach Assumes demand in period is the as demand in most recent period e g If January sales were 68 then February sales will be 68 Sometimes cost effective and efficient Can be good 2014 Pearson Education Inc 4 28 Moving Average Method MA is a series of means Used if little or no trend Used often for smoothing Provides overall impression of data over time 2014 Pearson Education Inc 4 29 Moving