module 6 pm

• Forecasting techniques


  Models that utilize managerial expertise, judgement, and intuition into formal forecasts
• Executive opinion


  Corporate top-down forecasting technique where the forecast is arrived at through the opinions, predictions, and experiential judgement made by informed executives and experts
• Sales force composite


  Corporate bottoms-up forecasting method where frontline employees (i.e., sales personnel and customer service representatives) provide forecasts based on customer feedback
• Scenario analysis


  1. Exploratory scenario starts in the present and moves out to the future based on current trends

  2. Normative scenario analysis leaps out to the future and works back to determine what path to take to achieve an expected goal
• Delphi method


  Technique based on subjective expert opinion gathered through several structured anonymous rounds of data collection
• Decision trees


  Probabilistic approach to forecasting where various contingencies and their associated probability of occurring are compared against each other
• Assumption-based modeling


  Technique that attempts to model the behavior of the relevant market environment by breaking the market down into observable factors
• Forecast by analogy


  Technique that assumes that two different kinds of phenomena share the same model of behavior
• Time series models


  Use historical data as the basis of estimating future
• Moving average/weighted moving average


  In financial applications, a simple moving average (SMA) is the (weighted) mean of the previous n data points
• Exponential smoothing


  A set of techniques that develop forecasts by addressing the forecast components of level, trend, seasonality, and cycle
• Autoregressive moving average (ARMA)/Autoregressive integrated moving average (ARIMA)


  A set of advanced statistical approaches to forecasting which incorporate key elements of both time series and regression model building, sometimes called box-jenkins models
• Extrapolation


  A method for projecting out a forecast based on past sales
• Diffusion models


  Models that estimate the growth rate of a durable product by considering the impact of mass media and word of mouth influence on the consumer adoption process
• Linear regression


  Assesses the relation between one or more managerial variables and a dependent variable
• Non-linear regression


  Assesses the relation between one or more managerial variable and a dependent variable
• Logistic regression


  Assesses the relation between one or more managerial variables and a binary outcome
• Concept testing


  A survey asking consumers to evaluate their probability of buying a new product/service based on a concept description
• Product-use testing


  A market research process in which consumers evaluate the effectiveness of a marketing campaign
• Premarket testing


  A market research procedure that uses syndicated data and primary consumer research to estimate the sales potential of new product initiatives through forecasts of purchase intent and preference share
• Market testing


  A market research process by which targeted customers evaluate the marketing plan and the new product in marketing setting
• Forecasting level


  Focal points in the corporate hierarchy where the forecast applies
• Forecasting time horizon


  The time frame for how far out one should forecast
• Forecasting time interval


  The granularity of the forecasts with respect to the time interval as well as how often the forecast might be updated
• Forecasting form


  The unit of analysis for the forecast
• Contingent forecasting strategies


  • Sales analysis strategy in a current market with current product technology
  • Product life-cycle strategy in a current market with new technology for line extensions
  • Customer/market analysis strategy in new market with current technology
  • Scenario analysis (what if) strategy in new market with new product technology