OMIS 320 - Chap 5

collaborating planning, forecasting and replenishment (CPFR)

According to the Voluntary Interindustry Commerce Standards (VICS) Association, CPFR is "a b usiness practice that combines the intelligence of multiple trading partners in the planning and fulfillment of customer demand. CPFR links sales and marketing best practices, such as category management, to supply chain planning and execution processes to increase availability while reducing inventory, transportation and logistics costs.

multiple regression forecast

a forecast technique using multiple regression

naive forecast

a forecasting approach where the actual demand for the immediate past period is used as a forecast for next period's demand

linear trend forecast

a forecasting method in which the trend can be estimated using simple linear regression to fit a line to a time series of historical data

cause and effect forecasting

a forecasting method that uses one of more factors (independent variables) that are related to demand to predict future demand

exponential smoothing forecast

a forecasting technique in which forecast for next period's demand is the current period's forecast adjusted by a fraction of the difference between the current period's actual demand and forecast

running sum of forecast errors (RSFE)

a measure of forecast bias - that is, whether the forecast tends to be consistently higher or lower than actual demand

forecast bias

a measure of the tendency of a forecast to be a consistently higher (negative bias) or lower (positive bias) than the actual demand

simple moving average method

a method that uses historical data to generate a forecast; it works well when the demand is fairly stable over time

time series forecasting

a prediction technique based on the assumption that the future is an extension of the past and that historical data can thus be used to forecast future demand

weighted moving average forecast

a technique that allows greater emphasis to be placed on more recent data to reflect changes in demand patterns

tracking signal

a tool used to check the forecast bias

business cycle

alternating periods of expansion and contraction in economic activity

mean absolute deviation (MAD)

an indicator of forecast accuracy based on an average of the absolute value of the forecast errors over a given period of time. The measure indicates, on average, how many units the forecast is off from the actual data

mean absolute percentage error (MAPE)

an indicator of forecast accuracy based on the true magnitude of the forecast error. The monthly absolute forecast error divided by actual demand is summed, then divided by the number of months used in the forecast to derive an average, and lastly multiplied by 100. The measure indicates, on average, what percent the forecast is off from the actual data.

mean square error (MSE)

an indicator of forecast accuracy. The forecast errors are squared and then summed and divided by the number of periods to determine the mean square error. The measure penalizes large errors more than small errors

quantitative forecasting methods

forecasts based on mathematical models and relevant historical data

qualitative forecasting methods

forecasts based on opinions and intuition

simple regression forecast

similar to the linear trend forecast. The difference is that the independent variable is no longer time but an explanatory variable of demand

forecast error

the difference between actual demand and the forecast

cloud computing

when shared resources and other info ration are made available to users over the internet, usually for a subscription fee. It allows small businesses, for example, to make use of sophisticated software without actually making the purchase; also termed on-demand computing