When actual demand is zero, MAPE is infinite.  By definition, forecast error can be greater than 100%.  However, accuracy cannot be below zero.

Forecast Accuracy = max (1 - forecast error, 0)

If Actual demand is 25 and forecast is 100, then error is 75 implying a 300% error. But accuracy is always zero for cases where error is higher than 100%. You can use the ISERROR function in excel to overcome the DivisionByZero error. Although this is an excel workaround, this actually preserves the impact of the actual being zero in calculating the total forecast error.   See the excel accuracy template available at DemandPlanning.Net Downloads.

Here is a list of key acronyms and abbreviations used very commonly by supply chain professionals.  Some are more specific to forecasting, nevertheless this should be a useful reference.

Supply chain metrics include customer service metrics (fill rates), inventory metrics (inventory turns, dead and near-dead inventory, inventory coverage), manufacturing planning (production volatility, manufacturing schedule adherence), and demand metrics (forecast accuracy and forecast bias.  Once defined, the question is who will own these measures.  All the measures are inter-related.  By observing the metrics, we can understand the effect of organizational bias.  More.