Which statement best describes 'Bias' in forecasting?

The statement that best describes 'Bias' in forecasting is a consistent deviation from the mean in a random manner. Bias refers to systematic errors in forecasts that consistently overestimate or underestimate the actual values. This means that if a forecasting process has bias, it will often predict results that deviate from the average (mean) values in one direction systematically, rather than providing a balanced forecast around the mean. In forecasting contexts, understanding bias is crucial because it can impact decision-making if forecasts are consistently unreliable due to either overestimating or underestimating future demands or trends.

The other options do not accurately capture the concept of bias in forecasting. Total forecast accuracy involves many metrics that assess how well forecasts match actual outcomes, while a normal property of a good forecast generally entails being unbiased; thus, bias would not be considered a desirable characteristic. A trend influencing future forecasts refers more to how patterns over time can affect predictions, but it does not specifically denote the systematic error described by bias.