We explore the impact of judgement bias on demand forecast accuracy and profit to identify thedriving force of decision-makers to be biased. We study the accuracy-maximising forecasts and theprofit-maximising forecasts, which results in the least error of demand forecasts and minimum devi-ation from the optimal order decision, respectively. Under the assumption that period-to-perioddemand is independent over time, we find that both types of forecasts are biased. It implies thata newsvendor has the motivation to be biased to obtain either a more accurate demand forecastor a higher profit. Moreover, the decision error under the accuracy-maximising forecasts can belower than that under unbiased demand forecasts and be bounded by twice of the error underprofit-maximising forecasts. It suggests that the biased accuracy-maximising forecasts can per-form satisfactorily in both forecasts and decisions. We further relax the assumption of independentdemand by considering correlated and trended demand processes, and show the robustness of thepositiveimpactofjudgementbias.Wethenproposeamethodtosolvepuredata-drivennewsvendorproblem and examine its performance with empirical evidence. Our paper contributes to the litera-ture on behavioural operations management by investigating the rationality of judgement bias andits implications.