Casting votes of antecedents play a key role in successful sequential decision-making.

Aggregation of opinions often results in high decision-making accuracy, owing to the collective intelligence effect. Studies on group decisions have examined the optimum weights for opinion aggregation to maximise accuracy. In addition to the optimum weights of opinions, the impact of the correlation among opinions on collective intelligence is a major issue in collective decision-making. We investigated how individuals should weigh the opinions of others and their own to maximise their accuracy in sequential decision-making. In our sequential decision-making model, each person makes a primary choice, observes his/her predecessors' opinions, and makes a final choice, which results in the person's answer correlating with those of others. We developed an algorithm to find casting voters whose primary choices are determinative of their answers and revealed that decision accuracy is maximised by considering only the abilities of the preceding casting voters. We also found that for individuals with heterogeneous abilities, the order of decision-making has a significant impact on the correlation between their answers and their accuracies. This could lead to a counter-intuitive phenomenon whereby, in sequential decision-making, respondents are, on average, more accurate when less reliable individuals answer earlier and more reliable individuals answer later.