"Dialectical Bootstrapping" is a simple procedure that may improve your estimates. This is how it works:
- Estimate the number in whatever manner you usually would estimate. Write that down.
- Assume your first estimate is off the mark.
- Think about a few reasons why that could be. Which assumptions and considerations could have been wrong?
- What do these new considerations imply? Was the first estimate rather too high or too low?
- Based on this new perspective, make a second, alternative estimate.
Herzog and Hertwig find that average of the two estimates (in a historical-date estimating task) is more accurate than the first estimate, (Edit: or the average of two estimates without the "assume you're wrong" manipulation). To put the finding in a OB/LW-centric manner, this procedure (sometimes, partially) avoids Cached Thoughts.
In the reliability condition, the first and second estimates for each question were nearly identically accurate, with a mean within-participants difference of 0.4 (SD = 6.7; Mdn = 0.0; confidence interval, or CI = 0.0–+1.4; d = 0.06). In the dialectical-bootstrapping condition, the second estimates were somewhat, but not reliably, more accurate than their respective first estimates (within-participants difference: M = 4.5, SD = 19.6; Mdn = 3.0; CI = -1.0–+10.4; d = 0.23).