"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.
http://www.overcomingbias.com/2008/06/average-your-gu.html
The same point is made there, with the addition that the second guess is usually worse than the first. What kind of weighting do we need to put second answer so that we can eliminate that bias? It has to be less than one (since the second answer is worse than the first), but more than one fourth (since the average is better than the first guess)
The improvement in this paper, over simply making two estimates one after another, is the focus on assuming your first estimate is wrong while constructing your second estimate.
The control group in the paper did make two estimates; I'll edit to emphasize that.