One key to writing an effective proposal is to have some encouraging preliminary results. It's important that there is neither too little data (which may indicate too much risk), nor too much (which may indicate a lack of need for funding).
Although it may seem a little confusing if you're new to this, the 'titration' model of presenting preliminary data is useful because there are so many ways that responsible parties may feel the need to be cautious when judging whether research is worth an investment. There are many individuals who can act as "Dr. No\ when reviewing proposals, for a wide variety of reasons.
For example, it's taxpayer money that is being spent. Accountability falls on the shoulders of the proposers, the reviewers, the program managers, the directors of funding agencies, and the Congresspeople who allocate budgets for science and technology research. The why and the how of the research need to be mapped out in sufficient detail, and with sufficient justification, such that it's almost not research by the time it's fundable, but rather a set of tasks that look more like a manufacturing effort. Do step A, needed for these reasons, interpret 'up' or 'down' results, go to next steps B or C accordingly...and so on.
In reality, however, true research is fuzzy, uncertain, exploratory, and risky. Possible questions and their possible answers are not always clear from the outset. Scientists need to be able to launch new efforts with a great margin of error, and be allowed to fail.
Judicious revelation of some results can bridge this gap. This strategy plays to the hyper-risk-averse audience, to assure them that you're doing something worthwhile.
The author's affiliation with The MITRE Corporation is provided for identification purposes only, and is not intended to convey or imply MITRE's concurrence with, or support for, the positions, opinions or viewpoints expressed by the author.