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This question is motivated by an argument that arose in relation to this question.

We know there are decadal surveys recommending the priorities in planetary exploration. There is also a neat problem summarized by Andrew Kennedy (see wait calculation) for interstellar exploration probes.

Each mission study has the following hard-wired quantitative parameters:

  • time to develop, test and launch the spacecraft (given by the launch window);
  • maximum payload mass, power, and datarate that limit how much data can be collected and how fast the results can be transferred (given by the chosen trajectory and available launchers);
  • time in transit from launch to destination (or destinations) when the scientific payoff is minimal;
  • cost of launch campaign;
  • cost of mission control over various mission phases;
  • use of otherwise limited resources (like plutonium-238 for RTGs).

There are also "soft", less quantifiable parameters:

  • expected value of scientific results;
  • probability of missing the launch window due to the need for redesign;
  • expected development costs.

A naive straightforward approach would be to calculate discounted net present value (NPV) of all the outlays and scientific results (somehow converted into money) and use it or the implicit rate of return to compare missions.

My question is twofold:

  • Is there a widely-accepted handbook outlining theory to be used in top-level decision making while choosing the mission portfolio?
  • Are there any studies that analyze how decisions are really made (by NASA or other agencies)? What discounting rates are implicitly used by decision-makers?
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    $\begingroup$ It isn't possible to even try to quantify the NPV of basic research. The decision must be made on qualitative basis and gut feeling. Different research areas, which happen to be established, taking turns as in it being Venuses time now soon, and of course progressive to further away planets as in Uranus next. Johannis Kepler's equation for Mars' movements ended up as the basis for Newton's and Einstein's equations too. The emperor certainly expected a high NPV from his investment in astrological research, but from forseeing the destiny rather than from industry. $\endgroup$ – LocalFluff Oct 25 '15 at 8:08
  • $\begingroup$ @LocalFluff - the truth is out there ;) Gut feeling is awfully subjective and indefensible. $\endgroup$ – Deer Hunter Oct 25 '15 at 8:34
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    $\begingroup$ Well, the gut is as good as the brain when it comes to the unknown. And there's no point with discovering the known. Some administrative rituals may provide comfort, and distribute responsibilities randomly when stuff fails. But it doesn't help the discovery process. It is psychologically hard to accept ignorance, but that's the very raison d'etre for basic research (and even for many entrepreneurial investments). $\endgroup$ – LocalFluff Oct 25 '15 at 8:50
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    $\begingroup$ @LocalFluff - There was actually an economic paper back in 2012 entitled Basic Research and Prosperity: Sampling and Selection of Technological Possibilities and of Scientific Hypotheses as an Alternative Engine of Endogenous Growth that actually tried to estimate the financial return of basic research. It is a very interesting paper, especially if you are grant-dependent researcher ;) $\endgroup$ – honeste_vivere Dec 6 '15 at 19:42
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This is actually a really good question, but quite a bit more involved. How missions in general are prioritized is as follows (For discovery class missions, or the Martian Scout Program):

  1. A scientist (Or group of scientists) decides they want to see a certain kind of mission.
  2. Periodically, NASA sends out solicitations for proposals. Typically any mission is allowed, so long as the mission can be done for a particular cost.
  3. NASA looks at all of the proposals, along with a team of reviewers from other scientists. They essentially weight each proposal, on the science achieved and the engineering of the project, etc, to see if the mission can succeed.
  4. NASA gives a select few teams more money to develop the missions, to ultimately pick the one with the best science/ engineering combination.

The short answer, the more scientists are interested in something, the more highly weighted it will be. This really applies for every class of NASA mission to some extent. #4 is the real key.

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