Before rushing headlong into the problem-solving or decision-making stage, scientists need to look at the nature of the problem before deciding what to do. For a problem with only one solution, an analytic approach might be best. However, for problems with multiple solutions, a scientist may need an approach that first figures out a few possible answers from many possibilities, then considers the strengths and weaknesses of each proposed solution. Sometimes a scientist might even need a team to come to an acceptable answer. Once they have determined the the type of answer they are seeking, they have a better idea of what kind of method to apply.
The pros and cons decision-making method is based upon the idea of weighing many choices for their individual merits. If the problem has many solutions, this can be a useful mechanism. This method relies upon coming up with many possible solutions first, in a process called brainstorming. Once the scientist has selected many potential solutions, he lists them and then makes two columnar lists for each one. The positive aspects of each solution is placed in a pros column, and the negative aspects are listed under the cons column. This list often makes it easy to select a choice.
The pros and cons method is sometimes insufficient to refine a specific result. In those cases, it sometimes helps to apply a grading rubric to the process. For each potential answer, the scientist comes up with a list of concerns that are important to the quality of the decision. They grade how each solution meets a given concern with a common scale. At the end, the answer that has the highest total value as graded is selected as the best solution.
Sometimes it's hard to envision how a solution will play out in the course of its application. For example, if an engineer is trying to decide how a dam will affect the community, sometimes pictures alone will not suffice. If there are concerns with construction methods, space, safety or utility, modeling is a good tool. The model can be as simple as creating a blueprint and applying simple force diagrams to it or as complex as using three-dimensional simulations of the environment, depending upon resources and the specific need. Modeling generally works best on problems where the solutions are spatial or visual, but applied creatively can assist in other decision types as well.
In some cases, the answer that seems best to one scientist might not be the best for them all. For example, if the consideration is proposed on how to spend a financial budget for a team, one person is seldom going to be the best decider for the body as a whole. In these cases, it is often beneficial to employ many people in the problem-solving process. In much the same way, as in the brainstorming steps of many problem-solving techniques, the scientists propose a number of solutions. Instead of relying on an individual to assess the value of the potential solutions, a group consensus is applied to determine which one offers the best outcome.