Trying to solve  a problem without baseline data is a fool’s errand.
It is the contrast between the data of the process, and the baseline data, that makes it possible to identify that a problem exists and to analyze it for root cause.
Most problems are identified because the output departs from the expected.
Brainstorms do not solve problems, they usually just waste resources in a process of aggrandized groupthink.

How's the power production there, team?

I call this “the Diff” when I am working with continuous improvement teams. It is the difference between expected and actual.
You cannot have a difference without having an expected or baseline measure of the characteristic to be improved.
Four Measures that I have used in my continuous improvement work include

  • Frequency of Occurrence,
  • Cost,
  • Duration,
  • Location of Occurrence.

Frequency of Occurrence
The difference between expected (or under statistical control) frequency and the rate of occurrence in the current state gives insights into what may be occurring. If it is a small fraction of a percent- it is unlikely that a global change of process is needed. if the rate is in the double digit percentages, it is likely that there is a major change in the process (or needed!)
Simple ratios can also be powerful clues. Defects arriving in 20, 25 or 33 percent  of the production point to areas within the greater process where there may be 5, 4, or 3 sub processes- like dies, cavities, or molds. Similarly, a rate of 12.5%  on an 8 spindle screw machine tells me not to look at a single tool ( it hits all 8 spindles) but instead to look for one of the 8 spindles (12.5% of the machine’s total production) that might be out of line compared to the others.
My cell phone costs spiked almost 100%  in July of 2010. In August, I brought my Dad back home to a nearby assisted living facility. The cell phone cost data was a pretty clear ‘cost’ signal that something had changed compared to prior (baseline) bills- Dad need assistance. ( BTW- Dad’s doing fine!)
Comparison of time to complete 100 ton orders on my mill  grew  by a significant figure, and follow up indicated a problem at an intermediate shear. Without baseline data, how would I have known  that my production time had increased?
Location of occurrence
This  is another piece of data that when tallied against the baseline of “no occurrences” always leads your thinking. If it only occurs in the threaded area, but not on the original bar surface, what does that mean?
Looking for deltas or “Diffs” between your baseline and current process data is a far better way to inform your Problemsolving than Brainstorming.
Interested? The Delta is the Difference