Another thing I've observed is when you have two measures that operate at different time scales. Both may even be valid measures, but the one measured (and responded to) more often has a stronger impact, and can negatively impact the less frequently measured metric when there's a conflict between them.
A particular instance for this has been (to keep it simple) quantity (speed) and quality in production environments (factories and the like). Daily throughput measures paired with less frequent quality measures. The desire is to keep throughput high, and quality ends up suffering as a result. By integrating quality measures into the process you make the two measures compete on more equal footing, forcing a balance. At least one factory I worked in (well, adjacent to, I was in the software portion not the assembly line) massively reduced their quality problems by integrating quality checks between each station. This contrasted with the prior years where throughput, being measured and reacted to daily, drove them to make things so fast that they had piles of rework at the end. Integrating the quality measures between stations slowed them down, but their rework numbers turned into a rounding error (over a decade ago so I've forgotten the exact numbers, but they went from having items needing rework nearly every day to maybe one or two a month). As a result their real (deliverable to customers) production increased and their cost per unit dropped.
I see this as the root cause of the recently announced class action suit against LADWP over their implementation of tiered electricity pricing.
The tiers (kwh rates) are in hunks of the a day measured in hours.
But the reporting is only available to the consumer in the form of a monthly bill, so by the time you discover you were eating pixies in the Peak Cost hours the heat wave is over and your bill is already through the roof.
(Any local SoCal residents please feel free to pick my analysis apart, but that was my first take when I heard about the legal action.)
A particular instance for this has been (to keep it simple) quantity (speed) and quality in production environments (factories and the like). Daily throughput measures paired with less frequent quality measures. The desire is to keep throughput high, and quality ends up suffering as a result. By integrating quality measures into the process you make the two measures compete on more equal footing, forcing a balance. At least one factory I worked in (well, adjacent to, I was in the software portion not the assembly line) massively reduced their quality problems by integrating quality checks between each station. This contrasted with the prior years where throughput, being measured and reacted to daily, drove them to make things so fast that they had piles of rework at the end. Integrating the quality measures between stations slowed them down, but their rework numbers turned into a rounding error (over a decade ago so I've forgotten the exact numbers, but they went from having items needing rework nearly every day to maybe one or two a month). As a result their real (deliverable to customers) production increased and their cost per unit dropped.