I believe the way we collect data around the economy needs to be completely rethought. It's clear that the gig economy model is the future for many workers, but it's proliferated in a way that absolves companies of financial responsibility and has created massive inequality that our current system isn't able to effectively address.
We have to rethink the way we define and calculate employment, underemployment, and unemployment to more realistically align with how the labor market works today. It would be a very ambitious effort, no doubt.
I recall a time many moons ago when I was doing some research on the way in which my state determined their own employment/economic statistics.
It was quite an eye opening experience and exploration. State level economists/demographers are using totally obsolete methods, worse was they they didn't want to disclose certain key elements short of a DPA (state equivalent to FOI) which further led to believe that their archaic approach may be intentionally misleading because "look at how great our unemployment rate is" ;)
I can't speak to fed stuff, never dug in to deep. Totally agree with what you are saying and wondering what (trusted) existing KPIs out there would make sense to look at as say a subcategory of unemployment, if it gets any more granular?
Ultimately, the most hopeful future I see is one where all levels of government, from municipalities all the way up to the federal government report out raw data as close to real-time as possible so that academic institutions, non-profits, etc., can do data science for the public, so to speak.
We have to rethink the way we define and calculate employment, underemployment, and unemployment to more realistically align with how the labor market works today. It would be a very ambitious effort, no doubt.