Old knowledge newly used

First, the description.

Yet again, one to add to the list of low-hanging fruit when it comes to innovation. Immense productivity increases reported here, with reduced wait times and earlier diagnosis likely saving a great many lives: https://t.co/hV51PlJ58S

— Dr Anton Howes (@antonhowes) December 12, 2023

Glancing through this, though, and taking nothing away from the two doctors for bringing the innovative processes into reality, the innovation is in the doing, not necessarily the concepts.

Specifically, much what seems to be being described seems like basic problem solving, TQM, reengineering and Six-sigma tools applied in a medical context.  Peter Drucker and Edwards Deming redux.  

I was having a conversation the other day about the fact that we have had tremendous progress in the past fifty years, largely from using problem solving, TQM, reengineering and Six-sigma tools, in improving manufacturing, supply chain, and logistics for material goods and yet seem not to have made nearyl as much progress applying the same tools to services businesses.  They are applicable.  Either we haven't applied them or have somehow failed to make the application work.

I have done a lot of work on both sides of the equation quality tools and techniques applications in material production and in services.  I can lay my hands on legion and definitive research and case studies on the material production side of the house.  The pickings are more meager on the services side.

I have some weak speculation as to why that might be but I have no great confidence in those explanations.  My buddy was similarly absent of robust explanation for the phenomenon.

Atul Gawande wrote The Checklist Manifesto in 2009, championing an ancient quality control tool, the checklist, in modern medicine.  

Which poses the interesting epistemic paradox.  Not knowing the answer is not the issue which precludes progress.  Not using the knowledge already known is the issue.

We are pinning a lot of hopes on AI for improving national productivity over the next couple of decades, and it will likely makes some material contributions.

My sneaking suspicion, though, is that we might get similar increases in productivity were we simply to seek to ensure that all quality related tools and techniques were well known and well-applied on all areas where they can make a difference.  

We have done well with these tools and techniques so far in the past fifty years.  My deep suspicion is that we simply have not used them nearly as extensively as they could be.  We have used them dramatically (see the improvement in quality and cost in automobile manufacturing) in select sectors but virtually not at all in others (see eduction).  Were we to use the same tools and techniques with which we are already experienced and familiar in sectors yet untouched, I suspect we might see further dramatic improvements in productivity.

Why have we not done so?

My default theory is that Quality Improvement was first adopted in manufacturing for two reasons.  1) Manufacturing is capital intensive - you build a new plant and it is expensive and it will last a long time.  Incrementally minor improvements at the margin aggregate into major improvements in the bottom line.  2) Those most directly affected, blue collar workers, are less well represented in the national policy and political environments of the 1970s-present day.  Policy tends to be made by white collar people and they can be class blind to the interests and needs of those in the blue collar ranks.  White collar people find it easier to impose the costs of change (which occur with Quality Improvement) on blue collar people than they do on other white collar people.

When you look at the TQM-thin services sector, where have you found real application of Quality Management?  In the parts that are most like manufacturing in terms of being long cycle or primarily blue collar.  SCM and Logistics are fantastically more efficient and reliable than twenty years ago.  But with equipment and warehouses, that is a capital intensive sector with long investment time horizons and those most impacted are blue collar people (see Amazon warehouse labor issues.)  

Medical, Law, education, government - white collar, comparatively shorter cycle times and less capital intensive.  And overwhelmingly white collar.

It is at best an adequate theory.  The real answer might be different or at least more complex.