SCIENCE, Physics, DeSIGN
My professional career as a multidisciplinary engineer has been in the realm of assuring reliability of safety-critical products, sub-systems and components as well as in working in the business-critical areas of eliminating waste and making organizations LEAN.
LEAN thinking probably has the biggest impact, but it is dreadfully simple for most people to appreciate. People, particularly engineering managers, tend to appreciate the superstitious magic of impenetrable complexity. LEAN is not magic. LEAN might look simple but making something look simple is almost never easy ... if you want to make something LEAN, you must relentlessly apply the D.O.W.N.T.I.M.E. habitually on such a continuous, nonstop fashion so that you immediately see and eliminate waste without even thinking about tolerating it ... get rid of Defects, Overprocessing, Waiting, Neglect, Transport, Inventory, Motion, Ego ... all are important, but perhaps the most important are eliminating Ego and any kind of pretentious behavior; that helps the cause in other areas, such as never ever ever Neglecting anyone's suggestions for improvement -- you need the ideas coming from the bottom most. Listen to the guy has to clean up behind the parade of elephants before you waste any time listening to the jibberish spewing from mouth of the CEO, even though somebodies going to have to clean up after that asshole's parade ... when you travel, treat the maid making your bed in the motel with more respect than you show anyone else.
The quality discipline can seem to get complicated, particularly in complex systems, but the reality is that it is almost tediously simple ... simple structures like the Define-Measure-Analyze-Improve-Control framework OR the 8-step corrective action and root cause investigation of failures OR the risk prioritization of Failure Modes and Effects Analysis. We use the Plan-Do-Check-Act cycle over and over and over; we methodically work at managing the scope of a project [and its requirements, calendar and budget] then define key variables and measure those things with repeatable, reproducible, unbiased stable measurement systems so that you can optimize or achieve reliability growth in a quantified form. Maybe it can sound like a bunch of jargon, but it's mostly about disciplined listening and investigation -- seeking first to understand BEFORE breaking out the heavy duty quant stuff. As with data science and how much effort must be devoted to data wrangling FIRST, the FUN part of the quality discipline involves the application of math, statistics and heavy machinery ... when people don't understand the problem first, ALL of their masturbatory analysis is FAR WORSE than being merely useless.