Reference: Data Series
Reference: Data Series 19—THE REAL WHY
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THE REAL WHY
WHY = that basic outness found which will lead to a recovery of stats.
WRONG WHY = the incorrectly identified outness which when applied does not lead to recovery.
A MERE EXPLANATION = a “Why” given as THE why that does not open the door to any recovery.
Example: A mere explanation “The stats went down because of rainy weather that week.” So? So do we now turn off rain? Another mere explanation “The staff became overwhelmed that week.” An order saying “Don’t Overwhelm Staff” would be the possible “solution” of some manager. BUT THE STATS WOULDN’T RECOVER.
The real WHY when found and corrected leads straight back to improved stats. A wrong why, corrected, will further depress stats. A mere explanation does nothing at all and decay continues.
Here is a situation as it is followed up:
Stats are down in a school. An investigation comes up with a mere explanation: “The students were all busy with sports.” So management says “No sports!” Stats go down again. A new investigation comes up with a wrong why: “The students are being taught wrongly.” Management sacks the dean. Stats really crash now. A further more competent investigation occurs. It turns out that there were 140 students and only the dean and one instructor! And the dean had other duties! We put the dean back on post and hire two more instructors making three. Stats soar. Because we got the right why.
An arbitrary is probably just a wrong why held in by law. And if so held in, it will crash the place.
The test of the real WHY is “when it is corrected, do stats recover?” If they do that was it. And any other remedial order given but based on a wrong why would have to be cancelled quickly.
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