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Figure Figure 3 Revenue operations & AI

Four tests, two instruments, no survivor

The first instrument alarms on noise and on bookkeeping. The rebuild is robust and blind: it detects a real 30% shift less often than it false-alarms. The marked rows are why nothing is prescribed.

Of four simulation tests, the naive elasticity instrument fires on 49.8% of pure-noise runs and on 98.9% of pure accounting reclassifications; the first-difference rebuild fires on only 3.9% of reclassifications but detects a genuine 30% variable-cost shift in only 3.8% of runs, below its own false-positive rate.20%40%60%80%100%v1: fires on random noise49.8%v1, tested: fires on a reclassification98.9%v2: fires on a reclassification3.9%v2: detects a real 30% shift3.8%Share of simulation runs (%)
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Reference & Evidence

Source: diagnostic-v1-failed.py, 20,000 replications: fires on 49.8, 50.7 and 49.6% of runs across three noise levels, the first drawn here. diagnostic-v2-failed.py, 6,000 replications: a one-off 8% cost reclassification, and a ramped 30% variable-cost shift with a bootstrap interval. Both published as failures at isoglu.com/research/gross-margin-panel/.

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