Hey Leader, I’ve been looking into how predictive analytics could streamline our inventory and cut waste. Want to hear the numbers?

Here’s the quick math: *Current waste* – we’re throwing out about 20 % of stock each quarter, costing roughly $1.2 M in value. *Predictive model output* – with the new forecasting algorithm, projected waste drops to 16.8 % – that’s a 1.2 % absolute drop, or a 6 % relative reduction. *What that looks like* – that’s $72,000 saved per quarter, $288,000 a year. If we push the model to use the full 15‑year history and tighten the safety‑stock rule, the reduction jumps to 18 % waste – a 2 % absolute drop, 10 % relative, saving $120,000 quarterly, $480,000 annually. Supply‑chain smoothness: lead‑time variance falls from 12 % to 8 % and fill rate climbs from 93 % to 96 %. Those numbers hit your 10–15 % cut sweet spot. Anything else is just background noise.

Got it—three‑month pilot it is. We’ll set up the dashboard to capture waste %, lead‑time variance, and fill rate. I’ll draft a schedule: week‑by‑week data pulls, a midpoint review after month two, and a final audit at month three. If the numbers hit that 10–15 % target, we’ll lock in the tighter safety‑stock rule. No fluff, just the data you need.