The Problem
Picture a 38-person supplier in Auburn Hills making inventory and purchasing decisions on data that is three weeks old on average. Reporting takes one operations manager half a day every month. She pulls figures from four systems (the ERP, the supplier portal, the logistics platform, and a spreadsheet only she fully understands) and assembles them into a summary for leadership. Tuesday's decisions get made with last month's numbers, and over-ordered inventory keeps eating into margin.
The Solution
The audit maps the four data sources and finds the 12 metrics that drive purchasing decisions. The build is two connected automations. The first is a weekly KPI digest that pulls from all four systems at 6 a.m. every Monday and sends leadership a plain-English summary of inventory levels, open POs, supplier lead-time changes, and a three-week demand signal. The second is an alert that fires when a tracked SKU falls below its threshold and suggests a reorder, with quantities calculated from past usage.
- Automated weekly KPI digest from 4 connected data sources
- Plain-English narrative summary with leadership-ready format
- Exception alerts with pre-calculated reorder suggestions
- Real-time inventory threshold monitoring for critical SKUs
The modeled results
Before
Baseline
After
−17%
Before
4–5 hrs / month
After
0 hrs / month
Before
~3 weeks old
After
Current week
Before
Reactive (after stockout)
After
Proactive (7-day warning)
Million-dollar purchasing decisions shouldn't run on month-old data and a spreadsheet only one person understands. The target is a Monday briefing leadership can read in five minutes, with carrying-cost savings that cover the engagement inside a quarter.Tier-1 automotive lessons for SMB AI adoption