Measure What Suppliers Actually Do, Not What They Promise
Your vendor master data says a supplier has a 6-week lead time. Reality says 9 weeks. Alora tracks actual delivery performance against quoted lead times, monitors confirmation patterns and slips, and scores each supplier at the part level — so risky vendors surface first in your worklist, not after they've already caused a delay.
The Challenge
What teams deal with today
Quoted vs. Actual Lead Times Diverge
Supplier lead times in ERP are often outdated or optimistic. Without tracking actual performance, procurement plans are built on unreliable assumptions.
Vendor Performance Is a Black Box
Most teams rely on gut feel to judge supplier reliability. There is no systematic scoring, and the same unreliable suppliers cause repeated delays.
Deteriorating Patterns Go Undetected
A supplier doesn't go from reliable to unreliable overnight. The warning signs are subtle — slightly longer confirmations, occasional quantity mismatches — and invisible without trend data.
Overall Scores Hide Part-Level Problems
A supplier may perform well overall but consistently fail on specific part categories. Aggregate scorecards miss these targeted weaknesses.
How Alora Solves This
Built for this exact problem
Real vs. Quoted Lead Times
Track actual delivery performance against what was promised on the PO.
Part-Level Scoring
Score suppliers per part number — not just overall. One bad category surfaces clearly.
Feeds Into Prioritization
Vendor scores feed directly into PO risk ranking — risky suppliers surface first.
Pattern Recognition
AI identifies deteriorating patterns before they become delivery failures.
How It Works
From data to action
Track Every Interaction
Alora monitors every PO confirmation, date change, quantity adjustment, and delivery event across all your suppliers — automatically, from ERP and email data.
Score at the Part Level
Each supplier gets a behavior score per part number — not just an overall rating. A supplier who delivers motors on time but consistently delays control boards shows both clearly.
Detect Trends and Patterns
Alora's AI identifies deteriorating patterns before they become delivery failures. Gradually increasing lead times, more frequent re-confirmations, or growing confirmation gaps all trigger early warnings.
Feed Into Risk Prioritization
Vendor scores flow directly into PO risk ranking. When a poorly-scoring supplier has an open PO line for a critical build, it automatically surfaces higher in the worklist.
Real Scenarios
How this plays out in practice
Hidden pattern reveals at-risk supplier
A long-standing supplier gradually extends their average lead time from 4 weeks to 6 weeks over 6 months. No single PO is late enough to trigger an alarm, but the trend is clear in the data.
Alora detects the deteriorating pattern and flags the supplier's score as declining. The procurement team opens a conversation with the supplier before the next critical order is placed, avoiding a potential 2-week delay on a $600K build.
Part-level scoring reveals hidden weakness
A supplier has a 91% on-time rate overall — above threshold. But their on-time rate for a specific connector family is just 62%. The aggregate score masks the problem.
Alora's part-level scoring surfaces the connector weakness immediately. The team qualifies a secondary source for that part family while keeping the supplier for their strong categories.
See Vendor Scoring in Action
A focused conversation about execution — we'll walk through how it actually works.