Lost time. Lost output. Lost opportunity.
Look across Lean waste, downtime, quality, and resource use to understand where your operation keeps losing value.
Total Loss Intelligence for Operations
Turn scattered reports and performance data into a clear picture of recurring loss. See what it costs, where to act, and whether the fix worked.
Find recurring losses. Focus improvement. Verify what works.
Discover what is lost. Understand what it costs. Focus action where it matters, verify the fix holds, and carry the learning forward.
Explore the platformFind recurring loss.
Estimate the exposure.
Focus where it matters.
Identify evidence-led actions.
Check for lasting improvement.
Feed outcomes into discovery.
A stoppage in a shift log. A deviation in a quality report. The same problem after another fix. Verdant connects the evidence so you can see where loss repeats and what deserves attention.
Look across Lean waste, downtime, quality, and resource use to understand where your operation keeps losing value.
Find a recurring problem. Connect it to performance and estimate what it may cost.
See an unexplained loss. Find the related issues and conditions worth investigating.
Four practical steps. One connected loop of evidence, action, and learning.
Bring together existing reports, observations, and performance data. Start with Excel or CSV, or capture new reports in Verdant.
Start with the data you already have.→Connect differently worded reports into recurring issue families across processes and sites. Keep every finding linked to its source.
Inspect the original evidence.→Rank loss cases by estimated exposure, recurrence, trend, and evidence. Give the team a clear starting point for investigation.
Priorities for investigation, with evidence.→Track the intervention, owner, and outcome. Review recurrence and performance, then retain what worked in Industrial Memory.
Keep the lessons, including failed attempts.Explore the operation, inspect the biggest recurring losses, and follow actions through to their outcomes. Select any process to begin.
See where operational loss concentrates—and what connects it.
Solid arrows show process flow. Dotted links show related evidence—not proven causation. Select a process to inspect the context →
Understand the patterns behind the losses.
86 related records · 4 source systems
Recommended investigationCompare pre-start checklist adherence with restart delay across Lines 3 and 4.
Turn investigation into measurable improvement.
| Issue / opportunity | Process & owner | Status | Value |
|---|---|---|---|
| ManufacturingA. Keller | Investigating | €184k / monthEstimated exposure | |
| SuppliersM. Russo | Intervening | €92k / monthPotential benefit | |
| Quality ControlS. Weber | €76k / monthPotential benefit | ||
| PackagingJ. Costa | Intervening | €64k / monthPotential benefit | |
| PackagingL. Novak | Verified | €31k / monthVerified improvement | |
| Customer DeliveryP. Meyer | Inconclusive | €18k / monthPotential benefit | |
| ReceivingE. Fischer | No improvement | €22k / monthEstimated exposure |
Evidence review is open. No root cause has been confirmed.
Owner: A. KellerEstimated exposure, potential benefit, and verified improvement remain separate.
Keep your existing systems. Start with focused imports and native reporting, then add connections where they help explain operational loss.
Keep source systems in place. Verdant connects the relevant evidence, context, and learning.
Connect different names for the same assets, processes, and products. Keep source references attached so every finding can be inspected.
Start with one site or operational area. Turn existing reports and performance data into a prioritized picture of recurring loss.
A practical starting point for your improvement team:
Begin with one site or a focused operational area. Agree the operating question, available evidence, review participants, and success criteria.
Use existing issue records and available performance data. Preserve source provenance and make evidence gaps visible.
Identify what repeats, where it appears, what supports it, what it may cost, and what deserves investigation next.
Use native reporting after the initial analysis. Where history is insufficient, establish a 90-day reporting baseline for meaningful issue mining.