Run your supply chain on causes, not guesses.
Ergodic builds a working model of your supply chain from ERP, warehouse and planning data. Find what's really driving failures, test the fix before you make it, and act before the next disruption lands.
$270M
failures diagnosed
Weeks to minutes
for root cause
10%+
better launch forecasts
$1M+
saved a year
The real causes stay hidden.
Failures get a generic label.
Most late orders are tagged "capacity constraint", which hides the chain of events that actually caused them.
Diagnosis takes weeks.
Senior operators spend weeks in data and war rooms before anyone can act.
Plans are fixed months ahead.
Long lead times force irreversible decisions on forecasts that are argued over, not tested.
Trace the cause, then test the fix.
Ergodic works backwards from a failure to its true root cause, then simulates each fix forward so you act on the one that works.
Trace it back to the real cause.
Test every fix before you commit.
Fix the ingredient supply, not the line. On-time delivery recovers for the lowest cost.
How Ergodic helps.
Ground
Data from ERP, warehouses and manual files unified into one end-to-end model of your supply chain, in weeks.
Explain
Automated five-whys traces every failure from symptom to root cause, by plant, product or region.
Simulate
Test corrective actions, allocations and forecasts against the model before you change the plan.
Reconcile
Forecasts stay coherent from SKU and site up to category, region and enterprise.
Learn
Every action is measured against what actually happened, so the model improves with each cycle.
What it has delivered.
Live in Fortune 500 companies. Operations teams use it to trace why service fails and to plan supply when the history is thin.
$270M in hidden OTIF failures diagnosed
A top 3 global consumer packaged goods leader, across hundreds of facilities and thousands of SKUs.
Problem
About 80% of OTIF failures were tagged "capacity constraint". Diagnosing a major failure took weeks or months.
Solution
An AI-driven root cause engine connected SAP, Snowflake and Power BI data and traced failure chains automatically, such as ingredient delays triggering line changeovers.
Results
Hundreds of hidden failure chains uncovered, root cause analysis cut from weeks to minutes, and a clear roadmap for fixes and investment.
$270M
failure drivers uncovered
$30M
clawback value identified
10% more accurate forecasts for new product launches
A Fortune 100 global technology conglomerate's $3B infrastructure division.
Problem
Four-month lead times and no history for new products. Forecasts were negotiated between Sales and Supply Chain, causing stockouts and excess stock.
Solution
A causal forecasting engine modelled adoption before the first unit shipped. Sales and Supply Chain tested assumptions together, from revenue targets down to part-level supply.
Results
Faster, higher-confidence launch decisions and protected working capital.
10%+
better launch forecast accuracy
5 to 15%
less launch inventory risk
$1M+ a year saved in reverse logistics
A top 5 global automotive manufacturer running just-in-time production.
Problem
There was no visibility of critical reusable packaging across the supplier network, which led to shortages, emergency freight and spreadsheet reconciliation.
Solution
Real-time visibility of packaging flows, a shared hub for logistics, procurement and suppliers, and predictive redistribution before shortages hit.
Results
Emergency packaging spend eliminated, teams moved from firefighting to forward planning, and supplier accountability enforced with evidence.
$1M+
annual cost avoidance
30+ hours
a week back
$270M
failures diagnosed
Weeks to minutes
for root cause
10%+
better launch forecasts
$1M+
saved a year
Bring us an operations decision.
We'll show you the real cause and the fix that works, tested on a model of your supply chain.
Talk To An Expert