Proof & methodology
Show me
the math.
WERISCO is new. So instead of logos and testimonials we can't back up, this page shows you exactly how every number on this site is produced, and invites you to test it on your own data.
- Cost calculations with every formula
- Product demonstrations you can click
- Illustrative scenarios, labeled
- Our exposure and accuracy methodology
- Benchmarks with named sources
- Invent customers, logos or testimonials
- Present a simulation as a result
- Claim certifications we don't hold
- Present a file export as a live connection
- Hide the formula behind a number
The homepage example, line by line.
- aStockoutsLost margin, penalties and recovery on orders that couldn't ship= stockout cost, per year82
- bExcess inventoryCarrying cost on stock above target cover= $8.0M × 6% excess × 20% carrying96
- cExpedite freightPremium transport to recover late supply= expedite invoices, per year36
Illustrative example for a $60M manufacturer with $8M of inventory. Not a customer result. Every input and rate is editable in the calculator.
Run it with your numbersMethodology · exposure
How an exception gets its $ number.
Exposure is an estimate, not a forecast of certainty. Every component is traceable to records in your data.
Σ (open order value × gross margin %) for orders the exception reaches before recoveryContractual service fines on affected customer orders (from your terms)Expedite freight + overtime + spot-buy premium, from your historical ratesExcess value × carrying rate × days held ÷ 365A + B + C (+ D where stock is held)Data & forecast methodology
Measured against baselines, not adjectives.
Data quality first
Every record is mapped to one model. Unit mismatches, impossible values and duplicates are quarantined with a reason, never silently used.
Forecast accuracy
Per-SKU models are back-tested on a hold-out window at the planning horizon and reported as wMAPE, bias and skill versus naïve and seasonal-naïve forecasts.
Recommendations
Options are compared on cost, time and residual risk. Your team approves. Estimate and outcome are both logged so accuracy of the recommendations themselves is measurable.
Benchmarks with sources
Why this matters, from the research.
Survey respondents reported material supply-chain disruptions lasting a month or longer every 3.7 years on average.
Source: McKinsey Global Institute, “Risk, resilience, and rebalancing in global value chains”, August 2020Carrying cost rates in the cost calculator are planning assumptions, not benchmarks. They are editable on the page. The audit does not estimate savings.
Product demonstration
The method is in the product.
Risk Impact in the real product: every exposure line shows its formula and record count. Risks that can't be quantified from your data are labeled, never guessed.
Illustrative scenarios
Simulations, labeled as simulations.
A late casting order, caught before the housings ran out.
A late jar order, seen before the promotion started.
One SKU list, two DCs, $38K of imbalance.
Supply chain audit
The only proof that matters is your data.
A 20-minute call and two file exports: stock by item and open orders. You see the inventory and order value exposed. No integration, no savings estimate, and an NDA if you need one.