Four browser-based diagnostic tools powered by AI. Check inventory health, audit forecast accuracy, simulate supply chain risks, and optimize cost, profit, or volume across 50 SKUs — all free, no signup, no data leaves your browser.
Upload your inventory CSV and get a comprehensive 10-dimension health score with actionable recommendations.
Upload demand data to auto-detect patterns, select the best forecasting model, and get MAPE and bias analysis.
Bayesian risk engine with Monte Carlo simulation. Model disruptions, compute VaR, and build resilience strategies.
LP/NLP solver for production (volume maximization), transport (cost & distance minimization), and procurement (spend minimization). Mode-specific data, up to 50 items.
Supply chain inefficiency costs businesses 15–25% of annual revenue through excess inventory, poor forecasts, unquantified risk, and sub-optimal allocation. Mathnal's free diagnostic suite gives you the data to fix it — without expensive software licenses or consultants.
ABC-XYZ classification identifies which SKUs drive 80% of revenue (A items) versus which have erratic demand (Z items). Combined with safety stock calculation using the statistical formula SS = Z × √(LT × σd² + d² × σLT²), it quantifies exactly how much buffer you need at your target service level. The 10-dimension health score covers stock coverage, turnover ratio, aging analysis, demand variability, carrying cost efficiency, fill rate, reorder point accuracy, dead stock percentage, order cycle performance, and overall supply reliability.
→ Launch Inventory Health CheckDemand forecasting accuracy directly impacts inventory costs, service levels, and production planning. The audit auto-detects trend (linear, exponential, piecewise), seasonality (additive vs multiplicative), and variability classification (smooth, intermittent, lumpy, erratic). It then runs 7+ models — ARIMA, ETS, Holt-Winters, Prophet, Croston, SBA, and naïve benchmarks — selecting the best model by MAPE. Error decomposition separates bias (systematic over/under-forecasting) from noise (random variation), while tracking signal alerts you when forecasts drift persistently.
→ Launch Forecast Accuracy AuditBayesian risk analysis updates prior probability estimates with new evidence using likelihood ratios. The SCRRS tool models 45+ disruption scenarios across geopolitical, climate, supplier failure, logistics delay, demand shock, quality failure, cyber, regulatory, and financial risk categories. Monte Carlo simulation runs 10,000+ iterations to build a loss distribution, from which Value-at-Risk (VaR) at 95% confidence quantifies worst-case financial exposure. The resilience score rates your supply chain's ability to absorb and recover from disruption on a 0–100 scale.
→ Launch Risk SimulatorMathematical programming optimizes resource allocation across production, transport, and procurement decisions. The LP solver uses coordinate descent to find the global optimum for proportional cost structures. The NLP solver handles economies of scale using a log-discount factor c(x) = c₀(1 − 0.02·ln(1+x/100)). Five objectives — cost minimization, distance minimization, volume maximization, profit maximization, and revenue maximization — with six global constraints (budget, capacity, service level, distance, weight, iterations) and per-SKU bounds. Outputs include optimal allocation table, constraint utilization chart, sensitivity analysis with shadow prices, and LP formulation matrix.
→ Launch Optimization ToolOur diagnostic tools give you the insights. Our consulting team helps you act on them. Talk to a supply chain AI specialist.
Three free AI-powered tools to diagnose your supply chain health. Want a quick guided tour of what each tool does?
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