What ROI can I expect from a Mathnal supply chain AI engagement?

Typical Mathnal engagements have delivered 12-38% reductions in core supply chain costs or errors: MAPE down 25-38%, safety stock down 18-28%, transport cost down 8-12%, RFQ cycle time down 60-70%. ROI is usually realised within 6-9 months of go-live.

Does Mathnal publish detailed client names?

Mathnal anonymises all case studies by industry, geography and scale to respect client confidentiality. We are happy to introduce qualified prospects to a relevant reference client under mutual NDA.

What industries has Mathnal worked with?

Mathnal Analytics has delivered supply chain AI projects across FMCG, pharma, 3PL logistics, automotive, apparel, e-commerce, chemicals, electronics, and higher education capstone partnerships. We work with companies of all sizes — from ₹50Cr regional brands to ₹5,000Cr+ enterprises.

Supply Chain AI Case Studies — Quantified ROI & Outcomes

FMCG · ₹1,200Cr · India

From Spreadsheet Forecasts to ML-Driven Demand Sensing

Challenge

A multi-state FMCG distributor was running monthly Excel-based forecasts with MAPE hovering at 42%. Stockouts were 8% in fast-moving SKUs, while slow-movers carried 11 months of dead stock.

Approach

Mathnal deployed a hierarchical ML stack: ETS & SARIMA baselines, XGBoost with calendar + price features, LSTM ensemble for top-50 SKUs. Forecast Value Added (FVA) used to audit planner overrides.

-38%

MAPE

-65%

Stockouts

XGBoost LSTM FVA Python

Pharma · ₹3,400Cr · Multi-site

Bayesian Safety Stock Across 4,200 SKUs

Challenge

A pharma manufacturer carried safety stock based on rule-of-thumb (2× average demand × LT). With volatile API supply and 4,200 SKUs, working capital had ballooned by ₹38Cr in 18 months.

Approach

Multi-echelon inventory optimisation (MEIO) with Bayesian posterior P(stockout) per SKU. (s,S) policies for A-items, (R,Q) for B/C, lean make-to-order for slow-Z. Service-level differentiation by ABC class.

-28%

Safety stock

+4pp

Service level

Bayesian MEIO ABC-XYZ

3PL Logistics · 220 vehicles · India

VRPTW Routing & Live Dispatch Optimisation

Challenge

A 3PL operator was dispatch-planning manually with 220 trucks across 5 hubs. OTIF was 81%, route utilisation 64%, empty backhaul 27%.

Approach

VRPTW formulation with OR-Tools, time-windows, vehicle-capacity and driver-hour constraints. Live re-optimisation every 2 hours via ETA feedback. Backhaul matching engine for return-trip loads.

-12%

Transport cost

+9pp

OTIF

VRPTW OR-Tools Live ETA

Auto Parts · OEM Tier-1 · India

Agentic AI for RFQ Negotiation & Award

Challenge

A Tier-1 auto-parts manufacturer was running 1,400+ RFQs/month with 3-supplier-quote rules. RFQ cycle averaged 11 days, supplier scoring was subjective, award decisions inconsistent.

Approach

LangGraph-based agentic AI for RFQ orchestration: agents handle supplier outreach, quote parsing, scoring on 7 dimensions, scenario simulation. Human-in-the-loop approval on awards > ₹10L.

-70%

RFQ cycle

-6.2%

Purchase cost

LangGraph Agentic AI Procurement

Apparel Retail · ₹680Cr · 142 stores

End-to-End S&OP Transformation

Challenge

An apparel brand ran disconnected demand, supply and finance plans. Markdown losses were 14% of revenue, end-of-season stock 31% of starting inventory.

Approach

Built unified S&OP cadence with consensus demand (ML + commercial overrides), supply allocation MIP, financial reconciliation. Power BI executive S&OP dashboard with scenario simulation.

+24pp

Forecast accuracy

-9pp

Markdown losses

S&OP MIP Power BI

E-Commerce · 4 DCs · India

Warehouse Slotting & Pick-Path Optimisation

Challenge

Peak-season pick times at 4 fulfilment centres hit 11 minutes per order. SLA breaches were costing ₹2.4Cr/month in escalations and refunds.

Approach

Slotting optimisation by velocity + correlation. S-shape and largest-gap pick routes via shortest-path on aisle graph. Cluster picking for multi-item carts. WMS rule engine refresh.

-31%

Pick time

+18%

Throughput

Slotting VRP WMS

Specialty Chemicals · ₹1,800Cr

Multi-Echelon Inventory Optimisation

Challenge

Specialty chemicals manufacturer with 3-tier network (plants → CFAs → distributors). Tier-level inventory was being managed independently, with 5.8 months of total system inventory.

Approach

End-to-end MEIO with stochastic lead times. Joint optimisation of plant-CFA-distributor safety stock. Pyomo + Gurobi solver, weekly refresh. Service-level guard rails per business segment.

₹14Cr

WC freed

-1.6mo

Inv days

MEIO Pyomo Gurobi

Electronics · ₹4,500Cr · Multi-country sourcing

Bayesian Supply Chain Risk & VaR

Challenge

An electronics OEM faced semiconductor lead-time spikes (12 → 38 weeks). With 11 single-source critical components, exposure was material but unquantified.

Approach

Bayesian risk modelling per supplier × component, Monte Carlo simulation for portfolio VaR, mitigation optimiser (dual-source, safety stock, contracts) under cost cap. Quarterly refresh.

-42%

Portfolio VaR

-31%

CVaR (tail)

Bayesian Monte Carlo VaR

Higher Education · CSCOP Cohort #3

CSCOP Capstone — 14 Industry Projects in 12 Weeks

Challenge

A B-school partnered with Mathnal to upskill 32 working executives on supply chain optimisation. Programme had to combine theory, Python labs and industry-grade capstones.

Approach

12-week CSCOP curriculum: LP/MIP/NLP, VRP, network design, Bayesian risk. 4 capstone tracks (FMCG distribution, airline spares, e-commerce fulfilment, supplier risk), each presented to industry panel.

14

Industry projects

94%

Placement / promotion

CSCOP Training Capstone

Supply Chain AI in the Real World — Quantified ROI Across 9 Engagements

Hard numbers, not anecdotes

From Spreadsheet Forecasts to ML-Driven Demand Sensing

Bayesian Safety Stock Across 4,200 SKUs

VRPTW Routing & Live Dispatch Optimisation

Agentic AI for RFQ Negotiation & Award

End-to-End S&OP Transformation

Warehouse Slotting & Pick-Path Optimisation

Multi-Echelon Inventory Optimisation

Bayesian Supply Chain Risk & VaR

CSCOP Capstone — 14 Industry Projects in 12 Weeks

Aggregate ROI across these 9 engagements

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