Subject Matter Expert — Storage & Warehouse Network Optimisation

Engagement: Contract / consultant Base: India (metro base of your choice), with regular travel to Andhra Pradesh — Vijayawada/Amaravati and district locations

About the role

Andhra Pradesh State Civil Supplies Corporation (APSCSCL) stores and distributes rice and other essential commodities through a network of rice mills, buffer godowns, mandal-level stock points and roughly 29,800 fair price shops. Storage today is planned manually, with no optimisation logic anywhere in the chain.

We are building a decision intelligence platform to change that. You will own the storage side of the problem: where stock sits, in whose warehouse, at what cost, and for how long.

What you will own

Warehouse selection and consolidation. Stock is held across private, SWC/CWC-managed and SWC-owned warehouses, each with different rental rates, and with Handling & Transportation (H&T;) rates that vary warehouse by warehouse. Two godowns of identical capacity are not interchangeable. You will build the cost model that makes those differences visible, the logic that selects between warehouses, and the case for releasing warehouses running below viable utilisation.

Mill-to-godown mapping. Which buffer godown each mill's custom-milled rice is delivered to is decided by hand today. It sits at the pivot of the chain and drives storage cost directly. This is among the highest-leverage decisions in the network.

Storage economics and dwell. Storage duration is a cost driver, not a residual. You will model rental × duration, build the logic that reduces idle storage, and define what good dwell looks like by commodity and season.

Capacity and utilisation modelling. Godowns are structured as blocks → stacks → consignments,



with one commodity per stack. You will model that structure faithfully enough that recommendations are physically executable, not just arithmetically attractive — including the difference between sanctioned and genuinely usable capacity.

Monthly stock positioning. How much of each commodity should sit where, month by month, given annual district requirements that must be protected before any surplus is released.

Explainability. Warehouse hiring in this environment is subject to pressures that are not purely economic. A consolidation recommendation that cannot be defended line by line will not be acted on. Every output you design must carry its own arithmetic.

Responsibilities

- Translate storage operations into a formal model: entities, constraints, cost functions, decision variables
- Specify and validate optimisation formulations for warehouse selection, consolidation, stock positioning and dwell reduction
- Define the storage portion of the domain model alongside the data engineering team
- Interrogate source data — warehouse masters, rental and H&T; schedules, occupancy, stock ledgers — and identify early what is wrong, missing or unusable
- Establish the storage cost baseline: cost per tonne stored, utilisation by godown, average dwell, and the consolidation prospect in ₹




- Spend time with district and godown staff to understand what actually happens versus what the SOP says
- Pressure-test model output against operational reality before it reaches a client screen
- Design the rationale layer so recommendations survive contest
- Support client workshops and steering reviews

Must have

- 10+ years in warehousing, inventory or storage network design, with genuine depth rather than adjacent exposure
- Direct experience of bulk or agri-commodity storage — food grain, FCI/CWC/SWC or state warehousing, agri-warehousing, or comparable bulk storage at scale. Retail or e-commerce DC experience alone is not a substitute.
- Working command of optimisation. You can formulate a storage or facility-location problem, reason about its constraints, judge whether a model's output is sensible, and hold your own with an OR specialist. You do not need to write solver code.
- Cost modelling fluency — rental structures, handling charges, carrying cost, and the economics of hired versus owned space
- Comfort with messy public-sector data, and the patience to work through it
- Credibility with field staff and senior officials alike, often in the same week
- Willingness to travel to Andhra Pradesh regularly, including to godowns and district offices

Strongly preferred

- Experience with Indian public distribution, food grain procurement or state civil supplies
- Familiarity with warehousing contracts, H&T; rate structures and government storage norms
- Exposure to knowledge graph or ontology-based modelling
- Python and data analysis capability sufficient to explore data independently
- Prior work on a decision-support product rather than a one-off consulting study
- Telugu language ability (useful, not required)

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