Walk me through your background + your path into DC / fulfillment network design.

What it tests: Story arc - quantitative / analytical training + operator exposure + concrete DC or FC modeling work. Interviewers screen for candidates whose path lands on warehousing network design as deliberate, not generic supply-chain analytics.

Tell me about a DC or FC design / capacity / automation project you've owned end-to-end.

What it tests: Modeling rigor + capital + operator lens. Can the candidate walk problem framing -> data -> model -> recommendation -> stakeholder handoff cleanly. WHY: warehousing network roles sit between strategy and capital; interviewers want both modeling and operator credibility.

Why warehousing / fulfillment network design vs broader 3PL design or shipper-side supply chain?

What it tests: Authentic alignment - DC + FC focus, operator + capital stakes, automation depth vs broader brokerage / forwarding work.

Why network planning specifically vs warehouse operations, industrial engineering, or commercial roles?

What it tests: Specificity. Generic 'I like analytics' fails.

What it tests: Real homework - site footprint + automation + recent moves + tooling - not 'great brand'.

What's your read on our network + customer footprint?

What it tests: Industry literacy - site footprint, customer concentration, recent moves, where the design team likely focuses.

Tell me what you understand about our network design tooling + automation posture.

What it tests: Engineering maturity awareness - in-house solver, named tool stack, automation footprint, recent investments.

Walk me through how you'd design or redesign a DC / FC network.

What it tests: Modeling fluency + capital instinct - can the candidate frame problem, choose tools, identify data needs, propose scenarios, quantify service-cost trade-offs.

Network Planning interview prep.

Trained on network designer / supply chain engineer / DC strategy / fulfillment network architect / industrial engineer interviews across retail DC operators, e-commerce fulfillment networks, contract logistics, cold-storage, and parcel-adjacent fulfillment.

What interviewers look for

Can the candidate frame a DC / FC network design problem - objective, constraints, decision variables, data needs?
Do they understand service-cost trade-off curves - how adding or removing nodes shifts cost + service?
Are they fluent in cube + throughput economics - velocity + dim weight + slotting + flow-path implications?
Can they build an automation business case - capex, opex savings, payback, IRR, sensitivity?
Do they speak credibly to peak + capacity planning - design throughput vs nameplate, surge, contingency?
Are they grounded in operator reality - WMS, MHE, labor, safety, go-live risk on any design they propose?
Can they speak to sustainability + scope-3 + design levers - mode mix, load fill, automation energy?
Long-game fit - analyst / senior / manager / director / VP network design or fulfillment strategy trajectory?

Behavioural questions to expect

Walk me through your background + your path into DC / fulfillment network design.
What it tests: Story arc - quantitative / analytical training + operator exposure + concrete DC or FC modeling work. Interviewers screen for candidates whose path lands on warehousing network design as deliberate, not generic supply-chain analytics.
Tell me about a DC or FC design / capacity / automation project you've owned end-to-end.
What it tests: Modeling rigor + capital + operator lens. Can the candidate walk problem framing -> data -> model -> recommendation -> stakeholder handoff cleanly. WHY: warehousing network roles sit between strategy and capital; interviewers want both modeling and operator credibility.
Why warehousing / fulfillment network design vs broader 3PL design or shipper-side supply chain?
What it tests: Authentic alignment - DC + FC focus, operator + capital stakes, automation depth vs broader brokerage / forwarding work.
Why network planning specifically vs warehouse operations, industrial engineering, or commercial roles?
What it tests: Specificity. Generic 'I like analytics' fails.
Why this firm?
What it tests: Real homework - site footprint + automation + recent moves + tooling - not 'great brand'.
What's your read on our network + customer footprint?
What it tests: Industry literacy - site footprint, customer concentration, recent moves, where the design team likely focuses.
Tell me what you understand about our network design tooling + automation posture.
What it tests: Engineering maturity awareness - in-house solver, named tool stack, automation footprint, recent investments.
Walk me through how you'd design or redesign a DC / FC network.
What it tests: Modeling fluency + capital instinct - can the candidate frame problem, choose tools, identify data needs, propose scenarios, quantify service-cost trade-offs.

Technical concepts to master

Network design fundamentals

Greenfield vs brownfield: Greenfield = optimal network from scratch (ignore existing assets); brownfield = constrained by current leases, labor markets, automation in place.
MILP + heuristic solvers: Network design typically formulated as Mixed-Integer Linear Programming (MILP); large problems solved with commercial solvers (CPLEX, Gurobi) or heuristics (genetic, simulated annealing).
Tool stack: Industry-standard network design tools: Coupa Supply Chain Guru (formerly Llamasoft), OptiLogic Cosmic Frog, AIMMS, AnyLogistix; simulation: AnyLogic, FlexSim; many shops also run custom Python / Pyomo / OR-Tools.
Service-cost trade-off curve: Plotting total cost vs service level (% population within next-day, % within 2-day) across network configurations - the Pareto curve guides executive trade-off conversations.

Cube + throughput economics

Cube utilization: % of available storage cube actually filled with inventory - drives space cost per unit + DC sizing.
Dim weight + parcel economics: Parcel carriers bill on the greater of actual weight or dimensional weight (length x width x height / divisor); drives packaging + cube discipline.
Throughput vs nameplate: Design throughput (what you build to) vs nameplate (vendor spec under ideal conditions) vs sustainable throughput (peak day-after-day) - typically 60-80% of nameplate.
Velocity slotting + flow path: A-B-C velocity slotting + flow-path design (forward pick zone, reserve, replenishment cycle) drives picker travel + UPH.

Automation strategy + vendor map

Automation archetypes: AS/RS (dense storage + retrieval, crane-based), GTP shuttle (AutoStore, robotic cube storage), AMRs (Locus, 6 River, Geek+), conveyor + sortation, robotic arms (pick + place).
Capex vs flex trade-off: Fixed-infrastructure automation (AS/RS, conveyor) is lowest opex per unit at scale but rigid; AMRs are flexible but higher per-unit opex.
Ramp curve realism: Time from go-live to design throughput; AS/RS + conveyor 6-12 months, AMRs 3-9 months, robotic arms 12-24 months for new SKU coverage.
Integration debt: WMS / WCS / MHE integration is typically 15-25% of hardware capex + highest source of go-live delay; vendor lock-in via proprietary WCS a strategic risk.

Sustainability + scope-3 in network design

Scope-3 logistics emissions: Customer scope-3 categories 4 + 9 (upstream + downstream transportation + distribution) - DC / FC operators own the data + lever set.
Network density + carbon: Forward-deployed FCs reduce parcel transit miles + carbon AND service time; consolidation lowers fixed-emission overhead but extends line-haul.
Building + energy levers: DC roof solar, LED + smart lighting, EV charging infrastructure, building certifications (LEED, BREEAM) - increasingly part of design briefs.
Load + cube optimization: Higher cube + weight utilization, reduced empty miles, regional consolidation, multi-stop routing - all reduce emissions per unit shipped.

Practical drills

A 600K sq ft e-com FC is evaluating a GTP shuttle system. Capex is $40M (hardware + integration + facility). It would reduce 80 pickers (out of 200) at a fully-loaded $55K / yr each. Maintenance + energy adds $1.5M / yr. Ramp curve is 12 months to full throughput. Walk through simple payback, year-1 NPV impact, and the IRR view. Show your numbers.
A retail customer runs 8 regional DCs across North America serving 2,500 stores. They're asking whether to consolidate to 4 mega-DCs to save fixed cost + invest in automation. They have a 2-day standard service spec. How would you approach the study and what's your initial hypothesis?
An e-com pure-play with a single 1M sq ft FC in the Midwest is exploring forward-deployed FCs to offer same-day delivery in top metros. They have $200M capex envelope over 3 years. Walk me through how you'd scope the study and what your initial network framework would be.

Smart-question anchors

Network design team org - centralized strategic vs embedded with operations or customer teams
Tool stack maturity - in-house solver vs commercial, simulation tools, AI / ML investments
Automation strategy - AS/RS, AMRs, GTP, named vendor partnerships, capital deployment cadence
Site footprint + growth - mega-DC strategy, forward-deployed FCs, geographic expansion
Sustainability + scope-3 - public commitments, building certifications, mode-shift programs

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