Would you fairly put one huge storage exterior a cheap city, or ten smaller ones near impatient customers? That sole choice can quietly decide shipment speed, inventory levels, freight cost, hiring difficulty and equal whether the endeavor example works.
- Facility location method choosing anywhere to location plants, warehouses, stores or assistance nodes to assist petition at the finest total cost-service-risk balance.
- The correct location is not the cheapest rent. It is the finest total landed cost following transport, inventory, labour, taxes, utilities, assistance levels and risk.
- Key factors autumn into four buckets: demand proximity, supply access, operating economics and risk or regulation.
- Common methods: factor rating for qualitative comparison, load-distance for transport effort, centre of gravity for geographic placement and cost-volume analysis for fixed versus changeable disbursal trade-offs.
- The center trade-off is simple: additional nodes normally enhance speed but lift fixed disbursal and inventory complexity.
- Interview answer structure: explain objective, map petition and constraints, shortlist factors, choose method, difference scenarios, propose alongside risks.
- The biggest error is optimizing one apparent cost, normally rent or freight, during ignoring assistance flat and network-wide cost.
Big Picture: Facility Location Is a Network Decision, Not a Real-Estate Decision
A facility is a node in a provision sequence network. Its location affects inbound supply, outbound delivery, inventory pooling, labor access, capacity, resilience and client experience. So the inquiry is not “Which location is cheapest?” The inquiry is “Which network scheme finest supports the strategy?”
The Four Factors That Drive Facility Location
Think of all facility location issue as a scoring exercise throughout four aspect families. The weights alter by industry: a quick-commerce dreary shop overweights client proximity; a alloy factory overweights raw matter and utilities; a financial institution branch overweights catchment petition and accessibility.
The Core Trade-Off: Cost Versus Service
Facility location is complete of trade-offs. Centralising inventory in one or two nodes improves measure and inventory pooling, but may dilatory deliveries. Decentralising into many nodes improves client proximity, but raises fixed cost, coordination attempt and duplicated safety stock. This is why location decisions are normally evaluated through scenarios, not single-point answers.
This additionally connects immediately to inventory policy. Once a resolute adds nodes, it must decide what inventory all node carries, how it replenishes, and what assistance flat it promises. If you desire to fortify that link, revise setting inventory guideline for a multi-product business following this topic.
A 2x2 Matrix: Four Facility Location Archetypes
Use this matrix whenever an interviewer gives you an open-ended location problem. First ask: does the endeavor need to be near to demand? Second ask: is there a powerful disbursal advantage in a particular region? The answer points to the archetype.
Methods to Evaluate Facility Location
In interviews, you do not need to build an advanced optimizer. You need to cognize which method fits which problem, what it measures, and what its blind spots are.
Worked Example: Centre of Gravity in 90 Seconds
Suppose a business must choose a storage location to assist three petition zones. Each area has map coordinates and monthly shipment volume. The centre-of-gravity method estimates a location that balances valued demand.
Formula: X* = Σ(load × X) / Σ(load), and Y* = Σ(load × Y) / Σ(load).
X* = (100×2 + 200×6 + 300×10) / 600 = 7.33. Y* = (100×8 + 200×4 + 300×6) / 600 = 5.67.
The approximate location is hence (7.33, 5.67). In a genuine decision, this is lone the archetypal cut. You would afterward inspect roads, district availability, labour, taxes, lease cost, capability and risk.
Metrics to Compare Location Options
There is no worldwide “good” figure for facility location metrics since a pharma cold-chain network, an car factory and a market dark-store network have distinct assistance promises. In interviews, define the mark first, afterward difference options against it.
Definitions You Should Be Able to Say Clearly
- Facility location: choosing anywhere to location functioning nodes to encounter petition at the finest cost, assistance and hazard balance.
- Centralised distribution: serving many markets from small accommodation to acquire measure and inventory pooling.
- Decentralised distribution: serving markets through additional accommodation located nearer to customers.
- Total landed cost: the complete disbursal of getting a merchandise to the customer, including facility, freight, handling and inventory costs.
- Service coverage: the portion of petition that can be served inside the promised period or extend standard.
- Centre of gravity method: a weighted-average method used to evaluation a location near the demand-weighted centre of shipments.
Case Study: Zepto and the Dark-Store Location Logic
Zepto shows how facility location becomes the endeavor example whenever the commitment is ultra-fast market shipment in compact Indian cities.
Zepto’s example depends on placing small fulfilment nodes, commonly called dreary stores, near adequate to compact residential catchments to create fast shipment operationally possible. The strategic issue is extremely distinct from choosing one national warehouse. Zepto must decide micro-locations: which neighbourhoods validate a dreary store, how much assortment all should hold, and how to replenish them without choking the network.
The primary driver is petition density inside a tight shipment radius. A dreary shop lone plant whenever adequate nearby orders can shield rent, labour, passenger capability and inventory holding cost. The supporting drivers are assortment discipline, replenishment reliability, passenger availability, local real-estate fit and technology-led command batching or routing.
The lesson: in quick commerce, facility location is not a back-office supply-chain choice. It is the client commitment converted into geography. The winning network is not merely “more dreary stores”; it is the correct density of nodes, alongside disciplined assortment and replenishment economics.
How AI Changes Facility Location
AI is making facility location small fixed and additional evidence-led. The decision is motionless strategic, but the data inputs are richer and the circumstance evaluation is faster.
- Demand sensing becomes granular: ML models can evaluation petition by pin code, hour, weather, celebration period, receptacle category or client cohort. This helps decide whether a neighbourhood can assistance a store, storage or micro-fulfilment node.
- Digital twins enhance circumstance testing: teams can simulate “what if we add one local warehouse?” or “what if energy disbursal rises?” before committing capital.
- Routing and replenishment data nourish rear into location: shipment period predictions, unsuccessful shipment clusters and stockout patterns can disclose that a current node is wrongly placed. For the inventory flank of this loop, revise using AI for inventory optimisation and replenishment.
Use ChatGPT or Claude to create a location shortlist: paste a case prompt, define petition zones, ask for factors, weights, risks and a factor-rating table. Then difficulty the output by asking, “Which assumptions would alter the recommendation?”
Interview Relevance
“A D2C brand wants to develop from one storage to three. How would you decide the locations?”
Use the expression “total network disbursal at the required assistance level”. It signals that you comprehend the two operations and endeavor strategy.
Common Mistake
Optimizing the cheapest location alternatively of the finest network. Candidates frequently choose the lowest rent or lowest freight choice and halt there. That expenses them since facility location decisions power inventory, assistance levels, resilience, labour, capability and client experience. Fix: continually difference options on total landed cost, assistance safety and hazard together.
