Case: Choosing Between Two Distribution Models
A customer in Jaipur taps “buy now” at 8:30 pm. The company now faces a hidden design choice: ship from one national warehouse and save inventory, or stock closer to the customer and promise faster delivery.
That is the heart of a distribution-model case. The visible question is “Which model is cheaper?” The real question is “Which model creates the best service at the lowest total system cost, with acceptable risk?”
- Distribution model means how goods move from supply points to customers: direct, distributor-led, marketplace, warehouse-led, hub-and-spoke, dark-store or hybrid.
- Never compare only freight cost. Compare total landed cost, service level, working capital, control, scalability and risk.
- Centralised models usually reduce inventory duplication but increase delivery lead time and long-haul dependency.
- Decentralised models usually improve speed and customer experience but increase inventory, fixed cost and coordination complexity.
- The best interview answer uses a decision funnel: customer promise - demand pattern - product constraints - economics - risk - recommendation.
- Use numbers early: cost per order, OTIF, fill rate, inventory turns, lead time and damage or return rate.
- The winning recommendation is often not Model A or Model B everywhere, but a segmented hybrid: fast movers near demand, long-tail items centralised.
Big Picture: Distribution Is a Service Promise Wearing a Cost Mask
A distribution choice is not just a logistics route. It decides how quickly the customer receives the product, how much inventory the business must hold, how much control it has over the experience, and how fragile the network becomes when demand spikes.
Core Explanation: The Framework to Choose Between Two Models
Use this when the case says: “A company is deciding between direct distribution and distributors,” “Should it open regional warehouses?” or “Should it fulfil through dark stores or a central warehouse?”
The cleanest structure is the 6C framework. It keeps your answer broad enough for strategy and operational enough for an operations interviewer.
The 6C Distribution Decision Framework
The point is not to “list factors.” The point is to use each factor to decide where one model clearly wins, where the other wins, and where a hybrid is required.
Model A vs Model B: The Classic Trade-Off
Most cases reduce to one of these choices: centralised distribution versus decentralised distribution. The labels may change, but the economics remain similar.
The Metrics You Must Use in the Case
If you do not quantify the choice, your recommendation sounds like a preference. Use 4-6 metrics and explicitly say which model wins on each.
Notice the phrase “at the same service level.” A model that is cheaper because it delivers late is not cheaper - it has changed the promise.
Worked Example: Central Warehouse or Regional Hubs?
Assume an appliance brand must serve 10,000 monthly orders. It is comparing two models.
Model A monthly cost = ₹8,00,000 + 10,000 × (₹40 + ₹180 + ₹30) = ₹33,00,000.
Model B monthly cost = ₹18,00,000 + 10,000 × (₹55 + ₹95 + ₹20) = ₹35,00,000.
On current volume, the central warehouse is ₹2,00,000 cheaper per month. But Model B delivers two days faster. The recommendation depends on whether the extra speed creates enough value through higher conversion, lower cancellations, better reviews or premium positioning.
The break-even volume is found by comparing fixed-cost gap and variable-cost saving:
Extra fixed cost = ₹18,00,000 - ₹8,00,000 = ₹10,00,000. Variable saving in Model B = ₹250 - ₹170 = ₹80 per order. Break-even volume = ₹10,00,000 / ₹80 = 12,500 orders per month.
“At 10,000 orders, I would choose Model A if price is the dominant promise. I would pilot Model B in the densest regions if faster delivery improves conversion or reduces cancellations. Full rollout makes economic sense after roughly 12,500 monthly orders, assuming service benefits hold.”
Definitions You Can Say in One Breath
- Distribution model: The operating design used to store, move and deliver products from supply points to customers.
- Cost to serve: The total cost incurred to fulfil a customer order at a defined service level.
- Service level: The probability or proportion of demand fulfilled as promised, in quantity and time.
- Inventory pooling: Reducing total safety stock by serving multiple demand locations from a shared inventory point.
- Last-mile delivery: The final movement of an order from the nearest fulfilment point to the end customer.
Mini Case Study: Lenskart and the Omnichannel Distribution Choice
Lenskart shows why the right distribution answer is often a hybrid: online convenience plus store-led trust, fitting and service.
Situation. Eyewear is a difficult product to distribute purely online. Customers may need eye testing, frame trial, prescription accuracy, fit adjustment and after-sales support. A pure ecommerce model can give assortment and convenience, but it struggles with trust and physical fit. A pure retail model gives service, but it can limit reach and lock capital in many stores.
The move. Lenskart built an omnichannel model: digital discovery and ordering, physical stores for trial and service, and a fulfilment backbone that supports both online and offline demand. The primary driver is matching the distribution model to the product’s trust-and-fit requirement. Supporting drivers include online assortment, store experience, local service, demand aggregation and brand visibility.
The lesson. The model is not “online versus offline.” It is a designed split of jobs: online for discovery and convenience, stores for confidence and service, and centralised operations for scale. That is exactly how a strong case answer should think - assign each activity to the model that performs it best.
So what: When a product needs both convenience and confidence, the best distribution model is usually a hybrid where each channel has a sharply defined role.
How AI Changes Choosing Between Two Distribution Models
AI makes distribution-model choices more dynamic. Instead of choosing one static network for the whole year, companies can simulate demand, service and cost trade-offs more frequently.
A practical student workflow: load the case facts, demand table and cost assumptions into ChatGPT or Claude, ask it to build a Model A versus Model B cost tree, then manually verify every formula. If the case includes SKU-level stocking decisions, revise setting inventory policy for a multi-product business before practising the recommendation.
Interview Relevance
“An ecommerce company currently ships all orders from one central warehouse. It is considering regional warehouses in four cities to reduce delivery time. How would you decide whether to switch?”
If the interviewer gives limited numbers, say: “I will first compare total cost at the same service level, then check if faster delivery changes revenue through conversion, cancellation or repeat purchase.” That one sentence sounds mature.
Common Mistake
The biggest mistake is choosing the model with the lower transport cost. It costs candidates because distribution is a system choice: lower freight can be wiped out by higher inventory, poor fill rate, slow delivery or loss of customer data. Fix: always compare total cost to serve at a defined service level.