01 / Clarify the objective
What would make delivery worth doing?
Northline Coffee operates ten shops. The owner wants the chain to earn at least $100,000 in monthly operating profit. A delivery platform proposes a chain-wide launch. You have been asked to recommend whether to proceed.
Before calculating, name the questions you would ask. Separate the objective, the current business and the proposed change.
Compare your clarifying questions
- Is the target for the entire chain, and is it recurring monthly operating profit?
- What do current orders, average order value, variable costs and fixed costs look like?
- Are delivery orders incremental, or will existing customers switch channels?
- What commission, packaging and extra staffing does delivery require?
- Can the shops handle the extra volume without damaging the existing service?
For this exercise, use the monthly chain-wide figures below. Exclude tax, financing and one-time launch costs. Those exclusions limit the recommendation; they are not evidence those costs are zero in a real business.
Build a structure around the decision
Start with current profit. Then estimate the incremental contribution from delivery, subtract new fixed costs and any contribution lost from existing orders. Check capacity and service quality before turning the calculation into a launch recommendation.
New profit = current profit + delivery contribution − new fixed costs − lost shop contribution
A named framework is useful only if it helps answer this decision. See the consulting frameworks guide for further reading.
02 / Read the exhibit
Find the profit gap.
Exhibit 1 describes the current chain. All shops are combined; all money is in US dollars.
| Measure | Chain total |
|---|---|
| Orders | 180,000 |
| Average revenue per order | $6.00 |
| Variable cost per order | $3.60 |
| Fixed operating costs | $360,000 |
| Target operating profit | $100,000 |
What is monthly revenue, contribution and operating profit? How far is the chain from its target?
Check the current profit calculation
Revenue = 180,000 orders × $6 = $1,080,000/month.
Contribution per order = $6 − $3.60 = $2.40. Total contribution = 180,000 × $2.40 = $432,000/month.
Operating profit = $432,000 − $360,000 = $72,000/month. The target gap is $100,000 − $72,000 = $28,000/month.
Reasoning check: contribution pays fixed costs before it becomes profit. Treating the $432,000 as operating profit would miss the objective.
03 / Test the proposal
Does a bigger basket solve the problem?
The delivery platform estimates 30,000 delivery orders per month. Start by assuming they are all incremental. Delivery revenue below is the customer’s order value before commission; ignore taxes and customer delivery fees.
| Measure | Assumption |
|---|---|
| New delivery orders / month | 30,000 |
| Average order revenue | $8.00 |
| Variable product cost / order | $4.80 |
| Platform commission | 25% of order revenue |
| Packaging / order | $0.30 |
| Additional fixed staffing / month | $8,000 |
Calculate delivery contribution per order and the chain’s new monthly profit. Does the proposal reach the target?
Check delivery contribution and profit
Commission = 25% × $8 = $2 per order. Delivery contribution = $8 − $4.80 − $2 − $0.30 = $0.90/order.
Monthly delivery contribution = 30,000 × $0.90 = $27,000. After $8,000 of new fixed staffing, incremental profit is $19,000/month.
Chain profit becomes $72,000 + $19,000 = $91,000/month: a $9,000 shortfall. More revenue helps, but this proposal alone misses the owner’s target.
To close the original $28,000 gap with this cost structure, delivery must contribute $36,000 before staffing. At $0.90/order, that requires 40,000 incremental delivery orders/month, assuming the same costs and sufficient capacity.
Now challenge the strongest assumption.
Suppose 10% of delivery orders replace orders that would otherwise have been bought in a shop. Keep total delivery volume at 30,000 and all other assumptions unchanged. What happens?
Check the channel-switching sensitivity
Displaced shop orders = 10% × 30,000 = 3,000. Their lost contribution = 3,000 × $2.40 = $7,200/month.
Delivery’s net incremental profit is now $19,000 − $7,200 = $11,800/month. Chain profit becomes $83,800/month, $16,200 below target.
For each delivery order, expected lost shop contribution is 10% × $2.40 = $0.24. Effective incremental contribution is $0.90 − $0.24 = $0.66/order. Closing the $28,000 gap plus $8,000 staffing would require at least 54,546 delivery orders/month at that mix.
Commercial implication: order volume, channel switching and capacity need testing. A bigger basket does not automatically mean better economics.
04 / Make a recommendation
What would you tell the owner?
Give a recommendation in your own words before opening the example. State the decision, the supporting numbers, the main risk and the next action.
Compare a defensible recommendation
Do not commit to a chain-wide launch as the solution to the $100k profit target. At 30,000 fully incremental orders, delivery raises monthly profit to $91k; with 10% channel switching, it reaches only $83.8k. Run a limited pilot before committing, test incrementality and staffing, and revisit the terms or volume required to close the gap.
A pilot would test assumptions; these figures do not prove it will succeed. Measure delivery contribution after commission and packaging, displaced shop orders, service times and staffing needs. Check launch costs and capacity before setting commercial go/no-go thresholds.
Delivery can be profitable while still failing this specific target. Rejecting it outright without considering a pilot, or recommending it solely because revenue rises, would skip part of the decision.
Review your reasoning
- Did you define the target and period?
- Did you distinguish revenue, contribution and operating profit?
- Did you count commission and packaging once, with the correct units?
- Did you challenge whether delivery orders are incremental?
- Did your recommendation reflect the shortfall and the untested assumptions?
These prompts support self-review. They are not a score, a hiring prediction or a benchmark for interview readiness.