415. Expected Profit
415.1. Expected profit and lost sales (newsvendor)
This file doesn’t relax a dimension — it computes additional outputs of the standard newsvendor model. Once you have , what’s the expected profit, expected leftovers, expected lost sales? The answer for normal demand uses the standard normal loss function.
415.1.1. Setup
Same as basic newsvendor: , decision , prices .
Define the standard normal loss function:
where is the standard normal density, the CDF. measures the expected shortfall above for a standard normal — equivalently, .
Properties:
- as (no shortfall expected far in the upper tail)
- as (everything below is “missed demand” if you over-order huge)
For computation, is tabulated or computed numerically.
415.1.2. Expected lost sales
For demand where , lost sales when amount to . In standard-normal units, :
This is the expected shortfall in actual units — multiply by to scale back from standard normal.
415.1.3. Expected leftovers
By symmetry, expected leftovers . By inventory balance:
415.1.4. Expected sales
(Total demand minus the part that wasn’t satisfied.)
415.1.5. Expected profit
Per-unit revenue components:
- Sales bring in profit (margin) per unit sold.
- Leftovers: bought at , salvaged at , so loss = per leftover.
Expand:
Plug in :
The first term is the deterministic-demand profit (sell exactly units at margin ). The second is the stochastic penalty — the cost of demand uncertainty, scaled by .
415.1.6. Bounded loss from uncertainty
For any , the penalty is minimized exactly when . So the optimal newsvendor minimizes the cost of uncertainty given the cost structure.
Example
Given (same newspaper baseline):
- , ,
- , , , ,
Step 1 — loss-function value
At :
Step 2 — expected lost sales
Even at the optimum, expect about 4 missed sales per period.
Step 3 — expected leftovers
Step 4 — expected sales
Step 5 — expected profit
$177.8 / period
Compare to deterministic-demand profit
If demand were exactly every period:
$200 / period
The cost of uncertainty is $22.2 / period — that’s the gap between what you could earn knowing demand exactly vs. what the optimal newsvendor strategy actually earns under the given . Reducing demand uncertainty (better forecasting) directly recoups this gap.