Why Your Delivery Promise Breaks Before the Van Leaves: A Delivery Experience Optimization Framework - Locus
Why Your Delivery Promise Breaks Before the Van Leaves: A Delivery Experience Optimization Framework
[Ishan Bhattacharya](/content/author/ishan_locus/ "Ishan Bhattacharya"/index.html)
Aug 25, 2026
12 mins read
Key Takeaways
- A missed delivery is usually the last event in a failure that started hours earlier, at a decision nobody connected to the promise.
- Five pre-dispatch decisions determine whether a promise is achievable: the capacity check at order capture, release timing, load build, departure adherence, and route feasibility at plan time.
- CX owns the promise and has visibility into none of those five. That is why Delivery Experience Optimization stalls when it is run as a communications programme.
- The diagnostic is the promise-to-plan gap: at each stage, compare what the promise assumed against what the operation committed. The stage where they diverge is your actual problem.
- Reliability is now worth more than speed to customers, which makes promise accuracy the cheaper investment.
The promise breaks upstream
A customer receives a delivery outside the window they were given. The post-mortem looks at the route, the driver, and the traffic.
In most cases the route was already infeasible when the driver collected it...
The customer expectation makes this worth solving rather than managing. McKinsey found that speed fell from consumers’ number one delivery priority in 2022 to fifth by 2024, displaced by reliability and predictability, with around 90 percent of consumers willing to wait two to three days when delivery is free and arrives within the stated window. Customers are not asking to be served faster. They are asking to be told accurately, which is a promise-accuracy problem rather than a transit-time problem.
The five decisions that determine feasibility
1. The capacity check at order capture
The moment the promise is made. If the date shown to the customer comes from a static lead-time table rather than from available capacity and serviceability on that lane that day, the promise is a guess with a commitment attached...
2. Release timing
When orders are released to the floor determines whether they can be picked, staged, and loaded in time for the collection they were promised against...
3. Load build
What goes on which vehicle, in what order...
4. Departure adherence
The gap between the planned departure and the actual one, which is inherited in full by every stop on the route...
5. Route feasibility at plan time
Whether the plan the driver receives can actually be completed inside the promised windows, given realistic service times, access conditions, and the driver’s remaining hours...
Why CX cannot see any of it
Each of those five decisions is made in a different system by a different team against a different objective...
The cost of that is measurable on the customer side. Gartner’s customer effort research found 96 percent of customers who have a high-effort service experience become disloyal...
The promise-to-plan gap diagnostic
One analysis locates the break. At each of the five stages, compare what the promise assumed against what the operation actually committed.
| Stage | What the promise assumed | What to measure | The break looks like |
|---|---|---|---|
| Order capture | Capacity existed on that lane that day | Share of promises made without a capacity check | Promise dates cluster on days the network was already full |
| Release | Orders would be ready for the planned collection | Wave completion time against planned collection time | Waves clearing after the collection slot |
| Load build | Load matched delivery sequence | Share of loads built to delivery sequence | Driver-reported reload events mid-route |
| Departure | Vehicle left on its slot | Actual against planned departure, by depot | A consistent depot-level delay inherited by every route |
| Route plan | Stops completable in promised windows with real service times | Planned against actual service time per stop type | Misses beginning consistently from the same position in the sequence |
What changes when promise is an execution capability
Three shifts, in order of leverage.
The promise is computed rather than looked up. Capacity and serviceability checked at the moment of commitment...
What to measure
Four measures, none of which is a survey.
Promise accuracy, the share of orders delivered inside the window shown at checkout, reported by metro and by carrier rather than blended.
Promise-to-plan gap by stage, per the table above, which is the diagnostic rather than the outcome.
Proactive rate, the share of at-risk deliveries where the customer was told before they enquired.
Repeat purchase rate segmented by whether the previous order arrived on promise, which is the measure that connects this work to revenue rather than to cost avoidance.
Where Locus fits
Locus, the world’s first Decision-Intelligent, Agentic TMS, sits across the stages where the promise is actually determined rather than only at the point it is communicated...
The analysis to run first
Take a month of missed promises and record the stop number at which each route first fell behind...
FAQs
Why do delivery promises fail?
Usually upstream of the delivery...
Is delivery promise accuracy a CX problem or an operations problem?
An execution problem owned by CX...
What is capacity-aware promising?
Computing the delivery date at the moment of commitment against real available capacity...
How do you diagnose where a delivery promise breaks?
Compare what the promise assumed against what the operation committed...
Do better notifications reduce missed deliveries?
No...
Should retailers promise faster or more accurately?
More accurately, on current evidence...