Effectively limiting special deliveries across the store network
A retailer with several regional warehouses bundles special deliveries in an agentic workflow that assesses urgency and points out alternatives.
- Retail
- Supply chain management
Key metric
Share of unplanned special deliveries
10065runs
Unplanned special deliveries per week across the store network
At a glance
Starting point
The retailer operates more than 300 stores supplied from five regional warehouses. On top of the regular routes, 40 to 60 special deliveries are triggered every day by stock shortages, incorrectly picked goods or local promotions. Store managers report their needs to dispatch directly by phone, email or messenger. Each request is checked individually, often under time pressure and with incomplete information on stock, alternatives and costs. The transport department spends several hours a day organizing special deliveries, while the costs of additional runs are hardly tracked transparently.
- 300+
- stores
- 40-60
- special deliveries per day
The challenge
Special deliveries have become part of everyday operations, even though they should really be exceptions. Store managers point to looming out-of-stock situations or local promotions that were not planned in time. Dispatch has no consistent process for assessing urgency, costs and alternatives. Information on warehouse stock, planned routes and promotion calendars sits in different systems that are not checked systematically under pressure. Decisions depend heavily on the experience of individual dispatchers, which leads to inconsistent approvals and discussions. There is hardly any structured analysis of which special deliveries could have been avoided.
Typical symptoms in the organization
Why this remained unsolved
The problem had long been known but was accepted as an unavoidable consequence of the store business. A classic IT project seemed oversized because requests are often worded freely and depend on the situation. Attempts to establish rigid checklists or approval rules in Excel failed because of the variety of cases and dispatch's limited time. There was also no solution that brings together information from route planning, warehouse stock and promotion calendars while remaining easy for store managers to use. So decisions stayed manual: they worked, but caused high costs and a lot of coordination effort.
Our solution
An agentic workflow was introduced that captures all special delivery requests centrally, structures them and enriches them with relevant data. Store managers report their needs through a short form or by email, which is automatically converted into standardized fields. The workflow checks warehouse stock, planned routes and promotion data, assesses urgency and suggests alternatives, such as rebooking onto existing routes or temporarily limiting quantities. A special delivery is only forwarded to dispatch for approval if defined criteria are met. Decisions and their reasons are logged so that costs and patterns can be analyzed later. The result is a transparent, repeatable process that better balances store supply and transport costs.
Where generative AI comes in
Generative AI understands freely worded requests from the stores, extracts details on items, quantities and promotions and assigns them to categories. It writes alternative suggestions and justifications in plain language, handles different phrasings and captures complex situations without needing additional form fields.
- Central intake of all special delivery requests, with emails and forms automatically converted into structured records.
- Integration with route planning and warehouse stock to automatically check available capacity, current stock and deliveries already planned.
- Urgency assessment based on defined criteria such as out-of-stock risk, promotion relevance and the store's customer footfall.
- Generative creation of alternative suggestions, such as using existing routes, stock transfers or temporarily adjusting order quantities.
- Transparent approval process with documented decisions, justifications and cost notes for later analysis and steering.
How the special delivery workflow runs
Capture the request
Store managers send their special delivery request by form or email, and the workflow takes it over and structures all details automatically.
Enrich the data
The workflow pulls in stock levels, route planning and promotion data from connected systems and fills in missing information for the assessment.
Assess urgency
Based on defined criteria and context, urgency is assessed and a supply recommendation is prepared.
Suggest alternatives
Generative AI formulates concrete alternatives to the special delivery, including the impact on availability and costs for the store.
Document the approval
Dispatch makes the decision, and the workflow logs the approval, justification and cost notes and closes the case.
Measured: results after six months in operation
Period: results after six months in operation.
| Metric | Value | Basis |
|---|---|---|
| Share of unplanned special deliveriesKey metric | Reduced by around 35 percent | System measurementmeasured |
| Dispatch time per day | Saving of 1-2 hours per day | Time tracking before/afterestimated |
| Share of cases needing follow-up questionsQuality metric | Around 15 percent of requests need manual clarification | Samplemeasured |
Cost-effectiveness
The workflow's decisions are only as good as the connected data is current and complete. Unclear stock levels or missing promotion data can block sensible special deliveries or trigger unnecessary ones.
Integration and operation
Transferability
This approach suits any area where short-notice special processes cause high costs but have so far only been managed informally. The key is to capture requests in a structured way, enrich them with relevant data and assess them before a decision is made. Generative components help turn freely worded needs into standardized categories and suggest understandable alternatives. This way, special cases in other areas can also move from a state of exception to a managed process.
A similar case in your organization? Let's talk.
Briefly describe your process. We'll get back to you with an initial assessment of whether the pattern can be transferred and what it would realistically take.