Case studiesLogistics
10LogisticsMid-sized organisation

Giving customers immediate delivery visibility

A digital service layer answers tracking questions, captures delivery changes and prepares exceptions for operations teams.

Illustrative scenarioAll results shown below are modelled, not verified client outcomes.
THE OPERATING CONTEXT

A realistic starting point.

Customer service receives thousands of “where is my delivery?” contacts. Agents switch among tracking, depot and customer systems, while genuine delivery exceptions compete with routine status enquiries.

THE AIIT SOLUTION DESIGN

A digital employee built around the work.

SAM recognises shipment identifiers, retrieves current events, explains status in plain language and completes approved delivery instructions. Damaged, missing or time-critical shipments transfer with the relevant scan history and customer context.

END-TO-END WORKFLOW

From first contact to a useful outcome.

  1. 01

    Identify the shipment securely

  2. 02

    Retrieve tracking events and delivery commitments

  3. 03

    Explain the latest known status

  4. 04

    Capture an approved instruction or redelivery request

  5. 05

    Confirm the action and expected next update

  6. 06

    Create a prioritised case for exceptions

MODELLED OUTCOMES

What a well-run scenario could change.

Planning estimates only. Not a promise, forecast or report of actual AIIT client performance.

+48 points

Tracking contacts self-served

Baseline21%
Modelled69%
−68%

Average handling time

Baseline6 min 30 sec
Modelled2 min 5 sec
+29 points

Exception case completeness

Baseline63%
Modelled92%
−11 points

Calls transferred between teams

Baseline18%
Modelled7%
ASSUMPTIONS

The conditions behind the model.

These boundaries make the scenario interpretable. Change the demand, workflow mix, integration quality or adoption rate and the potential outcomes change as well.

Tracking events are accurate and available in near real time

Only approved delivery instructions can be completed automatically

Claims for loss or damage remain subject to human review

Handling-time estimates include escalated contacts

A CONTROLLED PATH TO VALUE

How this scenario could be implemented.

01

Create plain-language mappings for tracking events

02

Define instruction permissions by shipment state

03

Connect status first, then controlled actions

04

Monitor depot-specific exception patterns

DESIGN LESSONS

What matters beyond automation.

Customers need an explanation, not a raw scan code.

A promised next update reduces repeat contacts.

Exception summaries should preserve the complete shipment timeline.

About this scenario: AIIT created this fictional, anonymised operating example to support planning conversations. The figures are calculations based on the assumptions shown above; they do not represent an existing client, testimonial or guaranteed result.

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SAM JOBS

Digital Employee roles

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