Insights · AI Agents

From Daily CSV Reports to an AI Supply Chain Agent

7 min readBy Strahinja Jovanović

Every operations team has one report that quietly eats a person. In one q-commerce environment I worked in, it was the daily delivery report: ordered versus delivered, by supplier, by location.

The manual routine

The process looked like this, every single day:

  1. Open the daily operational report
  2. Identify ordered products that were not delivered
  3. Separate the issues by supplier and location
  4. Find the right supplier contacts
  5. Write individual emails
  6. Track responses
  7. Update internal teams
  8. Repeat tomorrow

Nobody had designed this workflow. It had accumulated. And like most accumulated workflows, it consumed serious time while still leaving room for missed cases, inconsistent messages, and plain human error. The people doing it were capable planners spending their mornings as email clerks.

What the agent does

We designed a supplier delivery accuracy agent around the exact same steps, in the same order:

  • Reads the daily operational report
  • Detects ordered products that were not delivered
  • Groups issues by supplier and fulfillment location
  • Connects each issue to the correct supplier contacts
  • Prepares standardized communication
  • Creates an audit trail of every case
  • Produces recurring management reporting

Note what the agent does not do: it does not invent a new process. It executes the process the team already trusted, without getting tired, skipping a supplier, or writing a different email on a bad day.

The result nobody expected

The headline number: approximately 60 to 80 hours of manual work removed per month. That alone justified the build.

But the more valuable outcome was analytical. Once every case was logged consistently, a pattern appeared: not every apparent supplier failure was actually caused by the supplier. Some products had physically arrived but were never correctly received or recorded internally.

The agent's audit trail let the business separate cases into distinct categories:

  • Supplier non-delivery
  • Partial delivery
  • Late delivery
  • Incorrect internal receiving
  • Master data problems
  • Internal execution failures

Before the agent, all of these looked identical in the report and the supplier got the blame for every one. After the agent, the business knew which conversations belonged with suppliers and which belonged with its own receiving process.

Why this matters beyond one report

Supplier reliability touches far more than procurement. It drives product availability, customer experience, inventory planning, working capital, and the level of trust between commercial and supply chain teams. Cleaning up the signal in one daily report improved decisions in all of those areas.

The operator takeaway

Do not start your AI journey with a moonshot. Start with the report someone opens every morning and processes by hand. Map the exact steps, automate them faithfully, log everything, and let the data tell you where the real problem lives. In our case, the real problem was partly on our own dock.

The decision this leaves you with

Start not with a moonshot but with the report someone opens every morning and processes by hand, map the exact steps, automate them faithfully, log everything, and let the data tell you where the real problem lives.


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