AI-02 · AI case study · Trade promotions · FMCG distribution

From promotion brief to live scheme, without re-keying

Concept case study · 2026 · Based on my promotion configuration and testing work on a DMS rollout

ConceptA design based on my project experience, written during my 2026 sabbatical. It is not a deployed client solution.

6Promotion types covered, on-invoice and off-invoice
Draft onlyA person approves every promotion
Before launchConflicts caught, not after invoicing
One sourceSame scheme in the DMS and the salesman app

The context

Every trade promotion starts as a brief from the brand team: which products, which shops, what discount or free goods, what budget and for how long. Someone then has to set it up in the DMS, field by field.

On my last DMS rollout I configured and tested six promotion types, on-invoice and off-invoice, for two markets. This concept uses that experience to design an AI-assisted set-up flow.

The problem

Set-up is manual, and mistakes surface only on invoices:

  • Briefs arrive as PDFs and emails, worded differently each time.
  • Each promotion is keyed into the DMS by hand.
  • Overlapping schemes and wrong dates are found only when invoices go wrong.
  • Corrections reach distributors and salesmen late.

What I did

  • Listed the fields each of the six promotion types needs, from my configuration and testing work.
  • Designed the extraction, validation and approval steps.
  • Defined conflict rules for overlaps, budgets, dates and eligibility.
  • Wrote a field-mapping sample and acceptance criteria for the draft step.

The process, before and after

Each column is a team or system. Numbered badges point to where time is lost today, and how the design saves it.

Scroll sideways to see the whole diagram →

Promotion set-up before: keyed in by handBrand teamDMS adminDistributorSalesmanNewpromotionShare brief asPDF or email1Key promotionin by hand2Spot wrongdiscounts3Fix andpublish againLateupdate
  1. 1Promotion rules arrive as a PDF or email, worded differently each time.
  2. 2Each scheme is typed into the DMS by hand, field by field.
  3. 3Mistakes surface only when distributors see wrong discounts on invoices.
Start Step Decision End Each column is one team or system. Arrows show hand-offs.

What changed, step by step

StepBeforeAfter
Promotion briefPDF or email, any formatStandard brief per promotion type
Set-upKeyed in by handDrafted automatically, then reviewed
ConflictsFound on wrong invoicesFlagged before approval
Going liveDMS and app updated separatelyPublished to both at once

The approach

  1. 1
    Standardise the briefOne brief template per promotion type, so the assistant always knows what to look for.
  2. 2
    Extract into a draftThe AI assistant reads the brief and fills a draft set-up: type, products, shops, value, budget and dates.
  3. 3
    Check before anyone approvesRules flag overlapping schemes, missing budgets, invalid dates and products not on the price list.
  4. 4
    Keep a person in chargeThe brand or trade marketing owner reviews and approves every draft. Nothing goes live on the AI's word alone.
  5. 5
    Publish onceThe approved promotion goes to the DMS and the salesman app together, so both show the same scheme.

Sample work: field mapping extract

FieldFrom the briefDraft valueCheck
Promotion typeBuy 10, get 1 freeFree goods, on-invoiceType is one of the six set up in the DMS
ProductsAll 1 litre packs3 product codesEvery code is on the active price list
ShopsGrocery outlets, North regionChannel: grocery · Region: NorthNo overlap with another live scheme
DatesWhole of next month1 to 30 NovemberStarts after approval and ends inside the budget period
BudgetUp to 5 lakh₹5,00,000Budget is set and not already used

Illustrative extract written for this portfolio.

Expected outcomes

  • Faster set-up, because nobody types promotion fields in by hand.
  • Fewer wrong discounts reaching invoices.
  • Distributors and salesmen see the same scheme on the same day.
  • A clear approval record for every promotion.

Design principles

  • Standardise the input before automating it.
  • AI drafts, people approve.
  • Catch conflicts before launch. Fixing invoices costs far more.

Concept case study written during my 2026 sabbatical. It is not a deployed client solution. Examples are generic.