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Kerning AI.

BAT GTR / AI planning prototype

Kerning / Intelligence

From demand signals
to planning decisions.

A prototype combining demand forecasting, gap analysis, allocation scenarios and a grounded planner copilot.

All work
Prototype
Mock data

A clearer signal.
A considered decision.

DEMAND / SUPPLY / ALLOCATIONSCENARIO STUDY
01Forecast02Understand03Compare04Decide
Prototype built with mock data. Live SAP, POS and Pack Smart integrations are outside its demonstrated scope. No production performance or business outcomes are claimed.
Client
BAT GTR
Sector
Global travel retail & supply planning
Focus
Prototype · mock data

The context

Start with the way
the business works.

Planners need more than a forecast. They need to understand why orders and deliveries diverge, identify the accounts that need attention and compare choices when available supply cannot cover all demand.

We developed a planning prototype that brings these questions into one workspace. Structured forecasting and analysis support a planner copilot, while alerts, customer views and allocation scenarios help make the reasoning behind a proposed decision visible.

A closer look

Inside the prototype.

Give the forecast context.

The prototype combines demand forecasts with order-versus-delivery gap analysis. Customer and portfolio views provide another lens on the signals, so a planner can move from an aggregate picture to an account that needs closer attention.

Make the trade-offs explicit.

An allocation model compares a priority-based recommendation with proportional distribution under a supply constraint. The scenario exposes demand, available supply and account-level recommendations instead of presenting one unexplained answer.

Bring analysis into the conversation.

The planner copilot uses tools connected to the prototype’s structured data and analysis. It sits alongside alerts, decisions and planning views, making conversational assistance part of the planning process.

The design principle

A prototype that makes decisions tangible.

Before committing to a wider implementation, teams can inspect the workflow, question its assumptions and experience how AI and structured analysis work together.

Next / Your business, reimagined

Build the next
version of your business.

Tell us what you need to build or improve. We’ll discuss the scope, the systems involved and a practical next step.

Discuss your project