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BUC-3 — AI-powered Trade Spend Forecasting: Smarter, Sharper, Earlier.

Nestlé Vietnam · Posted 2 days ago

Consumer goodsPredictive Analytics / Forecasting
Budget
To be determined
Timeline
Based on solution provider proposal
Apply by
22 Nov 2026, 23:59 ICT

Problem statement

A reliable TTS (Total Trade Spend) forecast by activity and channel/customer from validated bottom-up data; know early whether budget will be short or left over so it can be added or released in time, and build a TTS data foundation that can be reused globally. Today: - Trade spend is planned only for the very short term; a budget number is set and allocated across the year. - Spending on activities to boost sales is not tied to an activity-based plan, so budget can run short mid-year and extra requests to Finance lack a plan behind them. - The current trade promotion system is only used to record ROI.

Expected outcomes and success metrics

- Trade spend forecast accuracy beyond M+1 (Month + 1) and the TTS investment KPI. - No channel runs out of budget mid-year; less pressure on Finance. - Maximise sales and grow value gap; TTS and sales targets by channel; P&L forecast by channel and customer. - Commercial gets business scenarios to decide; Finance allocates resources right; DSP gets better demand-planning input. - Low-return spend flagged before renewal, with recommendations on where to reallocate for the highest incremental growth.

Target users and impacted teams

- Sales (TT, MT, eCommerce, OOH) - CDT (Customer Development Team) and Sales Control - Finance & Control - Supply Chain / Demand & Supply Planning (DSP)

Data availability and readiness

- SRS data (activity-based, budget, timeline, SKU sales forecast) – owner: CDT - Plan, contract, accrual, liquidation and payment data with P&L by customer × category × SKU Note: Synthetic data could be potentially provided during the process, upon approval of the Nestlé team and in compliance with data law.

Integration, deployment and infrastructure

To be determined Note: Nestlé's current environment includes Microsoft Azure and Microsoft Copilot. Solutions that can work with this environment are welcome, and final integration and deployment requirements will be confirmed with the Nestlé team.

Relevant AI technologies

Predictive Analytics / Forecasting

Also: Machine Learning. Based on Nestlé's description of AI that forecasts trade spend and sales, flags overruns and suggests scenarios.

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