F&B

Pernod Ricard — Business Intelligence

Pernod Ricard — Business Intelligence

60%

60%

Reduction in reporting effort

1

1

Monthly review cycle eliminated

About

A global F&B group where consolidated reporting took two weeks and arrived too late to act on. We built a unified data warehouse and executive command centre that delivers a daily view of every SKU, region, and distributor in one place.

Industry

F&B

Company size

1,000 – 5,000 employees

Founded

2005

The Company

A direct sales business growing faster than its planning infrastructure

Horizon Consumer Brands is a fast-growing FMCG company with a direct sales force of over 300 field representatives operating across 8 states. The company sells through general trade and modern trade channels, with a portfolio spanning personal care and home care categories.

Sales territory performance had long been a source of tension across the business. Some territories consistently outperformed targets while others chronically missed — and leadership lacked the analytical infrastructure to determine whether these differences were driven by territory potential, representative performance, or both. The business was leaving revenue on the table without a clear way to quantify how much, or where.

The challenge

Forecasting on an unreliable foundation

The sales planning team was producing monthly forecasts using a combination of historical sales data and anecdotal input from regional managers. Forecast accuracy was poor — averaging below 40% at the territory level — which meant that inventory allocation, sales incentive structures, and resource deployment decisions were all being made on an unreliable foundation.

Territory design itself was a further compounding issue. Sales territories had been drawn years earlier based on geography and historical boundaries, with no systematic analysis of market potential. Some high-potential markets were being under-resourced while representatives in low-potential territories were hitting activity targets but unable to generate proportional revenue.

Sales incentive design was suffering as a direct result. Representatives were being evaluated against historical averages that reflected territory design rather than individual performance — creating frustration and making it impossible to identify who the real high performers were.

The Solution

Forecasting and territory optimisation in a single integrated intervention

Seven Billion deployed a two-phase analytical intervention: a forecasting model to improve sales prediction accuracy, and a territory optimisation model to realign resource allocation to market potential.

For forecasting, an ensemble model was developed using Facebook Prophet for trend and seasonality decomposition, combined with a Random Forest model to capture SKU-level and territory-level performance patterns. The combination outperformed either approach in isolation, particularly on territories with irregular seasonality or recent distribution changes.

For territory optimisation, a Linear Programming model was built that took potential scores — derived from market size data, current penetration rates, and competitive activity indicators — and optimised territory assignments to maximise total addressable revenue within existing headcount constraints. The model produced a concrete reallocation recommendation with projected revenue impact quantified at each territory level. Output was delivered through a sales intelligence dashboard giving regional managers real-time access to territory-level forecasts, actual-vs-forecast tracking, and the territory potential heatmap used to drive the reallocation recommendation.

The Results

A 9% revenue improvement and a fundamentally better-run sales operation

Sales forecast accuracy improved by 30% across the territory network, with the greatest gains in territories where the historical model had been systematically biased by distribution changes. Territory realignment, implemented in phases over two quarters, drove a 9% improvement in total revenue versus the equivalent prior period — the highest organic growth rate the company had achieved without new product launches or market expansion.

Regional managers reported a significant reduction in time spent preparing and reconciling monthly sales reports, with the dashboard replacing a three-week manual consolidation process. Sales incentive design improved measurably as a result of the more granular understanding of territory potential — with representatives now evaluated against meaningful benchmarks for the first time.

The commercial impact extended beyond the numbers. The business now had a systematic way to diagnose territory performance and act on it — a capability that had been entirely absent before the engagement.

professional portrait

The commercial impact has been significant. But more importantly, we now have the tools to keep improving — and a sales team that finally trusts the targets it is working against.

VP Sales, Horizon Consumer Brands

The lowest-risk way to find out if AI is right for your business.

Phase 0 is a two-week discovery that tells you exactly which problems AI can solve, what it will take to build, and what it will cost. No obligation beyond it.

ABOUT Seven Billion

Seven Billion is an Applied AI company — a team of data scientists and AI engineers who build and deploy AI systems that run in production. Founded in 2020. Offices in Boston, USA and Bengaluru, India.

OFFICE

Boston, USA
Bengaluru, India

Intelligence that delivers starts here.

Whether you are mapping your first AI use case or scaling AI across the enterprise, we will help you cut through the noise and build something that actually ships.

ABOUT Seven Billion

Seven Billion is an Applied AI company — a team of data scientists and AI engineers who build and deploy AI systems that run in production. Founded in 2020. Offices in Boston, USA and Bengaluru, India.

OFFICE

Boston, USA
Bengaluru, India

The lowest-risk way to find out if AI is right for your business.

Whether you are mapping your first AI use case or scaling AI across the enterprise, we will help you cut through the noise and build something that actually ships.

ABOUT Seven Billion

Seven Billion is an Applied AI company — a team of data scientists and AI engineers who build and deploy AI systems that run in production. Founded in 2020. Offices in Boston, USA and Bengaluru, India.

OFFICE

Boston, USA
Bengaluru, India