Industry
Beauty & Cosmetics
Region
South Asia-Pacific, Middle East & North Africa (SAPMENA)
Solution
AI-Powered Demand Forecasting
About the client

A global beauty company serving diverse markets and channels

A global beauty and cosmetics company, the organization serves millions of consumers across South Asia-Pacific, the Middle East, and North Africa (SAPMENA). Its demand landscape spans thousands of products across direct-to-consumer (D2C), B2B, e-commerce, retail, and specialty distribution channels. Behind that scale is a constantly shifting mix of promotions, product demand, and consumer preferences across markets. As digital commerce expanded, the organization needed a more accurate and efficient way to forecast demand and support planning across this increasingly complex environment.

The measurable impact

20%+

Improvement in forecast accuracy 
Forecast accuracy improved by more than 20% across major product lines for both short- and mid-term forecasting, supporting more informed planning decisions.

50% 

Reduction in manual forecasting effort 
A centralized planning solution reduced manual forecasting effort by approximately 50%, giving demand planners one place to manage forecasting activities.

12

Business reports with Power BI integration
Power BI integration delivered 12 business reports, giving demand planners greater visibility into demand trends and planning insights.

Optimized

Inventory and supply chain planning 
More accurate demand forecasts supported inventory optimization by reducing stock-outs and excess inventory while strengthening supply chain planning.
The business challenge

Demand planning that needed to keep pace with growth

As the company’s direct-to-consumer business expanded across SAPMENA, forecasting had to account for a broader product portfolio, multiple sales channels, and increasingly dynamic demand. An approach built largely on historical patterns and planner judgment was becoming harder to scale consistently across this growing planning environment.

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planning challenges
Growing demand complexity created five areas of friction that affected forecasting accuracy, consistency, and agility across the business.
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Manual forecasting dependence

Forecasting relied heavily on historical patterns and planner judgment, making a consistent approach harder to scale across products and markets.

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Fragmented demand data

Demand drivers were spread across Excel, Google Cloud, order management systems, and other non-standard sources, adding complexity to the forecasting process.

Where friction was building

 
As demand grew more dynamic across products, channels, and markets, fragmented data, changing demand signals, and inconsistent forecasting practices made reliable planning increasingly difficult.
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Manual forecasting effort
Forecasting relied heavily on historical patterns and planner judgment, adding manual effort and making consistent planning harder to scale.
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Fragmented demand data
Demand drivers were spread across Excel, Google Cloud, order management systems, and other sources, making it difficult to create a unified view for forecasting.

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Demand shaped by multiple signals
Promotions, pricing changes, media spend, platform traffic, holidays, special events, and stock-outs introduced demand signals that forecasting needed to account for across products and markets.
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Inconsistent forecasting approaches
Different forecasting practices made it harder to establish a consistent approach across products, channels, and markets.
The solution

Bringing AI and planner judgment into one forecasting platform

The platform brings data engineering, AI-powered forecasting, MLOps, planner workflows, and reporting into one demand planning experience. Designed for D2C and B2B channels, it combines multiple demand signals and forecasting models with planner input to support forecasting across a diverse portfolio of SKUs.
Data engineering
Data from Excel, Google Cloud, order management systems, and other sources is processed and brought together to support demand forecasting.
AI-powered demand forecasting
The forecasting engine incorporates promotions, pricing changes, media spend, platform traffic, holidays, special events, and inventory stock-outs. ARIMA, SARIMAX, XGBoost, LightGBM, and Prophet support different forecasting patterns across a diverse portfolio of SKUs.
MLOps
MLOps capabilities support the deployment, management, and maintenance of AI/ML forecasting models within the platform.
Planner-centric web application
A web interface enables demand planners to review, adjust, validate, and create consensus forecasts while incorporating business judgment into the final forecast.
Reporting and business insights
Power BI integration delivers 12 business reports, giving demand planners greater visibility into demand trends and planning insights.
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One platform.
Smarter forecasts.
Planning with confidence.

 

What it enabled


The AI-powered demand forecasting platform replaced fragmented planning with a centralized, enterprise-grade solution that combines data engineering, data science, MLOps, a web application, and reporting. Designed for both D2C and B2B channels, it enabled demand planners to review, validate, and manage forecasts from a single platform.

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Centralized demand forecasting platform

Data engineering, data science, MLOps, a planner-facing web application, and reporting came together in one enterprise platform, providing a centralized solution for demand planning.
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AI-powered, business-aware forecasting

The forecasting engine incorporated promotions, pricing changes, media spend, platform traffic, holidays, special events, and inventory stock-outs alongside AI/ML forecasting models to generate business-aware forecasts.
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Planner-centric forecast management

Demand planners could review, adjust, validate, and create consensus forecasts through an intuitive web interface, while MLOps capabilities supported the deployment, management, and maintenance of AI/ML models.
The business outcome

More accurate forecasts.
Less manual effort.
Smarter planning.

The AI-powered demand forecasting platform improved forecast accuracy by more than 20% and reduced manual forecasting effort by approximately 50%, while giving demand planners centralized access to forecasting, reporting, and decision support. More reliable forecasts also supported better inventory and supply chain planning.

Forecast accuracy improved
20+  

Forecast accuracy improved by more than 20% across major product lines for short- and mid-term forecasting, supporting more informed planning decisions.

Manual forecasting effort reduced 50%

A centralized planning solution reduced manual forecasting effort by approximately 50%, giving demand planners one place to manage forecasting activities.
.

Business reports delivered
12 



Power BI integration delivered 12 business reports, improving visibility into demand trends and access to planning insights.

Inventory and supply chain planning
Optimized  

More accurate demand forecasts supported inventory optimization by reducing stock-outs and excess inventory while strengthening supply chain planning.
The technology stack

Built on AI, machine learning, and enterprise data engineering

The demand forecasting platform brings together data engineering, data science, MLOps, a web application, and reporting to deliver accurate, scalable, and business-friendly demand forecasting across D2C and B2B channels.
Data engineering
Excel, Google Cloud, Order Management Systems
AI & Machine Learning
ARIMA, SARIMAX, XGBoost, LightGBM, Prophet
 
AI & Machine Learning
ARIMA, SARIMAX, XGBoost, LightGBM, Prophet
MLOps
MLOps
Application
Web Application
Analytics & Reporting
Power BI
Business transformation

From manual forecasting to AI-powered demand planning

The transformation brought AI-powered forecasting, richer demand signals, planner-led review, forecast explainability, and MLOps into one centralized planning capability across D2C and B2B channels.
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More accurate demand forecasting
The forecasting engine incorporates multiple demand drivers and AI/ML models to improve forecast accuracy across a wide variety of SKUs.
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Centralized demand planning
A centralized platform provides demand planners with a one-stop solution for planning activities, forecast review, validation, and consensus forecasting.
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Business-aware forecasting
Promotions, pricing changes, media spend, platform traffic, holidays, special events, and inventory stock-outs are incorporated into demand forecasts to better reflect business conditions.
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Forecast explainability
Built-in forecast explainability helps business teams understand forecast trends and generate actionable insights for faster, more informed decisions.
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Scalable AI operations
MLOps capabilities support the deployment, management, and maintenance of AI/ML models within the forecasting platform.

Turn demand into
smarter decisions.

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