Improving Demand Forecasting with Advanced Supply Chain Analytics

Enabled proactive demand planning through a centralized analytics platform that provides visibility into forecast accuracy, forecast bias, shipment performance, and demand trends, helping optimize supply chain operations and inventory management.

6

Demand forecasting analytics domains delivered 

3

Supply chain data sources unified for demand planning analytics

18

Month consensus demand forecasting visibility enabled for future planning horizons

Executive Summary

A leading biotechnology company sought to improve demand planning effectiveness by gaining better visibility into forecast accuracy, forecast bias, shipment performance, and demand trends. Limited analytical insight into forecasting performance created challenges in aligning production, inventory, and supply chain operations with anticipated demand. 

DiLytics implemented a Demand Forecasting Analytics solution leveraging Oracle ASCP, Oracle Demantra, Oracle EBS, Oracle Business Analytics Warehouse, Informatica, and OBIEE. The solution delivered analytics capabilities across forecast accuracy, shipment variance, forecast bias, forecast changes, out-of-trend forecasting, and consensus demand planning. 

The implementation improved forecast accuracy, increased supply chain efficiency, reduced inventory carrying costs, and enabled more proactive, data-driven planning decisions across the organization’s supply chain operations. 

A leading biotechnology company sought better visibility into forecast accuracy, bias, shipment performance, and demand trends to improve demand planning and align supply chain operations with anticipated demand. DiLytics implemented a Demand Forecasting Analytics solution integrating Oracle ASCP, Oracle Demantra, Oracle EBS, Oracle Business Analytics Warehouse, Informatica, and OBIEE to deliver insights into forecast accuracy, shipment variance, forecast bias, forecast changes, and consensus demand planning. The solution improved forecasting effectiveness, increased supply chain efficiency, reduced inventory carrying costs, and enabled more proactive, data-driven planning decisions.

Submit Your Details to See the Complete Transformation Story 

Transformation Unlocked!

Use the top navigation menu or scroll down to explore the details.

Client Overview

The client is a global biotechnology company focused on developing and commercializing innovative therapies for rare genetic diseases. Headquartered in California, the company operates across more than 20 countries and employs over 2,500 professionals worldwide. As the organization expanded its global footprint, it invested in enterprise platforms to support growth across supply chain, manufacturing, finance, compliance, and human resources functions. 

Overcoming Forecasting Inefficiencies and Limited Demand Visibility

The organization lacked comprehensive visibility into forecast performance, demand changes, shipment variances, and forecasting trends. Limited analytical insight made it difficult to effectively align production, inventory, procurement, and supply chain planning activities with future demand. 

Limited Forecast Accuracy Visibility

Limited Forecast Accuracy Visibility

Business users lacked insight into forecast accuracy across products, geographies, and planning horizons, making performance evaluation difficult

Inability to Identify Forecast Bias

Inability to Identify Forecast Bias

The organization required better visibility into systematic over-forecasting and under-forecasting trends that impacted planning decisions

Challenges in Demand–Supply Alignment

Challenges in Demand–Supply Alignment

Limited forecasting insights made it difficult to synchronize manufacturing, inventory, and procurement activities with expected demand

Lack of Proactive Forecast Monitoring

Lack of Proactive Forecast Monitoring

Business teams needed the ability to identify forecast anomalies, demand shifts, and out-of-trend patterns before they impacted operations

Overcoming Forecasting Inefficiencies and Limited Demand Visibility

Limited Forecast Accuracy Visibility

Limited Forecast Accuracy Visibility

Business users lacked insight into forecast accuracy across products, geographies, and planning horizons, making performance evaluation difficult

Inability to Identify Forecast Bias

Inability to Identify Forecast Bias

The organization required better visibility into systematic over-forecasting and under-forecasting trends that impacted planning decisions

Challenges in Demand–Supply Alignment

Challenges in Demand–Supply Alignment

Limited forecasting insights made it difficult to synchronize manufacturing, inventory, and procurement activities with expected demand

Lack of Proactive Forecast Monitoring

Lack of Proactive Forecast Monitoring

Business teams needed the ability to identify forecast anomalies, demand shifts, and out-of-trend patterns before they impacted operations

Centralized Demand Forecasting Analytics for Smarter Supply Chain Planning

DiLytics implemented a Demand Forecasting Analytics solution leveraging Oracle Analytics, Oracle Business Analytics Warehouse, Informatica ETL, Oracle ASCP, Oracle EBS, and Oracle Demantra. The solution integrated planning, forecast, shipment, and operational data into a centralized analytics platform and delivered dashboards, KPIs, exception reporting, conditional alerts, and drill-down analytics supporting demand planning and supply chain operations.

Services Provided
  • Conducted requirements gathering and business process analysis 
  • Performed fit-gap assessment and solution design 
  • Designed and implemented ETL, enterprise data warehouse, and Oracle Analytics reporting architecture 
  • Developed dashboards, KPIs, reports, alerts, and drill-down analytics 
  • Conducted conference room pilots, testing, user acceptance testing, and deployment activities 
  • Delivered training, knowledge transfer, and production support 
Business Solution

The solution delivered analytics capabilities across six major demand planning areas: 

  • Forecast Accuracy Analytics: Measuring forecast accuracy by product, product family, geography, and time horizon 
  • Shipment Forecast Variance Analytics: Monitoring differences between forecasted and actual shipments 
  • Forecast Bias Analytics: Identifying systematic over-forecasting and under-forecasting trends 
  • Forecast Change Analytics: Tracking changes between planning cycles and forecast versions 
  • Out-of-Trend Forecast Analytics: Identifying forecast anomalies and demand patterns requiring attention 
  • Consensus Forecast Analytics: Providing visibility into future demand plans and consensus forecasts across products and markets 
Technical Solution
  • Integrated planning data from Oracle ASCP, forecast data from Oracle Demantra, and actual shipment data from Oracle EBS 
  • Implemented automated ETL processes using Informatica 
  • Leveraged Oracle Business Analytics Warehouse as the centralized repository for demand planning analytics 
  • Developed metrics, KPIs, dimensions, hierarchies, dashboards, conditional alerts, and guided navigation capabilities in Oracle Analytics 
  • Enabled drill-down analysis from summary forecasts to detailed shipment and planning data 
  • Established a scalable analytics foundation supporting future supply chain analytics initiatives 

Driving Better Supply Chain Outcomes Through Forecast Intelligence

The Demand Forecasting Analytics solution transformed demand planning by providing deeper visibility into forecasting performance, enabling proactive planning decisions, and improving alignment across supply chain operations.

Improved Forecast Accuracy

Enhanced visibility into forecast performance enabled more accurate demand planning across products and markets

Better Demand Planning Effectiveness

Provided timely access to trusted forecasting and shipment insights for more informed planning decisions

Improved Supply Chain Alignment

Strengthened coordination between demand forecasts, manufacturing schedules, inventory management, and procurement activities

Increased Supply Chain Efficiency

Enabled more effective planning processes that improved responsiveness and operational performance

Reduced Inventory Carrying Costs

Improved demand visibility and forecast reliability helped optimize inventory levels and reduce excess stock

Proactive Risk Identification

Enabled early detection of forecast anomalies, demand shifts, and planning risks through alerts and exception-based analytics

Tech Stack Summary

The solution leveraged Oracle’s integrated supply chain and analytics ecosystem to deliver end-to-end demand forecasting insights and performance tracking.

Data Sources
Data Integration
Data Warehouse
Data Visualization

Transform Demand Forecasting with Advanced Analytics

Improve forecast accuracy, reduce inventory costs, and enhance supply chain efficiency with an integrated demand forecasting analytics solution.