Challenge:
The client, a leading FMCG food company, faced significant challenges with its demand management processes. Manual forecasting and planning led to inefficiencies, inaccuracies, and an inability to respond quickly to changing market dynamics. Forecast errors resulted in overstocking, stockouts, and increased operational costs.
Solution:
Using Aera Decision Intelligence, the company implemented a fully automated demand forecasting system. The solution leveraged AI-driven algorithms to predict demand patterns with high accuracy, factoring in historical data, market signals, and real-time inputs. By integrating Aera's capabilities, the company eliminated manual planning and adopted a touchless forecasting approach.
Outcomes:
- Reduced forecast errors by 10-15% on all A class segments.
- Decreased inventory carrying costs by 10%.
- Improved service levels by, resulting in better on-shelf availability.
- Enhanced agility in responding to market changes.
- Freed up planning teams to focus on strategic tasks rather than manual data processing.
This transformation enabled the company to optimize its supply chain, reduce costs, and improve customer satisfaction.
Challenge:
A global health and animal nutrition company faced difficulties in managing its procurement processes, particularly for imports and exports. Fragmented systems and manual processes created a lack of visibility across the supply chain, leading to inefficiencies, delays, and compliance risks.
Solution:
The company partnered with Aera Decision Intelligence to fully digitalize its procurement collaboration. The solution provided real-time visibility into procurement operations, integrated data from multiple sources (ERP, CRM, and third-party systems), and used AI-driven insights to optimize decision-making. Key features included supplier mapping, ranking, and automated workflows for import/export processes.
Outcomes:
- Reduced procurement cycle times by 15%
- Reduction in manual emails or follow-up by 50%
- Improved on-time delivery performance
- End to end visibility from Planning to Wearhouse
- Attained end-to-end visibility across the supply chain.
- Strengthened supplier relationships through better collaboration and transparency.
The digital transformation empowered the company to build a resilient and efficient supply chain, ensuring compliance and cost-effectiveness in global operations.
Challenge:
A leading automotive battery manufacturing company with a significant market presence across Southeast Asia, ANZ, and North America faced challenges in optimizing its production scheduling. Managing production across multiple sites with various constraints, such as capacity, resource availability, and delivery deadlines, relied heavily on manual planning. This led to inefficiencies, longer production cycles, and suboptimal resource utilization.
Solution:
The company partnered with us to execute a test drive of fully digitized production scheduling using Decision Intelligence. Leveraging our expertise and the Aera platform, we integrated SAP and other manufacturing databases to enable real-time data ingestion and processing. AI-driven decision agents analyzed constraints, such as labor availability, equipment capacity, material readiness, and order priorities, to generate automated shift and load plans.
Capabilities Delivered
Production Scheduling: Decision Intelligence agents dynamically adjusted schedules based on real-time constraints and priorities.
Data Integration: Seamless integration of SAP and other manufacturing systems ensured end-to-end visibility and data consistency.
Optimization: AI algorithms optimized shift planning and resource allocation to minimize delays and maximize throughput.
Outcomes:
- Increased production efficiency, resulting in higher throughput.
- Reduced manual scheduling errors
- Improved on-time order fulfillment rates
- Enhanced agility to respond to changing production requirements and order priorities.
- Freed up planners to focus on strategic production optimization instead of repetitive scheduling tasks.
The digitized production scheduling approach not only improved operational efficiency but also demonstrated the transformative potential of Decision Intelligence in complex manufacturing environments. The successful test drive laid the foundation for scaling these capabilities across the company’s global operations.
Challenge:
The client, a leading global lubricant manufacturer, struggled with fragmented demand planning across its multiple business units (BUs). The lack of a unified approach led to inefficiencies, inconsistent forecasts, and suboptimal resource allocation.
Solution:
The company implemented Aera Decision Intelligence to transform its demand planning processes. The solution provided a centralized platform that integrated data across BUs, enabling consistent and accurate forecasting. AI-powered decision agents automated the planning process, dynamically adjusting forecasts based on real-time data and market changes.
Outcomes:
- Increased forecast accuracy by, enabling better resource allocation.
- Improved profitability through optimized production and inventory management.
- Fostered collaboration and consistency across BUs.
- oEnhanced agility to respond to changing customer demands and market conditions.
By unifying and automating demand planning, the company achieved significant operational efficiencies, improved decision-making, and strengthened its market position.