CHALLENGE

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Outdated analytics models and limited data visibility were driving inefficient inventory management and increasing working capital requirements.

The existing approach lacked alignment with industry standards and offered little flexibility for business inputs, making it difficult to respond to changing demand patterns. Without a proactive system or real-time visibility, teams were unable to identify risks early, leading to excess inventory and poor capital utilization.

• Legacy analytics models not aligned with industry standards
• No proactive system for managing inventory decisions
• Limited visibility into inventory data and performance drivers
• Lack of user-controlled inputs for scenario planning
• High risk of excess inventory and elevated working capital

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SOLUTION

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Aligned Automation developed a fully digitized, statistical model-driven application to modernize inventory planning and enable data-driven decision-making.

The solution aligned with industry standards and introduced advanced analytics to improve forecasting accuracy, identify anomalies, and optimize inventory levels. Enhanced data granularity and configurable inputs allowed teams to adjust models based on real-time business conditions.

Key capabilities included:

• Statistical modeling for demand forecasting, outlier detection, and data smoothing
• Alignment with industry standards such as APICS for inventory calculations
• Enhanced data granularity from monthly to daily insights
• Configurable inputs for flexible, scenario-based decision-making
• Standardized mapping of pipeline networks and value streams
• Advanced analytics to identify trends, risks, and optimization opportunities

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What Changed

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Inventory management evolved from reactive and model-constrained to proactive and insight-driven.

The organization gained greater visibility and control over inventory decisions, reduced excess stock, and improved working capital efficiency through more accurate, data-driven planning.