Enhancing Forecast Accuracy with Predictive Analytics & Data Lake Architecture

A high-growth company faced forecasting inaccuracies, inventory shortages, and disconnected data systems. With sales increasing 70%+ annually, the company st...

The Challenge

A high-growth company faced forecasting inaccuracies, inventory shortages, and disconnected data systems. With sales increasing 70%+ annually, the company struggled to predict demand, optimize inventory, and provide leadership with forward-looking insights. The result was a persistent 20% backorder rate and excess inventory costs.

Our Approach

Agema Labs developed and implemented a predictive analytics framework and enterprise data lake to:

  • Integrate 10+ critical data sources – Unified ERP, finance, Google Analytics, e-commerce, and operational data into a centralized data lake.
  • Deploy predictive sales analytics – Built real-time dashboards to provide executives with forward-looking business visibility.
  • Optimize inventory and production – Leveraged seasonality trends to predict inventory and consumer sales within 10% accuracy for the following year.
  • Automate forecasting and production planning – Transformed demand data into actionable production schedules, reducing inefficiencies.

    • Impact

    • Completely eliminated backorders after seven years of persistent 20% backlog.
    • Optimized inventory levels, reducing excess stock while meeting demand.
    • Enabled 70%+ annual sales growth without operational bottlenecks.
    • Provided executives with real-time forecasting, improving strategic decision-making.
    "

    In the year after we started work with Agema Labs, we saw a 70.7% increase in gross revenue and a 47.1% increase in net profit. We have real-time data for decision making and overall our operations and systems will enable us to keep up the pace for the foreseeable future.

    Brian Wurts

    CEO

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