A mid-sized global bicycle manufacturer had no AI or data science function and relied entirely on manual processes for sales and marketing, demand forecasting, and inventory management.
Leadership recognized AI’s potential but had no internal precedent or roadmap for adoption. The company faced costly inefficiencies including overproduction risk, stockouts, and missed market opportunities, with no clear starting point for change.
MoD+M identified 30+ AI use cases through stakeholder interviews, narrowed to seven high-impact priorities with ROI estimates, then deployed AI-powered customer segmentation via Databricks, time-series demand forecasting models built in-house, and a third-party OpenAI-powered customer service tool.
ML models identified high-value customer groups with greater precision, enabling more targeted marketing campaigns and improving conversion rates, directly boosting revenue.
Time-series forecasting algorithms improved production planning accuracy, reducing the risk of costly overproduction and stockouts and giving leadership data-driven confidence in inventory decisions.
AI-powered SKU optimization identified redundant product lines without sacrificing demand coverage, delivering direct cost reductions for the company’s retail operation.
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