MarginPar
Marginpar has been producing unique cut flowers for over 30 years, resulting in a wide range of more than 100 summerflower varieties that are recognized for originality and quality. With multiple farms of their own in Kenya, Ethiopia, Tanzania, and Zimbabwe and the benefit of diverse climates they’re able to grow flowers year-round.
The Situation
Known for their demand-driven approach, Marginpar continues to lead with innovation in their operations. From developing a comprehensive Digital Experience Platform (DXP) to experimenting with AI-driven imaging for crop monitoring, the company is constantly seeking new ways to align production with customer needs.
The Challenge
For a demand-driven model to function effectively, accurate forecasting is essential, especially across multiple regions, varieties, and growing conditions. Marginpar needed a structured, scalable way to generate consistent forecasts that would support both short-term planning and long-term strategy.
How Lima came in
Lima was engaged to enhance forecasting accuracy across all flower varieties. Through its Yield Predict solution, Lima introduced snapshot-based, automated forecasting, moving the team from manual estimations to a more scientific and data-led approach.
The Results
-
Achieved 90% forecast accuracy across varieties
-
Improved alignment between supply and demand
-
Reduced forecasting errors and operational overhead
-
Contributed to increased revenue and more efficient resource planning
-
Strengthened Marginpar’s broader innovation roadmap with a reliable forecasting layer
Over four years of collaboration, Lima has become a trusted partner in helping Marginpar scale their demand-driven ambitions with confidence.
