- Analytics & Modeling - Predictive Analytics
- Platform as a Service (PaaS) - Application Development Platforms
- Agriculture
- Equipment & Machinery
- Quality Assurance
- Sales & Marketing
- Demand Planning & Forecasting
- Inventory Management
- System Integration
- Testing & Certification
Biobest Group is a global leader in integrated pest management, biological control, and pollination. The company provides a green alternative to pesticides by rearing beneficial insects and mites used by farmers to protect their crops against diseases and selling bumblebees for pollination purposes. Founded in 1987 and headquartered in Belgium, Biobest has 25 subsidiaries worldwide and employs 1,600 people. The company prides itself on providing tailored advice and technical support for farmers, with innovation and product quality at the heart of its activities. Biobest's mission is to be the most reliable supplier of bumblebees and crop protection products.
Biobest, a global leader in integrated pest management, biological control, and pollination, faced a complex challenge of balancing production capacity and demand. The company operates in an industry characterized by long production times of up to 16 weeks, fluctuating levels of demand, and variations in crop yields due to their biological nature. This created a complex balancing act between available production capacity and demand. The company was also grappling with the challenge of treating each subsidiary as a separate business entity, which led to disjointed operations and inefficiencies. Additionally, the company was heavily reliant on Excel-based forecast templates to collect information from customers and distributors, which proved challenging to keep up-to-date.
To overcome these challenges, Biobest implemented the Board Intelligent Planning Platform, a solution that unifies business intelligence, planning, and predictive analytics capabilities in a flexible, highly customizable environment. The platform enabled Biobest to create a holistic, integrated approach across the entire organization, replacing disparate spreadsheets and systems. The platform also automated administrative tasks, reducing workload. The implementation of the platform involved a five-stage process: initializing the process with system-built forecasts, collecting demand and available production capacity figures at a global level, aggregating and breaking down forecasts at different levels of granularity, allocating available production capacity to demand, and measuring and evaluating forecast accuracy. The platform also facilitated the fast sharing of accurate data throughout the business, improving efficiency and decision-making.
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