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Demand Forecasting and Smart Inventory Allocation: The Bolian Case Study
Bolian

COMPANY

Bolian

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COMPANY

Bolian

“The project with Holistic has helped us bring structure and optimization to a critical part of our daily operations. Being able to clearly define which products should be stored in Autostore and which in the conventional warehouse has made our workflow much easier and has increased stability in order fulfillment. Additionally, the API integration makes the solution truly practical for everyday use. It has been a very positive collaboration with a direct impact on warehouse efficiency.”

Eugeni fibla
Eugeni Fibla

Partner – Bolian by Akoma

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Bolian

Bolian (www.bolianlogistics.com) is the e-commerce logistics company of Grupo Akoma (www.grupoakoma.com), specializing in the preparation and fulfillment of multi-SKU orders, with a high volume of activity primarily driven by subscription-based e-commerce operations. This type of operation creates a dynamic and constantly shifting demand, with significant fluctuations throughout the lifecycle of each collection or subscription, requiring highly precise planning of both resources and available inventory.

From an operational standpoint, Bolian operates a hybrid warehouse model that combines a conventional production area, where manual picking takes place, with an automated and robotic zone powered by the Autostore system. This integration of manual and automated environments improves order fulfillment efficiency, but also introduces additional complexity in inventory management, as it becomes critical to determine how much of each product should be allocated to each system based on forecasted demand and outbound flow.

Project Scope

The project originated from Bolian’s need to optimize its warehouse operations and ensure stable daily output in an environment where manual and automated processes coexist. Variability in demand across collections, combined with the mismatch between fixed shipping capacity and variable picking capacity, was creating operational imbalances that impacted overall efficiency.

In response, Holistic proposed the development of an analytical solution to more accurately estimate future product outflows and determine how inventory should be allocated between Autostore and the conventional warehouse at any given time for each incoming product. The project focused on building a model capable of supporting these decisions and integrating seamlessly with operational systems for real-time access.

Project Description

Para dar respuesta a esta necesidad, Holistic desarrolló junto a Bolian un modelo analítico orientado a estimar de forma dinámica la demanda futura de cada producto y determinar la configuración óptima de stock entre Autostore y el almacén convencional.

La solución se basó en un proceso que corrige periódicamente la previsión inicial realizada por el equipo de marketing de Bolian, y a partir de las ventas reales observadas, ajustar la curva de demanda y mejorar la fiabilidad de las estimaciones.

A partir de esta demanda corregida, el modelo calcula mes a mes y día a día cuántas unidades deberían ubicarse en cada sistema, proporcionando un valor óptimo por producto para los siguientes ciclos operativos. Finalmente, la solución fue operativizada mediante una API que permite consultar en tiempo real el stock recomendado en Autostore para cada referencia, integrándose en el entorno tecnológico de Bolian y facilitando su aplicación directa en las operaciones diarias.

Results

The implementation of the model enabled Bolian, for the first time, to rely on a quantitative and dynamic framework for deciding the optimal distribution of inventory between the conventional warehouse and the Autostore system. By continuously adjusting demand forecasts based on real sales data, the company improved the accuracy of its outbound projections and gained greater visibility into its operational needs.

The integration of the solution via API allowed real-time access within the operational environment, ensuring that product allocation decisions were based on up-to-date forecasts rather than static rules. As a result, Bolian achieved:

  • Greater stability in order preparation and dispatch.
  • More efficient inventory management, reducing the risk of stockouts and overstocking.
  • Improved coordination between conventional and automated warehouse operations.

All of this translates into faster and more reliable service for their customers, while also laying the groundwork for future operational improvements.

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