In July 2026, Japanese company Calbee announced the development of a supply-chain simulation and optimization system called C-BOSS, short for Calbee Business Optimization Simulation System. The system combines data distributed across the company’s departments and various operations for use in simulating the entire supply chain, helping the company make optimization decisions at the corporate level rather than handling each part separately.
The project is significant because of the nature of Calbee’s business. Founded in 1949, the company produces potato chips and other snacks, including products such as “Jagarico.” The company relies on a supply chain affected by potato-growing seasons, production regions, and weather conditions, while the needs of factories, products, and markets change over time.
A Supply Chain That Is Difficult to Manage Using Traditional Methods
Calbee uses potatoes grown in Hokkaido in a cycle that extends approximately from the harvest season through the following spring, with the crop stored and used in stages. A new supply cycle then begins, involving different sources and regions. This sequence makes raw-material management more complex than simply matching demand with production, because crop quality and timing, as well as storage conditions, affect subsequent decisions.
The company also handles more than 1,000 inventory and product units, according to the material, in addition to differences in factory capabilities from one product to another. Snack-food demand varies according to seasons, campaigns, and new products, while the products’ shelf life does not allow inventory to be increased without limit. Therefore, a decision to shift production or adjust inventory at one location may affect other factories and operations.
From Separate Data to a Unified Decision
Before developing C-BOSS, departments collected data and responded to changes independently. Calbee believes that this approach makes it more difficult to make comprehensive decisions, particularly when demand or supply conditions change simultaneously. The new system aims to establish a mechanism for evaluating the impact of decisions across the entire network and then selecting a plan more consistent with the company’s objectives.
In 2023, the company began forming a team responsible for integrated operations and supply-chain planning within the S&OP framework. After comparing ready-made tools and other options, it chose to develop the system internally. The company stated that off-the-shelf package tools were not sufficient to address the unique characteristics of the potato supply chain or its needs related to optimizing operations across departments, and that it also wanted to retain greater flexibility in developing the system.
Why Does This Development Matter?
C-BOSS’s role is not limited to automating a single planning step; the project’s core value lies in linking raw-material, production, inventory, and distribution decisions within one model. For Calbee, this may help reveal the effects of a decision before it is implemented, rather than relying on subsequent problem-solving. However, the material does not provide figures on savings, improvements in forecast accuracy, or the full scope of implementation, so the system’s commercial results cannot yet be measured.
The project represents an example of using artificial intelligence and simulation to manage complex industrial operations, where the problem lies not only in a lack of data but also in its distribution among units and the difficulty of converting it into a shared decision. Calbee’s experience shows that developing a customized tool may be the preferred option when decisions are tied to operational characteristics that general-purpose software does not cover.