Forecast BI 'Tsunage Mon Simulator' that Breaks Through the Limits of Excel

basic information

**Three Strengths of the Simulator** 1. Machine learning models optimized for your company’s data Unlike general forecasting tools, we build dedicated models that fully learn your unique production capacity, lead times, and cost structure. 2. Automatic detection of bottlenecks When you input your target sales, the system proactively identifies future bottlenecks, such as "the second warehouse will run out of storage space in three months." 3. User-friendly dashboard for management Complex calculation results are displayed in easy-to-understand graphs, such as profit margins and utilization rates. You can also compare "Plan A" and "Plan B" with just one click.

Price information

The costs for building the system environment and providing ongoing support will be estimated based on the amount of data and requirements we receive. *Instead of immediately implementing the system, it is possible to start with a one-time "trial analysis report" using past data.

Delivery Time

※【Implementation Steps】1. Trial Report (Spot Analysis) ➔ 2. Construction of Simulator Environment ➔ 3. In-house Operation and Support

Applications/Examples of results

【Expected Uses and Implementation Effects】 ■ Supply Chain and Logistics Load Forecasting - Before Implementation: It was difficult to know how much load would be placed on manufacturing and logistics until just before launching a new product, leading to exhaustion. - After Implementation: High-precision demand forecasting, combining past sales data with external factors, allows for resource optimization in advance. Shifting from intuition-based management to data-driven management. The simulator presents the safest and most profitable routes.

Detailed information

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  【STEP1】Breaking Away from the Limits of Excel Forecasting We will systematize forecasting tasks that are too complex for Excel's formulas to handle, due to factors such as the establishment of new factories, rapid fluctuations in demand, and personnel shortages. By inputting your company's actual operational data, such as unique "production capacity," "lead time," and "cost structure," we will build a foundation (model) for high-precision simulations.

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  【STEP2】Dynamic Simulation Based on In-House Data Based on the input data, we will build a "forecast model" on the system that calculates the correlations between sales, costs, and resources. By simply changing variables on the dashboard, such as "What if the delivery of materials is delayed by one week?" or "What if the sales of our main product suddenly double?", the results can be recalculated instantly to see how they fluctuate. This allows for safe testing before making potentially catastrophic mistakes in the real world.

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  【STEP3】Identify Future Bottlenecks in Advance Complex calculation results are output as a dashboard that management can intuitively understand, including metrics such as profit margins and utilization rates. Furthermore, the system automatically points out future bottlenecks (risks), such as "the second warehouse will be overwhelmed in three months if things continue as they are." This strongly supports safe and reliable management decisions based on data and evidence, rather than relying on "intuition and guts."

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