Introduction
In the era of data-driven business decisions, predictive capabilities are no longer a luxury — they are a necessity. For companies operating in Japan, where precision in planning is vital for optimizing lean inventory practices and financial forecasting, Microsoft Dynamics 365 Business Central offers an advanced Forecasting API that delivers significant advantages. At Sysamic, we specialize in helping Japanese businesses unlock the full potential of Business Central, and integrating forecasting capabilities is a key part of that transformation.
What is the Forecasting API in Business Central?
The Forecasting API, also known as the Time Series API, enables Business Central users to predict future outcomes—such as inventory requirements or cash flow—based solely on historical, time-sequenced data. This is particularly relevant in the Japanese market, where seasonal trends, production schedules, and supply chain timelines must be precisely managed.
Unlike other models that require a complex set of variables, this API focuses on time-ordered records, making it accessible and powerful. Given that over 30% of tables in Business Central have date and numeric fields, Japanese businesses already have the foundational data needed to generate insights.
How It Works: Forecasting Model and Input Requirements
The Forecasting Model uses R-based statistical algorithms to evaluate historical trends and project future values. Here’s how it breaks down:
GranularityAttribute: For example, the “Item No.” in Japanese inventory systems can be grouped with location or variant codes for more localized forecasting.
DateKey: Represents consistent time periods (e.g., 月ごと for monthly).
TransactionQty: Reflects quantities sold or cash flow totals—critical for Japanese inventory and finance departments.
The model’s parameters allow deep customization:
Horizon defines how many future periods to forecast.
Seasonality adapts to Japan’s unique fiscal and seasonal cycles, such as April-March accounting years or seasonal peaks in retail.
Forecast_start_datekey and Confidence_level allow precision control over timing and certainty, ideal for Japanese risk-averse planning cultures.
Time_series_model options like ARIMA, ETS, and TBATS enable tuning for specific data patterns.
Output and Business Use Cases in Japan: The output includes forecasted quantities and sigma (variance), offering a probability range—a critical feature in Japan’s meticulous business planning.
For example, if you forecast 100 units of product demand with a sigma of 10 at 95% confidence, it provides decision-makers with a practical range of 90–110. This is especially useful in industries like manufacturing, distribution, or retail where overstocking or understocking carries significant cost and reputational risks.
Why Forecasting Matters in the Japanese Business Context
In Japan, where operational efficiency and precision are critical due to high customer expectations and lean supply chains, forecasting can make a significant difference. Consider these local use cases:
Inventory Optimization: Avoid overstocking or stockouts by forecasting product demand at the SKU and location level.
Cash Flow Visibility: Predict receivables and payables with greater accuracy, helping finance teams plan ahead with confidence.
Production Planning: Leverage seasonality models tailored to Japanese market trends, such as Golden Week fluctuations or year-end sales surges.
By adopting a forecasting model that supports local business nuances, companies in Japan can stay competitive and agile, even in uncertain market conditions.
Key Features of the Forecasting API
The Forecasting API supports various statistical models including ARIMA, ETS, and TBATS, ensuring adaptability across industries and data types. Its major capabilities include:
Time Series Forecasting: Generate forecasts using historical patterns in a consistent time interval (e.g., monthly, weekly).
Bulk Processing: Handle large datasets for multiple products or locations in a single request.
Confidence Levels: Quantify forecast accuracy and reliability through confidence ranges.
Seasonality Controls: Define typical business cycles—quarterly, monthly, or even weekly—to improve prediction quality.
For example, a manufacturing business in Osaka can analyze 12 months of production data and predict demand for the next quarter, factoring in seasonality such as rainy-season slowdowns or peak periods in the retail calendar.
Business Central and Sysamic: Simplifying Forecasting for Japanese Enterprises
As a trusted Microsoft partner based in Japan, Sysamic helps organizations unlock the full potential of Business Central by tailoring forecasting tools to local market needs. Whether deployed via Microsoft’s managed resources or through custom Azure environments, we ensure smooth setup and localization for Japanese enterprises.
We also support businesses in selecting the right forecast model, defining the appropriate time intervals, and visualizing results in Power BI dashboards or within Business Central itself.
The Sysamic Advantage
Implementing forecasting is not just about technology—it’s about business impact. Sysamic’s localized expertise ensures:
Accurate forecast configurations aligned with Japanese fiscal calendars.
Seamless integration into Business Central environments already used by Japanese SMEs and large corporations.
Ongoing support and refinement of models as your business evolves.
Ready to Future-Proof Your Business?
Whether you’re in retail, manufacturing, or services, now is the time to leverage forecasting capabilities built directly into your ERP. Let Sysamic guide your Business Central transformation and turn historical data into a roadmap for growth.
Contact us today to explore forecasting solutions customized for the Japanese market.