The Issue: Complex, Effective Forecasting
The ability to more accurately forecast customer demand directly translates to improved and more predictable financial and supply chain performance, reducing your inventory, expediting and over-time costs, while improving customer service.
Accurate forecasting is the key driver of your supply chain allowing better production planning, improving fill rates, and anticipating demand opportunities. Having an accurate forecast is especially key today as supply chains grow more complex and customer behavior becomes increasingly demanding. So, how can you effectively develop a forecast that best reflects the true demand picture, taking into account all the influences on your demand?
The Solution: Demand Forecasting
Oracle’s® JD Edwards EnterpriseOne Demand Forecasting enables you to efficiently develop a statistically based forecast to predict and plan your future demand. You can use your sales history and other types of time series data to generate statistical forecasts. Complex demand patterns, trends, seasonality, intermittent demand, and demand shifts are identified by using different statistical models, such as exponential smoothing, ARIMA, and Croston’s intermittent. The adaptive best-fit model selection forecast engine analyzes and compares the various models to dynamically produce a more accurate forecast your business. A graphical user interface gives you the flexibility to visualize your information in various ways to better understand key issues.
With Oracle® JD Edwards EnterpriseOne Demand Forecasting, you have the ability to easily analyze and model your enterprise on an ongoing basis. The flexible hierarchical data structure lets you organize and secure your data to fit your business. For example, you define such key relationships as product hierarchies, geographical organizations, customer types, and sales channels.
As your business structure changes, you can adapt the model quickly and easily to add new products, change territories, restructure product groupings, and add or
change channel partners. Product lifecycle planning lets you easily plan the demand for new products while other products are phased out. Robust calendaring lets you choose a wide range of forecasting “buckets” needed for your business: weekly, monthly, quarterly, for various fiscal quarters, and annually. The system uses the statistical variance in your demand in conjunction with lead-time and desired service level to recommend optimum safety stock levels.
With scenario analysis, you can focus your time and attention on specific parts of your business, creating different forecasts to reflect different scenarios. If, for example, you’ve just entered a new market, you might want to create optimistic and pessimistic scenarios for comparative analysis before committing to a certain forecast.
Demand Forecasting with Advanced Forecast Modeling
For complex, multifaceted forecasting, additional functionality is available through a supplementary product offering. With Oracle® JD Edwards EnterpriseOne Advanced Forecast Modeling, past promotions and other forecasting events are statistically identified and analyzed to determine their impact on your demand.
Additionally, multiple external factors, such as demographics and consumer price index, can be evaluated. Consequently, you can better understand the effectiveness of your promotions and campaigns to predict future demand more successfully.
- Key Features
- Automatic Best Fit statistical model selection & user-defined selection
- Multi-dimension, multihierarchy and multi-level forecast aggregation
- Scenario management for comparing statistical fit of forecast models
- Dynamic conversion rates for multiple units of measure (including currencies)
- Queries for forecasting by attribute(s)
- Optional module for causal and predictor modeling to plan events
- Memory-resident object oriented database for fast data synchronization and quick implementation
- Robust backwards compatible import/export format
- Integrated with Enterprise One via the Supply Chain Business Modeler (SCBM)
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