Adopting software tools to optimize Sales Forecast and Production Planning can bring great benefits to your Company:
- Improved service level
- Reduced stock and purchasing costs
- Optimized seasonal stock and distribution of production and logistics resources
- Optimized stock levels for each branch and warehouse
- Propose sales forecast curves based on mathematical time series studies
- Reach consensus forecasts through progressive involvement of the entire sales network.
- Simulate and manage new product launches and item replacement, implementing phase-in/phase-out strategies
- Simulate and manage new markets, channels and customer scenarios
- Look at past and future commercial events, in order to improve forecast accuracy
- React to changes in sales volumes, to ensure continuous improvement of the forecasts
- Improved service level in relation to actual demand
- Stock costs reduction, through inventory reallocation
- Supply cost reduction, due to early planning options
- Optimized use of production and logistics resources
- Optimized seasonal inventory planning process
- Inventory reduction from lost sales
- Optimized production and stock planning with respect to individual sales points and/or distribution warehouses
Demand Management: The sedApta Suite tool to benefit from production planning
Demand Management is the sedApta Suite component capable of ensuring that important strategic advantages are achieved by optimizing demand and sales analysis and forecasting activities through its three modules:
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Allows time series creation based on survey catalogues that can be configurated thanks to features such as:
- Business event management.
- Customized aggregation level of time series
- Dynamic library of analysis algorithms.
- Various statistical error measurements.
- Automatic calculation functions of the algorithmic best fit for the time series considered with configurable parameters.
Allows manual data forcing actions at different aggregation levels. Forcing on forecasts allows users to better manage:
- Special events
- Storage and management of special event effects for their rescreening
- Prompt interventions on each data aggregation level
- Forcing on past events to drive the forecast
- Forcing on forecast values
- Trend analysis for the distribution of forced values at high level on lower levels
- Forecasting support for the introduction of new items/areas/customers/markets
- Cloning/editing/mixing of historical values.