Demand Planning
Demand Planning is a multi-step operational process that is essential for a company to create a reliable supply chain forecast. Effective demand planning can increase the accuracy of revenue forecasts in tactical, operational, and strategic business plans.
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Key Stages
Methods
Classical forecasting
To ensure the accuracy of your forecasts Olapsoft provides multiple classiacal forecasting methods:
- Linear and non-linear regression;
- Simple moving average;
- Hyperbolic regression;
- Variations of exponential smoothing;
- Croston method;
- Auto-regressive integrated moving average models (S)ARIMA(x).
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Use Cases
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Marketing events planning
✓ Trade promotions. Compare different trade promo strategies and budgets, raise promotion plan accuracy. Maximize your promotion plans effectiveness.
✓ New product launches. Build a granular forecasting model to see what pirce would be most advantageous for different market segments in different regions.
✓ Store openings. Compare different possibilities taking into account wide range of influencing factors.
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Key Features
✓ Creating a multi-week statistical forecast based on a defined-week grouped calendar.
✓ Flexible time intervals for the demand and forecast period, allowing you to view the forecasts in days, weeks, months, fiscal quarters, calendar quarters, etc.
✓ Options to analyze historical demand data for each combination of product and location to determine the appropriate class of demand (e.g. seasonal, unseasonal, volatile or irregular).
✓ Selecting the most appropriate model from the group of algorithms and separating normal demand from advertising or unusual demand streams.
✓ Seasonality and trend analysis.
✓ Options to forecast in alternative units of measure (cost, price, cases, global sales unit, weights and sets).
✓ Demand forecasts can be adjusted to anticipated supply based on the latest supply chain planning capabilities.
✓ Allows users to easily import and export data from/to database and/or external data sources
✓ The power to create different scenarios and forecasts, then to compare them to one another.
✓ Identify and mark as exceptions the forecasts exceeding the parameters set by the user.
✓ Allows users to create scenarios using various parameter settings to understand how changes in such parameters (forecasted product price, expected growth) affect the organization’s forecast, stock position, revenue, and profit.
✓ Users can manually adjust demand history by exception so that demand anomalies (e.g. promotional) may be removed from the data to ensure statistical validity.
✓ Ability to add new statistical algorithms/models.
✓ Provides cross-functional capabilities to view forecasts in different divisions or at various levels of hierarchy within an organization.
✓ Forecasts across hierarchy levels (distribution center level, plant level, market level, customer level, product level).
✓ Generation of sales and operations planning reports with the option to conduct operational planning via “what-if” scenarios.
✓ Introduction of new production and option to phase-in and phase-out at the end of life, identifying similar elements and planning based on historical patterns.
✓ Classifying and grouping similar products into multiple categories (statistically significant, slow/no action/highly volatile) and applying different forecasting techniques to them.
✓ Tracking and monitoring of forecast accuracy shifts with varying lag times.
✓ Users can analyze order structure for each customer to determine the proportion of monthly or weekly forecasts in derived or estimated daily level forecasts.
✓ Exception management reports and alerts to inform the demand planner of any anomalies, outliers, abnormal patterns or trends.
✓ Long-term demand forecasts are used and developed as the product lifecycle ensues.
✓ Development, maintenance, monitoring, and evaluation of business plans, replenishment programs and forecasts.
✓ Synchronizes production, replenishment, forecasting and promotion plans throughout the extended network.
✓ Supports end-to-end planning and execution workflows, including sharing of orders, forecasts, logistics, inventory, and capacity.
✓ Power to define approval step workflow in the context of collaborative planning processes.
✓ Real-time data entry (cancelled orders, unusually large and/or unexpected orders, shipment notifications) are used to adjust expected demand.