Configuring Demand Planning for the first time to create a forecast - AWS Supply Chain

Configuring Demand Planning for the first time to create a forecast

You can create demand plans to forecast your inventory demand accurately across your organization.

Note

When you log into Demand Planning for the first time, you'll be able to view the onboarding pages that highlight the key features. This helps you to get familiar with the Demand Planning capabilities. Once Demand Planning is configured, you can view or modify the demand plan configuration settings under Settings > Organization > Demand Planning.

Note

Overrides are not allowed on the locked forecast periods. For more information, see Forecast lock.

The Enterprise Demand Plan is derived from single forecast configuration settings. Make sure that someone in your organization has used the following steps to complete the forecast configuration settings. If they have already been already set up by someone else in your organization, then you won't need to complete these steps. Instead, you will be directed to the Demand Planning page where you can start reviewing the forecast.

  1. Open the AWS Supply Chain web application.

  2. In the left navigation pane on the AWS Supply Chain dashboard, choose Demand Planning.

  3. On the Demand Planning page, choose Next.

    You can read through to understand what Demand Planning offers, or choose Next until you get to the Configure Demand Planning page.

  4. On the Configure Demand Planning page, there are five steps to configure Demand Planning.

    • Scope – Defines the dimensions and the time frame for Demand Planning to generate forecasts.

    • Configure your dataset – Defines the outbound_order_line dataset. This option is mandatory for Demand Planning to generate an accurate forecast. You also define how you want Demand Planning to handle negative quantity values in the outbound_order_line dataset. For more information about mandatory and optional Demand Planning fields, see Data entities and columns used in AWS Supply Chain.

    • Forecast Settings – Set global parameters to determine the forecast period, minimum forecast value, and initialization values for new products with no alternate data.

    • Scheduler – You can define how and when forecasts should be refreshed and published.

    • Organization Settings – Defines where your Demand Plans will be published. It also shows other configuration options within the application.

  5. Under Scope, Planning Horizon, select the following:

    • Time Interval – Select the time interval from the choice of daily, weekly, monthly, or yearly options. The time interval is used to aggregate and analyze data. Choose a time interval based on the nature of your business, availability, and granularity of historical data.

    • Time Horizon – Time horizon is the specific period for when a forecast is generated. The value should be a whole number with a minimum value of 1 and maximum of 500. The amount of historical data available also will dictate the Time Horizon. Make sure that at least one product in the outbound_order_line dataset has sales history at least four times the time horizon set. For example, if you set Time Horizon to 26 and Time Interval as weekly, the minimum order data requirement is 26*4 = 104 weeks.

    Under Forecast Granularity, Required Hierarchy, select the parameters to define your forecast hierarchy. Product ID attribute is mandatory and is automatically selected as the last level in the hierarchy. You can choose Add level to add additional hierarchy levels between product_group_id, product_type, brand_name, color, display_desc, and parent_product_id. Make sure that the required hierarchy attributes have information in the product dataset, because you can use these attributes to filter the demand plan.

    Under Optional Hierarchy, choose Add level to add up to five attributes from Site, Channel, and Customer to better manage your forecast. The supported columns from the outbound_order_line dataset are:

    • Site hierarchy = ship_from_site_id, ship_to_site_id, ship_to_site_address_city, ship_to_address_state, ship_to_address_country

    • Channel hierarchy = channel_id

    • Customer hierarchy = customer_tpartner_id

    Make sure that the required hierarchy attributes have information in the product dataset since these attributes are used to filter demand plans.

  6. Choose Continue.

  7. On the Configure your dataset page, under Configure Forecast Input, you should configure the required and recommended datasets.

    Note

    AWS Supply Chain recommends uploading two to three years of outbound order line history as an input to generate an accurate forecast. This duration allows the forecasting models to capture your business cycles and ensure a more robust and reliable prediction. For improved forecast accuracy, it is also recommended to include product attributes such as brand, product_group_id, and price in the product dataset.

    • Required Datasets – The outbound_order_line and product data entities are required to generate a forecast.

    • Recommended Datatsets – The product_alternate and supplementary_time_series data entities are optional. You can generate a forecast without these data entities but when provided, the forecast quality will be improved.

  8. Under Required Datasets, expand Historical Demand and choose Configure to set the negative value for missing data. outbound_order_line dataset is the primary source of historical demand.

    • Ignore – Select if you want AWS Supply Chain to ignore the products with missing order_date before creating the forecast.

    • Replace with zero – Select if you want AWS Supply Chain to replace the missing order_date fields with zero by default to the final requested quantity.

  9. No additional configuration is required for product data entity. Product attributes are used for filters, configure hierarchy, and for training the learning model.

  10. Under Recommended Datatsets, no additional configuration is required for product_lineage. You can use the product_alternate data entity to provide information on alternate or previous version of the product. For more information on product lineage, see Product lineage.

  11. Select Demand Drivers if you have demand drivers information such as promotions, price changes, and so on, you can use supplementary_time_series data entity to ingest data. You can select up to 13 demand drivers and configure aggregation and missing data filling strategy. For more information on demand drivers, see Forecast based on demand drivers.

  12. Choose Continue.

  13. On the Forecast Settings page, you need to configure the following:

    • Under Configure Forecast Start and End Date, enter the forecast start and end dates for New Product Introduction (NPI) and End-of-life EOL) products. For more information, see Product lifecycle.

    • Under New Product Initial Forecast, enter an initial forecast value for products with no demand history or product lineage to make the products searchable in the demand plan web application and to create a forecast. Specify the value and the periods to apply.

      Note

      The time period displayed will depend on the time period you chose under Time intervals in the Planning Horizon page. For example, if you chose Monthly under Time intervals, you will be able to specify the number of months before or after to start and stop the forecast, and for products with no demand history.

    • The planning cycle start date is based on the last order date in the outbound order line dataset. If the time interval configuration is:

      • Daily – Planning cycle start date will be the day after the last order date. For example, if the last order date is October 30, 2023, the planning cycle start date will be October 31, 2023.

      • Weekly or Monthly – When the last order date is the same as the time boundary, the planning cycle start date will be after a week or month. For example, when the last order date is October 29, 2023 (which is a Sunday and Demand Planning's week time boundary), the planning cycle start date will be October 30, 2023.

        When the last order date falls within the time boundary, Demand Planning will trim the order history for the last time window and create forecast from the new period. For example, when the last order date is November 01, 2023 (which is a Wednesday and not in the Demand Planning's week time boundary), the planning cycle start date will be October 30, 2023. Demand Planning will ignore the order history from October 30, 2023 to November 01, 2023.

    • (Optional) Choose Forecast Start Date if you want to override the default planning cycle start date and select a period in the past for back testing purposes.

      If the selected forecast start date is later than the outbound_order_line dataset end date, the default planning cycle start date is considered.

      If the selected forecast start date is before the outbound_order_line start date or if the length of the demand history is insufficient, the forecast will fail and display an error. For more information, see Prequisites before uploading your dataset.

      It is recommended to select the first of the month for monthly intervals or Monday for weekly intervals. If you choose a different date, Demand Planning will automatically adjust to the nearest default date. For example, if you selected Wednesday as the forecast start date, Demand Planning will select the next Monday as the forecast start date for weekly intervals. Similarly, selecting May 10th 2024 will result in June 1st 2024 as the planning cycle start date for monthly intervals.

  14. Choose Continue.

  15. On the Demand Plan Publish Scheduler page, under Recurring Forecast Runs, setup the forecast recurring cycle. Manual is the default Demand Plan publish schedule option. When you select Manual, you have to manually enter the planning cycle. Under Forecast interval, choose how you would like to setup the forecast. Choose Auto for AWS Supply Chain to automatically start the next planning cycle.

    If you choose Auto, you will see when your next forecast plan will be published on the Demand Planning page.

  16. Choose Continue.

  17. Under Configure Enterprise Settings, note the Amazon Simple Storage Service (Amazon S3) path where the demand plans are published.

    Note

    You can also find the Amazon S3 path for the published demand plans on the Settings page. For more information, see Modifying Demand Plan settings.

  18. Choose Complete.

    The Enterprise Demand Plan page displays. To start using Demand Planning, choose Create Forecast.

    Note

    Forecast is generated only when you ingest data into AWS Supply Chain. Make sure that all the required and optional attributes that you chose have information in the dataset.

After you set the forecast settings, you can generate the forecast and demand plan for the time horizon that you set. On the Enterprise Demand Plan page, choose Create Forecast.