WORK_FORCE Domain

Use the WORK_FORCE domain to forecast workforce demand. It supports the following dataset types. For each dataset type, we list required and optional fields. For information on how to map the fields to columns in your training data, see Dataset Domains and Dataset Types.

Target Time Series Dataset Type

The following fields are required:

• workforce_type (string) – The type of work force labor being forecast. For example, call center demand or fulfillment center labor demand.

• timestamp (timestamp)

• workforce_demand (floating-point integer) – This is the target field for which Amazon Forecast generates a forecast.

The following dimension is optional and can be used to change forecasting granularity:

• location (string) – The location where the work force resources are sought. This should be used if you have multiple stores/locations.

Ideally, only these required fields and optional dimensions should be included. Other additional time series information should be included in a related time series dataset.

Related Time Series Dataset Type

The following fields are required:

• workforce_type (string)

• timestamp (timestamp)

In addition to the required fields, your training data can include other fields. To include other fields in the dataset, provide the fields in a schema when you create the dataset.

Item Metadata Dataset Type

The following field is required:

• workforce_type (string)

The following fields are optional and might be useful in improving forecast results:

• wages (float) – The average wages for that particular workforce type.

• shift_length (string) – The length of the shift.

• location (string) – The location of the workforce.

In addition to the required and suggested optional fields, your training data can include other fields. To include other fields in the dataset, provide the fields in a schema when you create the dataset.