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Data Request

Carbon GPT's Data Request feature simplifies the process of collecting emissions data from across your organization and supply chain, enabling more comprehensive and accurate carbon accounting.

Introduction

The Data Request feature provides a structured way to request, collect, and validate emissions data from internal teams and external partners. It streamlines the often complex and time-consuming process of gathering the data needed for complete carbon accounting.

Key Capabilities

Request Creation

  • Create customized data requests for specific emission sources
  • Define required data fields and formats
  • Set submission deadlines and reminders
  • Include guidance and context for respondents

Distribution Management

  • Send requests to internal teams and external partners
  • Track request status and response rates
  • Send automated reminders for pending submissions
  • Manage recipient lists and communication preferences

Data Collection

  • User-friendly submission forms for respondents
  • File upload capabilities for bulk data
  • Mobile-friendly interface for on-the-go submissions

Validation and Processing

  • Automated data validation and quality checks
  • Outlier detection and flagging
  • Data transformation and normalization
  • Approval workflows for submitted data

Getting Started

Setting Up Data Requests

  1. Navigate to the Data Request section in the main navigation
  2. Click Create New Request to start the setup process
  3. Select a request template or create a custom request
  4. Define the data points you need to collect
  5. Configure validation rules and quality thresholds

Managing Recipients

  1. Create recipient groups based on organizational structure
  2. Import contacts from your address book or CSV file
  3. Set up recipient permissions and access levels
  4. Configure notification preferences for each recipient

Customizing Request Forms

  1. Select from pre-built form templates for common data types
  2. Add custom fields and instructions
  3. Configure field validation rules
  4. Add supporting documentation and guidance
  5. Preview the form from the recipient's perspective

Using Data Requests

Creating a New Request

  1. From the Data Request dashboard, click Create New Request
  2. Select the request type (internal, supplier, one-time, recurring)
  3. Define the data collection period
  4. Select or create the recipient list
  5. Configure deadline and reminder settings
  6. Review and launch the request

Monitoring Progress

The Data Request dashboard provides real-time visibility into:

  • Overall completion rate
  • Individual response status
  • Data quality metrics
  • Submission timeline
  • Reminder history

Processing Responses

Once data is submitted:

  1. Review submissions in the Responses tab
  2. Address any validation flags or quality issues
  3. Approve or request revisions for each submission
  4. Export collected data or process it directly in Carbon GPT

Integrating with Emissions Calculations

Collected data can be seamlessly integrated with Carbon GPT's emissions calculations:

  1. Map collected data to emission factors
  2. Assign data to appropriate organizational units
  3. Include data in relevant reporting periods
  4. Track data provenance and quality metrics

Best Practices

Request Design

  • Keep requests focused and concise
  • Clearly explain why the data is needed
  • Provide examples of correctly formatted responses
  • Include contact information for support
  • Allow sufficient time for data collection

Recipient Management

  • Build and maintain accurate contact lists
  • Identify the right data owners in advance
  • Establish clear responsibilities and expectations
  • Provide training and support for first-time respondents
  • Recognize and reward timely, high-quality submissions

Data Quality

  • Define clear data quality criteria
  • Implement appropriate validation rules
  • Provide feedback on submission quality
  • Document data sources and collection methods
  • Establish a process for handling incomplete or questionable data

Process Optimization

  • Learn from each data collection cycle
  • Refine requests based on feedback and response rates
  • Automate recurring requests where possible
  • Develop a calendar for regular data collection
  • Align request timing with internal reporting cycles