View our 2024 Annual Report

About / Data Equity Statement

Data Equity Statement

We believe that data are important and are committed to being thoughtful about collecting, analyzing, using, and sharing data in alignment with our organization’s values which include our commitment to equity. Data processes involve bias based on our own identities and experiences.

Because of this, we commit to including diverse lenses to provide more robust collection, analysis, use, and sharing of data. Therefore, this is a living document that will change and evolve based on mistakes and growth in our own learning, as well as shifts in the broader field. We invite other individuals and organizations to consider how they might adapt our approach in response to their contexts and needs. This statement will guide our intent and actions when collecting, analyzing, using, and sharing data.

Data Collection

  • Prioritize and Center Those Most Impacted by Systemic Inequities, Especially Based on Race
    • Acknowledge and uplift the stated strengths, aspirations, and challenges of communities in data collection design and methodology
    • Consider the potential harm in how data are collected, considering factors such as power dynamics, historical contexts, and differences in lived experiences
    • Incorporate community input around data collection design and accessibility, elevating the input of those with lived experiences (especially those who have historically been negatively impacted by data collection methods)
  • Handle Data with Care
    • Establish a clear purpose for why specific data are being collected
    • Ensure participants are aware and consent to the collection of their data
    • Ensure participant data remains private when appropriate
    • Develop and share clear processes for saving and keeping data secure and confidential
  • Think Beyond Traditional Measures
    • Honor and collect data on lived experiences
    • In addition to quantitative data, collect qualitative data to provide a fuller picture, including street data
    • Acknowledge that there is no one singular approach to collecting meaningful data
  • Emphasize Accessibility
    • Collect only what is necessary and minimize the burden of collection
    • Use precise language and avoid jargon in data collection methods
    • Prioritize language accessibility, providing translation and interpretation where applicable

Data Analysis

  • Prioritize and Center Those Most Impacted by Systemic Inequities, Especially Based on Race
    • Analyze data with a focus on strengths, uplifting data that reflect positive attributes of communities instead of solely highlighting weaknesses or deficits
    • Whenever possible, engage those most impacted to make meaning of the data
  • Analyze with Transparency
    • Surface and acknowledge biases and limitations of those interpreting data and of methodology
    • Understand that collected data are influenced by systemic inequities
    • Document the contexts in which the data were collected

Data Use

  • Prioritize and Center Those Most Impacted by Systemic Inequities, Especially Based on Race
    • Transparently share plans for data use
    • Authentically listen to those who provided data and incorporate their feedback on how data are used
  • Use Data for Continuous Improvement
    • Use data as a reflection/self-assessment tool to gauge progress, determine areas of strength, and areas for improvement
  • Use Data to Advance Equity
    • Advocate for change, especially when it can directly benefit those most impacted
    • Proactively uncover and address systemic challenges that have a disproportionate impact on those historically marginalized

Data Sharing

  • Prioritize and Center Those Most Impacted by Systemic Inequities, Especially Based on Race
    • Incorporate community voice in structuring the data sharing process
    • Share data and analysis back with those who provided it
  • Share Data in Alignment with an Established Purpose/Goal
    • Communicate clearly where, how, and why the data are being shared
  • Consider Power Imbalances Between Those Who Provide Data and Those Who Receive Results
    • As a nonprofit funded by philanthropic dollars, explicitly state when there is tension or misalignment between the data required by our funders and our data beliefs and internal practices
    • Adopt a stance to advance equity and dismantle power imbalances when interrogating data-sharing strategies

We understand that this statement is a living document that can and will be modified to reflect our own continued learning. We acknowledge that we work within and alongside systems of oppression that can create tension between our data equity principles and their practical implementation. As a learning organization, we commit to consistently assessing how we adhere to these principles, knowing we will make mistakes and can always improve.

Download the printable version of the statement here.