Unlocking Potential: A Hierarchy of Data Needs for Nonprofits

Maslow’s Hierarchy of Needs builds upon a foundation of having all of our basic needs met before self-actualization.
Hierarchy of Data Needs

Nonprofit organizations are constantly pushed to do more with less for the communities that they serve. Data is an invaluable tool that nonprofit organizations can use to allow them to meet those needs. In an era dominated by information, nonprofits must harness the power of data to optimize their operations, enhance decision-making, and achieve their goals.

Today, every organization strives towards using artificial intelligence for decision making. However, it can be challenging for organizations to understand how to navigate from their current state of data capabilities to the artificial intelligence minded, data driven organization they want to become.

One framework to consider draws inspiration from Maslow’s Hierarchy of Needs to guide organizations through the stages of developing their data capacity. Maslow’s Hierarchy of Needs builds upon a foundation of having all of our basic needs met before self-actualization. This “Data Hierarchy of Needs” similarly builds upon meeting our basic data needs to empower us towards artificial intelligence. This hierarchy provides a high-level roadmap for organizations to consider as they grow towards becoming a data driven organization.

  1. Collect: Building the Foundation
    At the base of the Hierarchy of Data Needs lies the crucial step of collecting data. Nonprofits must establish a robust data collection strategy to gather relevant information about their operations, beneficiaries, and impact. It is important that you consider what data should be collected in relation to your organization’s mission, vision, and theory of change. This may include data points related to measures of impact and operations. Data collection can happen through a wide variety of means including survey collection, case management tracking, and open data sources. Effective data collection forms the bedrock for informed decision-making.  
  2. Move/Store: Creating a Solid Infrastructure 
    Once data is collected, you can address the second tier of the hierarchy: moving and storing the information securely. A well-designed data infrastructure ensures that data is not only stored efficiently but also easily retrievable when needed. Many organizations will start by storing data in a variety of Excel or Sheets files. That can be a great starting point but will lead to many data quality issues as your organization grows. It is important to establish a “single source of truth” for data. As your organization matures, you should consider a cloud-based storage solution that offers scalability and accessibility, allowing your organization to adapt to changing data volumes and ensure that your information is always available when required. 
  3. Explore/Transform: Transforming Raw Data into Insights 
    Next, you’ll begin exploring and transforming raw data into meaningful insights. You should invest in analytics tools and talent to derive actionable conclusions from your collected data. You could begin to do this with business intelligence tools such as PowerBI or by using open-source programming languages like SQL, R, or Python. This process involves cleaning and transforming raw data into a format that facilitates analysis. At this point you will focus in on descriptive analytics questions and begin building an understanding of the metrics that matter to your organization.  
  4. Aggregate/Label: Organizing for Cohesion 
    Building artificial intelligence solutions requires that your data is aggregated and labeled appropriately. In the aggregation and labeling stage, you should consolidate and categorize their data for easier interpretation and decision-making. Creating a standardized system of labeling and aggregating data ensures consistency across different datasets and facilitates the generation of comprehensive reports. This work helps form the baseline of training data that you might use to build an artificial intelligence solution later. It helps you to organize your information in a way that is not only accessible to team members but also aligned with your mission and objectives. 
  5. Learn/Optimize: Iterative Improvement 
    The Learn/Optimize level is where we begin to utilize more advanced analytics techniques. At this stage, your organization should begin to think like a scientist – generating and testing hypotheses that you can test with your data. You’re building simple experiments that you can validate with statistical testing or machine learning models and using that information to drive decisions at your organization. 
  6. AI: The Pinnacle of Data Empowerment 
    The pinnacle of the Hierarchy of Data Needs for nonprofits is the integration of artificial intelligence (AI). As organizations ascend the data hierarchy, they can leverage AI to automate tasks, predict outcomes, and unearth patterns that may not be immediately apparent. AI empowers nonprofits to work smarter, not harder, by automating routine processes and providing advanced analytics that go beyond human capabilities. Whether it's predictive modeling for fundraising campaigns or optimizing resource allocation, AI can propel nonprofits to new heights of efficiency and effectiveness. You may use pre-trained, pre-deployed models such as ChatGPT to enable this work or build custom tools to support it. 


    Conclusion: The Journey Toward Data Empowerment  

    The Hierarchy of Data Needs offers nonprofits a roadmap for advancing their data capacity and, in turn, their overall effectiveness. By systematically progressing through the stages of Collect, Move/Store, Explore/Transform, Aggregate/Label, Learn/Optimize, and AI, nonprofits can unlock the full potential of their data.


In an era where information is key, the ability to harness and leverage data effectively can be a game-changer for nonprofits striving to make a positive impact on the world. As organizations embark on this journey, they not only enhance their data capacity but also strengthen their ability to fulfill their mission and improve the lives of those they serve. Tech Impact’s Data Innovation Lab is focused on helping our nonprofit partners use data to improve their communities.

If you are interested in learning more about how Tech Impact's Data Lab can help you ascend the hierarchy of data needs, reach out to learn more.


Learn More About The Data Lab