Many associations have a love/hate relationship with data and research. While recognizing its importance in providing insights for decision-making, staff may also feel overwhelmed by the challenge of collecting, understanding and interpreting the key information.
However, incorporating a data strategy into your management approach does not need to be difficult or expensive. It does require forethought, planning and sensitivity to the organization’s culture around decision-making.
By focusing on where you are in your data maturity journey, you can take steps to transform your data practices and maximize their impact.
Data is widely available to individuals and organizations. It can be gathered inexpensively from a myriad of secondary sources, such as government statistical portals, social media and universities, or your association’s database. You can also directly collect data to answer specific questions through surveys or interviews with your audience. Most associations tap into one or more of these sources.
Along the path to data maturity, associations typically fall into one of three stages:
Each stage presents unique challenges and opportunities for improvement.
The Association Data Maturity Model provides an overview of these stages, highlighting their key characteristics and the shifts required to move toward a fully data-driven approach.
This transition requires aligning data practices with goals, building trust in data, and fostering a culture of reliance on evidence-based decision-making.
Associations in this stage conduct research tied to specific projects or needs. While they value data, their use can often be inconsistent or siloed.
Common traits:
The challenge for data-informed associations is creating a cohesive, strategic approach to data to maximize its value.
Associations in this stage rely on empirical evidence for decision-making, supported by significant investment in infrastructure, expertise and governance.
Common traits:
These organizations understand the value of measuring what matters and using those insights to drive meaningful outcomes.
Advancing data stages requires aligning three elements: stakeholder input, a research strategy and consistent data collection.
Reaching the data-optimized stage requires intentional investments and a clear focus on three critical areas: people, processes and technology. Each plays a role in transforming your association’s approach to data:
One of the biggest challenges associations face in becoming data-optimized is understanding where they currently stand. Leadership and staff often struggle to evaluate their organization's data maturity, especially when different departments operate with varying levels of data sophistication.
What feels like a data-optimized approach in one area might mask significant gaps in others.
To bring clarity to this assessment, start by examining these fundamental questions about your organization's relationship with data:
Answers to these starting questions often reveal unexpected insights about your data maturity—like discovering your membership team relies heavily on analytics while other departments rarely consult data. You might also find that you have a robust data collection system paired with low team confidence in data interpretation. Identifying these gaps is a positive step that helps focus efforts toward these key indicators of a data-optimized organization.
Signs of a Data-Optimized Strategy:
Becoming data-optimized is about cultivating a mindset that puts data at the center of decisions. By assessing your current state of data maturity and taking intentional steps forward, your association can maximize its research efforts to make informed decisions that drive success.
Access the Data Maturity Model for Associations.
Are you interested in creating or revitalizing your association’s research and data strategy plan? Get in touch to learn more and find out how we can help deliver a research solution that works for you.