Tip #1: Start with your key business questions.
Boards and executive leaders have lots of questions and often 'instincts' that come from years of experience. This level of the organization needs space and time to work from questions that are just 'fishing in the data' to identify what will have real impact and strengthen their decision making. It requires constraint, discipline, and critical reflection to hone these questions into what is essential for an organization to know that drives their mission forward and your vision into greater value for your members.
Tip #2: Use data for both operational efficiencies and new product development.
Strive to build a good data feedback system, leveraging your own internal systems data (from your AMS and other applications), your member feedback channels (i.e., participation surveys and member support conversations), and any vendor or other service expertise providers. This will help you lean into what is working and away from what has 'seen' its day. This allows you to
make targeted strategic decisions when products are not serving the members rather than just across the board budget cuts that may choke off new development.
Tip #3: Develop and define metrics.
Metrics help us measure
something but they are not always apparent and need development. Sometimes it requires data transformation, recombination, or even a way to conduct adequate comparisons. Strong comparison data points can be generated internally (i.e., last quarter, year, pre-pandemic) or externally such as using other similar association data, state, or federal sources. It is important to look for those activities that you can adequately count and visualize and then apply the results to your decision-making process. Data needs to be used in context with what executive and association staff know from their experience and member conversations.
Tip #4: Invest in talent.
Consider as part of your strategy identifying and
acquiring the right kind of talent to help do this work. In my experience, associations need to have a dedicated data analyst to help compile and make sense of the data. Analysts should be able to apply standards of data quality, understand statistical techniques, and create data visualizations to strengthen the data storytelling presentation when answering key questions. Resist the temptation to get it 100% accurate because the extensive effort may preclude important decision making. As the French philosopher Voltaire reminds us, "don't let the great be the enemy of the good."
Finally, noted futurist Bernard Marr promotes this work by saying that "[data strategy] can help you gain valuable insights into market trends, customer behavior and operational performance." Developing a thoughtful plan, creating feedback loops, and hiring the right talent can make a lot of difference.