Actionable Approaches to Becoming a Data-Driven Organization

When speaking to association executives and industry partners, I love to quote the following from Nate Silver’s book, The Signal and the Noise:  Why So Many Predictions Fail—but Some Don’t.

“The numbers have no way of speaking for themselves. We speak for them.”

Silver, often recognized as one of the country’s leading statisticians, makes an interesting point:  The value of data analysis has as much, if not more, to do with individuals and their approach to the data analysis than it does with the actual numbers and the computations themselves. 

And why is this nuance important to associations?  Because if associations are to stay ahead of the ever-increasing, if not overwhelming, amount of demographic, financial, historical and social data created by their members and prospects and turn this data into actionable insights, they need to focus less on data itself and more on the “strategy” and actual decision-making.  (And then, leverage the appropriate technology to simplify the ability to make smarter decisions.)

Where to Begin?

For associations to become a data-driven organization and realize the full benefits of analyzing and leveraging their data to meet member recruitment, engagement and retention initiatives, they need a strategy, specifically a data analytics strategy, which includes the following elements:

  • Ongoing Strategic Business Initiative 

    To maximize the effectiveness of the association’s data analytics strategy, organizations should view the initiative as a long-term and ongoing commitment versus a project with a timeline.  There is no start date or end date to one’s strategic data analytics strategy.  The ongoing collection, measurement, analysis and overall health of the association’s data (arguably one of its most valuable assets) is a never-ending initiative the entire association must commit to.  And, it is never too late to start.

  • Measure & Evaluate (...repeat)

    Identify a few carefully selected metrics that represent a specific business problem the organization would like to address.  For example, registration for the annual conference is down 3%. Why? Once the specific data initiative in our analytics strategy has been completed, measure the same metric.  Did registration for the annual conference increase, decrease or stay the same?  Ongoing analysis helps measure the ROI (return on investment) of specific data analytics initiatives.  As the association becomes more comfortable with their ability to analyze and visualize their data, they should consider adding external data sources and identify ew metrics to capture and measure in relation to tackling critical business problems.

  • Assess Data Collection

    Garbage in, garbage out (GIGO) is a phrase often associated with data collection. Before launching the data strategy, associations should look at the data they are collecting and ask themselves why? It may be a good time to review and rethink why certain pieces of data are collected or not. Is the existing data helping the association address key business initiatives (ex. member recruitment or retention)? Or, are certain pieces of data being collected because “we have always done it that way?” Don’t collect data for the sake of collecting data. Rather, ensure data collection and the ongoing maintenance of the data is tied to key strategic initiatives.

  • Analyze Segmentation of Current and Future Data

    After assessing the existing data that has been collected, associations should analyze how the data (and future data) is segmented, tagged and/or scored.  Historically, associations have segmented individuals into broad categories (e.g. member versus non-member, what events were attended, products purchased or what committees volunteered for).  The collection of new data fields combined with the valuable data captured in complimentary databases (ex. social community, learning management, eMarketing) provides endless opportunities to segment members and individuals based on behavior and less on broad general categories.  More specifically, behaviors that may impact strategic initiatives tied to recruitment and retention as well as day-to-day behaviors impacting purchases (ex. who is likely to purchase certain products) or additional engagement opportunities.

Next Steps

Once the commitment has been made to capture and analyze data as part of a larger organization-wide data analytics strategy, associations should look to leverage technology to further facilitate the expected benefits and drive the ability to make data drive decision.  Many of next-generation smarter, simpler membership management platforms include data analytics and data visualization tools to help improve the capture, segmentation and, ultimately, the decision making process.  And unlike many of the earlier versions of data analytic tools, these new technologies represent an affordable investment in relation to the potential benefits.

Use the final weeks of the year to discuss how 2017 will be the year your organization commits to making data-driven decisions and developing a fact-based understanding of you most valuable members and what it takes to recruit, develop and retain these valuable members to drive business results.

This blog post was written by Patrick Dorsey, EVP of Marketing at Impexium, an Partner.


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