Debbie King

Posted & filed under Data Analytics Maturity Model.

It’s difficult to imagine planning a trip without knowing what the point of origin is. Whether you’re figuring out your route on Google Maps or searching for airline tickets, the first field you have to fill in is where you’re starting from. Without that crucial data point, any trip you might want to take will stall. The same applies to an association’s data analytics path.

But while knowing where you are geographically is fairly simple, defining your starting point for data analytics can confound the most sophisticated organization.

During our most recent Association Analytics Network meeting, associations and nonprofits met to discuss the issues facing them in terms of data analytics, and the need for an association data analytics maturity model (DAMM) was expressed. Out of this, a volunteer group was formed to build such a model that would help associations move from one stage of maturity to the next. The product of this, DAMM for Associations, is due to be released in December 2017.

DAMM for Associations

While several analytics maturity models, such as  the DMBOK and CMMI, exist, nothing specific for associations has been built.

Until now.

DAMM assesses the four key elements of Data Analytics:

  1. Organization and culture
  2. Architecture/technology
  3. Data governance
  4. Strategic alignment

Of course, no association is the same, and the answers to the assessment are varied. Based on how an association is built in regards to these areas, the assessment results place your association into one of the 5 Stages of Data Analytics Maturity.

Layer 1: Learning

Associations in this first layer understand the value and potential of data, but lack the knowledge, tools, and processes to take immediate action. Departments often operate independently, and data is not integrated across the organization. Basic reporting capabilities exist, but only for individual transactional systems. Decisions at Layer 1 associations are made often based on instinct, politics, and tradition.

Layer 2: Planning

Layer 2 associations are aware of the costs of not having an effective data strategy, and are seeing these negatively affect operational efficiency, member experiences, and financial performance. Associations in this layer have capable staff members with an analytical mindset and interest in data analytics, including one or more business area leader and an executive who can form a core analytics team. While pockets of interest exist to do more, the analytical mindset is not pervasive.

Layer 3: Building

Layer 3 organizations have taken action and begun building organization-wide tools and processes to leverage their data as an asset. There is an accepted strategy and implementation plan for analytics which includes a central data repository and tools for visualization and analysis.

Layer 4: Applying

Layer 4 associations are one step closer, with a mature central repository that is the trusted source for key association data. These associations use interactive visualizations and dashboards instead of static reports to manage performance in key business areas. And they use data and analytics to solve business problems. When action is taken, there are systems in place to monitor and measure results for continuous improvement.

Layer 5: Leading

The pinnacle of the Data Analytics Maturity Model for Associations, Layer 5 associations run businesses guided by their data—their member experiences and internal operations are managed and optimized using analytics.Data-guided decision-making is widespread throughout the organization and thus creates a strategic  advantage for these associations in terms of advancing their missions.

The DAMM for Associations includes indicators for each stage, which describe the signs and symptoms of the organization as it matures, along with action steps that can be followed to move associations from one layer to the next.

Learn More About DAMM for Associations

To learn more about the upcoming release of DAMM for Associations and what a data analytics model can do for your organization contact us and sign up for our monthly newsletter.