Archive for Data Analytics Maturity Model

5 Areas To Assess Using the DAMM—Data Analytics Maturity Model

At ASAE Tech earlier this month, we shared our Data Analytics Maturity Model (DAMM) which is built for associations by association leaders. Designed as an assessment and high-level action plan, DAMM helps staff members identify where their organization is when it comes to taking a data-guided approach to overall strategy.

Keep in mind though each association is unique and the need for data analytics differs so answers to this assessment vary.

While there are several indicators in each stage of DAMM worth examining, here are 5 areas to hone in on because it impacts where your organization lands in the model.

 

 

1. Make your data accessible to everyone.

At this year’s ASAE Annual Meeting, we conducted a live poll of our audience and discovered some interesting statistics that hold true at many associations. 68% of association staff members recognize the potential value of data, but they lack the processes and tools to make it useful to everyone.

Stage 1 of the Data Analytics Maturity Model focuses on “learning.” Associations need to evaluate where their data resides and how easy it is for everyone at the organization to access it. Or is the reporting centralized in the IT department? In the past, it might have made sense for IT to pull the reports and to own the data. However, for your organization to flourish, everyone needs to be able to see the data when it’s convenient for them. A sign of an organization’s maturity is when the data silos have broken down. The ability to use data is essential for competitive advantage and should be a goal for the entire company.

2. Instill an analytics-guided culture.

Chances are you do have business leaders in your organization who possess analytical mindsets and understand the value of data analytics. Those are the champions driving your organization to be more data-guided. Those same staff members can form the core analytics team and begin to develop an effective data strategy that be used throughout the company.

Stage 2 of DAMM is the “planning” phase. At this point, there’s the recognition that there’s a lack of trust in the accuracy of the data. Your team is unsure what data they need or even where to find it. The core analytics team is essential in helping to overcome this challenge. 

This same team can also be the ones who experiment with data visualization and create standard operating procedures around data quality management.

All it takes is a small team of interested and motivated staff members to instill a more analytics-guided culture. It won’t happen overnight, of course, but they can be an influential force in encouraging people to embrace analytics in their day-to-day roles.

 

 

3. Develop clearly defined KPIs.

Stage 3 is the next stage of maturity for an organization, and it’s all about “building.” By this time, your association has a data strategy in mind and action plan for analytics that has been given the green light from your executive team. Once you’ve gained the executive team’s buy-in, you’ll discover that KPIs need to be established to track your success along the way. How you measure success varies with every department so it’s up to your team to determine what is most suitable to measure your performance. Ideally, these KPIs should go beyond “vanity metrics” and really drill down to what will directly impact the member experience, and these should track back to what your organization’s overall goals are. These take time to refine, but it’s a sign that your organization is maturing.

4. Create a central repository that encompasses all key data sources.

It’s not uncommon to have data living in different systems because there was probably a time when this was a common practice at your association. When your association uses data and analytics to solve business problems, one of the immediate projects to tackle is keeping the data in one repository for everyone. Within this repository, you can find all the key data you need to have a deeper understanding of your members and the services you’re providing them.

Once your organization has a central place for data storage, you’re at Stage 4 which involves “applying” treating the data as an organizational asset and eventually becoming proficient in data analysis because it’s becoming a go-to source for understanding your organization and members. 

5. Implement a data governance program.

According to DAMM, the final stage is when your staff members are actively taking a data-guided approach to run their business. Data is routinely used by staff in their respective roles, and everyone has a 360-view of their members. One way to aid data-guided decision making is to establish a data governance program. Data governance keeps data updated and accurate for everyone who uses it. In order for this program to be successful and ongoing, you need to have a team take ownership of it. Whoever this group of staff members are, it’s up to them to communicate, follow, and continually improve the program so it’s relevant to the association as it continues to grow.

The DAMM for associations and nonprofits is an eye-opening way for your organization’s team to identify where it is in the model and what action steps you can take to move your association forward.

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.

2017 ASAE Tech Conference Recap

The 2017 ASAE Tech Conference was yet another stellar event. Thank you to the entire ASAE team who managed the show—making it a wonderful experience for us to both participate and contribute. Some were there to learn, others to show and some just for fun! We were there for all three! 

Aside from exhibiting, we offered attendees the opportunity to get their DAMM (Data Analytics Maturity Model) Score at our booth,presented with clients at three different sessions and held a dinner at Voltaggio Brothers Steak House.

 

Speaking at the 2018 ASAE Technology Conference

Digital Convergence: Data Strategy

Our friends at Community Brands asked us to co-present a segment with Sigmund VanDamme during the Digital Convergence pre-conference workshop they hosted in conjunction with ASAE. We shared 5 areas that associations can assess as part of the Data Analytics Maturity Model (DAMM).

Keep It Clean: Harness the Power of Gold Standard Data Hygiene

Another pre-conference session was co-presented by our own Julie Sciullo and Sean Hewitt along with Adam Rosenbaum from CASE. This session was about developing meaningful KPIs to get more from data analytics.

Turbo Charge your Analytics with Agile Data Warehousing

Lastly, I co-presented a session with Ric Camacho from Specialty Food Association Inc. where we took a look at how the Specialty Food Association went from 0 to 60 in record time using a practical approach to bring useful data to their team in order to make decisions.

How ASAE Uses Data Analytics & Visualizations

During the opening keynote to the conference ASAE CIO Reggie Henry revealed a look at a real-time dashboard we helped create. This tool is incredibly powerful with data being pulled from multiple data sources including much of it from ASAE’s Collaborate community powered by Higher Logic.

 

 

Why is this so powerful? Simply put, it helps ASAE know and understand what members are talking about.

For example, the word cloud you see here is dynamic and has a drill-down capability that changes with the most relevant topics for the community.

On the top right, you can see a certain member type. On the bottom right, you can see member years. This is helpful, for example, if you’d like to filter all the “new” members to find out what they’re interested in topic wise based on community discussions.

 

 

This next image of the dashboard provides an overview, so you can see what different users have been doing. You’re able to see what prospects or former members have been doing in order to get a sense for the engagement level of these two different groups. Then you can drill down to see exactly why on is more engaged over another—pinpointing which ones are at risk and if something can be done to prevent decreased engagement.

These examples just scratch the surface regarding how the data captured in key systems can be visualized, analyzed, and then inform key discussions within an association.

Thank you to Reggie Henry for sharing the dashboard with attendees and also Andy Steggles at Higher Logic for sharing the dashboard during his session titled 5 Keys to Disrupting Member Engagement, Improving Satisfaction and Growing Retention. We’re proud of the work that’s been down and even more excited about the impact it can have on associations who begin to harness data in this manner.

Dinner at Voltaggio Brothers Steak House

Rounding out the conference, we had a intimate dinner with some clients at the wonderful Voltaggio Brothers Steak House inside MGM National Harbor. It was a treat to spend quality time with great people! The conversation was an enjoyable mix of personal and business oriented topics—something we look forward to at events such as these.

 

Learn More

To learn more about DAMM (Data Analytics Maturity Model) for Associations or dashboards driven from multiple data sources—contact us . You can also stay up-to-date on the latest content we’re sharing each month by signing up for our monthly newsletter.

 

 

Plotting a Data Analytics Path for the Future Starts with Knowing Where You Are

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.