CMT ASSOCIATION RULES

I love my job. I love its glorious contradictions. Where else can the legacy of a venerable 50-year-old brand meet the raw potential of a tiny startup? Thousands of members representing over 135 countries, yet only 10 full time staff. Advancing a discipline that has been practiced since the Tokugawa Shogunate but is now rising to prominence in the age of quantitative finance.

This delightful bundle of contradictions has given me room to think about all mission-driven organisations, for profit or not. Over the past 5 years and 5 months, I have been given the freedom to choose the business problems I want to solve, by a leadership and board that is humble about its legacy, and confident in its ability to navigate the gap between data and behaviour. In a significant way, my decision to start this doctoral program was inspired by the potential I saw in GenAI to address the contradictions at CMT Association.

?That is why, this week in my Machine Learning Class, when we were introduced to the data mining technique called Association Rules, the name of this article practically wrote itself. #PunnyQuote intended

Introduction:

In the quest to advance missions and maximize impact, non-profit boards face the dual challenge of engaging volunteers and optimizing their contributions. One innovative strategy that has surfaced from the business analytics realm is the use of association rules – a data mining technique that reveals how items relate to each other. For organizations like the CMT Association, applying association rules can transform member data into actionable strategies, bolstering their mission to advance the discipline of technical analysis, serve financial service clients responsibly, and create growth opportunities for members.

Understanding Association Rules:

At its core, association rules look for patterns of items that occur together frequently. In retail, this could mean identifying that customers who buy bread also often buy butter. When translated into the context of non-profit associations, these rules help us understand which member activities correlate with higher engagement or which volunteer opportunities yield the most satisfaction and contribution to the association’s goals. The key is to remember that associations imply neither causality nor correlation. They are just associations. (Side note: I wish even among people we understood this better. It would eliminate so much intolerance.)

Case Study: Leveraging Data in Practice:

Consider the CMT Association, which embraced this approach by conducting a comprehensive analysis of their members’ engagement. Through data on professional backgrounds, event attendance, and volunteer history, the association identified key patterns. For instance, they found that members who attended webinars on market risk management frequently volunteered for research initiatives, leading to targeted invitations for these engaged members to contribute to new projects.

Actionable Steps for Implementation across member Associations:

1. Data Collection and Analysis:

?? Begin with the end in mind by collecting member data that includes demographics, professional experiences, event participation, and engagement levels. Ensuring data privacy and member consent at this stage is paramount.

2. Pattern Identification:

?? Analyze the data to spot frequent co-occurrences – for instance, members with certain certifications often engaging in specific types of volunteer work.

3. Rule Formulation:

?? Formulate predictive rules from these patterns. For example, if a member shows a keen interest in educational events, they might be more inclined to contribute to training materials.

4. Strategic Application:

?? Apply these rules to tailor volunteering opportunities. Use the insights to drive personalized engagement, aligning volunteer skills with the most impactful initiatives.

5. Feedback and Evaluation:

?? Incorporate feedback mechanisms to continuously refine your strategy, ensuring that the association remains adaptable to changing member needs and external conditions.

Ethical Considerations and Best Practices:

As you embark on this data-driven journey, navigate the ethical landscape by maintaining transparency with members about data usage, upholding stringent data protection standards, and securing informed consent for data collection and analysis.

Visualizing the Impact:

Augment your article with charts and graphs that illustrate the success of applying association rules, such as increased volunteer engagement rates, enhanced member satisfaction, or growth in professional development opportunities.

Broadening the Horizon:

The principles behind association rules have broader implications. For-profit businesses can also harness this technique to deepen customer relationships and personalize offerings, demonstrating its versatility across sectors.

Conclusion:

Embracing association rules can empower non-profit boards like the CMT Association to not only enhance volunteer engagement but also to ensure that their members are on a path of professional growth and personal satisfaction. By strategically analyzing member data, organizations can unlock hidden patterns, tailor volunteering opportunities, and ultimately forge a deeper connection between their volunteers and the overarching mission. It's not just about maximizing resources; it's about enriching the member experience and galvanizing the collective pursuit of a shared vision.