If you’re an association leader in learning and development or certification, you’re probably sitting on more data than you realize. (Or maybe you realize it and it makes you slightly anxious!) Every learner interaction, every assessment result, every course enrollment and engagement pattern adds to a growing pool of information that could be shaping better decisions, stronger programs, and more personalized member experiences.
The challenge? For most organizations, that data sits in a “data lake” that’s more like a reservoir with no tap. The information is there, but getting it out in a useful, timely way can feel impossible. Reports take too long. Dashboards don’t answer the right questions. And the people who need insights most, your instructors, your partners, your leadership team, are left making decisions based on lagging indicators and gut instinct.
We know because we’ve lived it. Holmes Corporation (HC) has spent more than 50 years helping associations build learning products, certification programs, and career development experiences. That work has generated an incredible amount of data. But the analytics infrastructure we’d relied on couldn’t keep pace. Partner data requests that should have been simple were taking days or weeks. Rebuilding internally would have taken years.
So, we made a choice: invest in modernizing our data capabilities, bring in the right expertise to help us do it well, and build the kind of analytics foundation that would benefit not just our team, but every association and learner we serve. This is the story of that transformation, and the lessons we learned along the way.
Taking the Plunge
As our products, partners, and learner base grew, the gaps in our analytics capabilities became more obvious. Our product teams needed deeper insights to continue improving learning experiences. And our stakeholders needed faster, more reliable access to accurate metrics to make confident decisions.
We knew we couldn’t just patch what we had. We needed a fundamentally stronger foundation. But we also knew that building it right meant bringing in expertise we didn’t have in-house. That’s what led us to Analytics8.
Lesson Learned: The biggest risk in a data transformation is not the technology. It is starting with the wrong questions. Before a single platform was selected or a single line of code was written, we insisted on a full assessment of where we actually stood. What we found surprised us and became the foundation for everything that followed. Diagnose before you prescribe.
Finding the Right Approach
When you’re choosing a technology partner for something this significant, the temptation is to focus on tools and platforms. We were more interested in finding a partner who would take the time to understand our business first.
That meant starting with a data strategy assessment. In just three weeks, the team interviewed our key stakeholders, reviewed our existing technology stack, and mapped everything to our business priorities. Very quickly, we had an actionable roadmap.
Steven Khraiss, HC’s Vice President of Data Strategy & Analytics, led the initiative on our side. He describes the experience this way:
That assessment became the turning point. It gave our team clarity on where we stood, where the inefficiencies lived, and what the path forward looked like.
Lesson Learned: Don’t let vendors lead with technology. Lead with your business priorities and let the technology follow. The most valuable thing an external partner can do is show you what you cannot see from the inside.
Building a New Foundation
With the roadmap in hand, we got to work on two major initiatives: rebuilding our “data lakehouse” and selecting the right embedded analytics platform for our needs.
A data lakehouse combines the flexibility of a data lake (which can store all types of data) with the structure and performance of a data warehouse (which organizes data for fast, reliable reporting). Think of it as taking everything in a data lake, cleaning it up, organizing it, and making it actually usable for day-to-day decisions.
The analytics platform evaluation was equally important.
Khraiss explains, “We knew we needed the embedded analytics piece, flexibility in data models, and the ability to give data teams the control and sophistication they require. When we found a platform that checked all the boxes and came highly recommended by people we trusted, the decision was easy.”
The practical impact was immediate. Built-in platform features like email alerts, filtered exports, and permission-based views were adopted into daily workflows, making everyone more efficient. Partner data requests that used to take days or weeks could now be answered in hours. And when key stakeholders saw the new dashboards, they noticed the difference right away.
Lesson Learned: Nail your criteria before you evaluate platforms. When you know exactly what you need, the right answer becomes obvious fast. And when adoption happens organically because the tools actually fit the way your team works, you know you made the right call.
What This Means for Our Association Partners and Learners
We didn’t take on this transformation just to make our internal team’s lives easier. The real purpose was to strengthen the products and services we deliver to our association partners and, ultimately, to the professionals who use our learning programs every day.
Our stakeholders now know they can get their metrics quickly, accurately, and from a single source of truth. As Khraiss puts it: “We’ve revolutionized the way we look at data.”
What does that mean in practice? With a modern data infrastructure in place, HC can deliver the kinds of capabilities that association leaders are increasingly asking for:
- Real-time performance visibility. Our education partners and their instructors can see exactly where learners stand at any moment, rather than waiting for quarterly reports.
- Predictive analytics.By analyzing engagement patterns across thousands of learning records, we’ve identified that learners with moderate-to-high engagement demonstrate 17-point higher success rates on certification exams. That insight powers early interventions that help struggling learners before it’s too late.
- Automated learner support. Behavioral data feeds into automation platforms hourly, triggering personalized communications that have reduced manual outreach workload by 45% while maintaining or improving learner activation rates. Those support messages perform at 3.2x the industry standard for email engagement.
- Comparative benchmarking. Associations can see how their programs stack up against peers, identify what high-performing courses do differently, and make evidence-based decisions about where to invest.
This analytics modernization is also the latest chapter in a longer data journey at HC. Earlier work with AI and machine learning produced our adaptive “My Study Plan” feature, which uses real-time performance data to recommend personalized study paths for each learner. That innovation contributed to a 35% reduction in required study time by helping learners focus on their actual knowledge gaps rather than reviewing material they’ve already mastered.
HC has been building toward data-driven learning for years, and this analytics transformation gave us the infrastructure to bring it all together.
Putting Data to Work for Your Association
If our challenge sounds familiar, you’re not alone. Many associations are sitting on valuable data without the tools or infrastructure to make it actionable. The good news is that modernizing your analytics doesn’t have to mean overhauling everything at once. It starts with understanding where you are, where you want to go, and who can help you get there.
If you’d like to learn more about how data-driven learning can impact your association, download The Association Leader’s Guide: How to Turn Learning Data Into Personalized Member Experiences.
