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Standardizing Quality: Establishing a Data-Driven Evaluation Cycle
Moved the eLearning team from a “build-and-forget” mindset to a structured, continuous improvement model.
Program Governance
Evaluation
Process Standardization
Leadership
The Challenge: The “Smile Sheet” Blind Spot
We were investing hundreds of hours into producing customer education, but our quality assurance process ended the moment a course was published.
We had fallen into a production mindset where reporting was entirely ad-hoc, meaning we measured "views" instead of effectiveness. We relied on superficial "smile sheets" at the end of courses, which left us completely blind to whether our training was actually helping users in the flow of their daily work or simply going stale.
My goal was to build a reliable way to systematically review our courses, figure out what was actually working, and clean up what wasn't.
42,500
Total Course Views
4.8 / 5
Avg Smile Sheet Score
?
Support Tickets Deflected
?
Product Adoption Impact
⚠ WARNING! Blind Spot Detected! No connection to business metrics.
The Strategy: Shifting to a Continuous Improvement Model
To change how we operated, I worked with leadership to map out a clear measurement plan.
The Pivot
We aligned around a simple rule: publishing a course is only step one. Every asset needed a clear way to track adoption and a schedule for routine check-ins.
New Standards
We established clear operational cadences, including standardized transparency meetings with cross-functional teams to review asset performance, and defined a rigid lifecycle for all customer education materials.
Execution: The 90-Day Review Cycle
To implement this strategy, I worked with my team to build and implement a rigorous, repeatable data collection and review process that eliminated guesswork.
- 90-Day Review Cycle: Every course and program required a mandatory 90-day post-launch audit, collecting distinct data points regarding enrollments, completions, seat time, and deep-link engagement.
- Troubleshooting Triage Matrix: To manage our team's bandwidth, I worked with the team to develop a structured Cost-Benefit matrix. When courses missed benchmarks, we categorized the necessary updates based on urgency and required time investment, allowing us to focus on the most pressing course corrections instead of wasting hours overhauling entire programs.
- Tracking Asset Usability: We expanded our engagement tracking beyond the LMS to measure how users engaged with in-workflow performance support, tracking precise launch and completion behaviors of certain activities.
Interested in the underlying blueprints? Review the structural criteria used during this phase in my Strategic Gap Analysis Framework.
Operational Impact
By replacing guesswork with real data, we fundamentally changed how our education programs ran. We stopped guessing what users needed and started relying on actual adoption data to guide our design choices. In fact, the most suprising thing I learned is that our learners love quizzes to test their understanding of the material!
90-Day
Standardized Audit
Cycle Established
35,000
In-Workflow Asset
Launches
83%
Average Asset
Completion Rate
- Massive User Adoption: Tracking in-workflow tools (iorad) revealed nearly 35,000 total launches with an 83% completion rate, proving that when support is strategically placed, users will actively engage with it to solve their own problems.
- Optimized Team Bandwidth: By using the Triage Matrix, we ensured that our instructional design resources were deployed only where data indicated a clear need, maximizing our team's operational efficiency.
View the Frameworks I Use
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