Using Data to Drive Employee Development

The DOJ consistently says that compliance programs should be effective, data-driven, and focused on whether employees are actually learning. Yet... The standard training "data" is literally just completion data! Imagine if I asked a revenue leader how their sales team was doing and the leader said, "100% of our sales reps came to work today." I'd be furious! How can I assess effectiveness if all I have is an attendance list? Compliance leaders I chat with want to move to a data-driven approach but change management is hard, especially with clunky tech. Plus, it's tricky to know where to start– you often can't go from 0 to 60 in a quarter. In case this serves as inspiration, here are a few things Ethena customers are doing to make their compliance programs data-driven and learning-focused: 1. Employee-driven learning: One customer is asking, at the beginning of their code of conduct training, "Which topic do you want to learn more about?" and then offering a list. Employees get different training based on their selection...and no, "No training pls!" is not an option. The compliance team gets to see what issues are top of mind and then they can focus on those topics throughout the year. 2. Targeted training: Another customer is asking, "How confident are you raising bribery concerns in your team," and then analyzing the data based on department and country. They've identified the top 10 teams they are focusing their ABAC training and communications on, because prioritization is key. You don't need to move from the traditional, completion-focused model to a data-driven program all at once. But take incremental steps to layer on data that surfaces risks and lets you prioritize your efforts. And your vendor should be your thought partner, not the obstacle, in this journey! I've seen Ethena's team work magic in terms of navigating concerns like PII and LMS limitations – it can be done!

How dispensaries train employees is changing. Since forever, retail and education leadership have been left in the dark about how employees perform and what they can do to help. Data visibility makes the difference here. Retailers can leverage their own historical data to understand where to improve employee performance. Here’s how Seed Talent does it today: 1. Analyze Analyze current qualitative and quantitative data to identify employee gaps in performance where supportive resources are needed. POS data is the key to retailers knowing whether or not employees are effective in their roles or may need additional sales or other supportive training! 2. Assign & Alert Automatically assign and alert employees of supportive training resources to address their performance gaps. Once the employee receives an alert, they have a set amount of time to complete their courses before sequential reminders are sent, helping managers stay on task. 3. Report Set up your KPIs and track progress against training after implementation. You can use your store dashboard to understand the direct business impact of upskilling your team. These reports will ultimately help you enable your team and make better strategic decisions about the role of training at your dispensary. Being able to measure the impact of resourcing and training your teams changes the conversation from box checking courses to actions that measurably drive your business forward!

I was reviewing quarterly reports with a client last month when they asked me a question that stopped me in my tracks: "Scott, we have all this learning data, but I still don't know which programs are actually improving performance." After 12 years as CEO of Continu, I've seen firsthand how organizations struggle with this exact problem. You're collecting mountains of learning data, but traditional analytics only tell you what happened - not why it matters. Here's what we've learned working with thousands of organizations: The real value isn't in completion rates or assessment scores. It's in the connections between those data points that remain invisible without the power of tools like AI. One of our financial services clients was tracking 14 different metrics across their onboarding program. Despite all that data, they couldn't explain why certain regions consistently outperformed others. When we implemented our AI analytics engine, the answer emerged within days: specific learning sequences created knowledge gaps that weren't visible in their traditional reports. This isn't just about better reporting - it's about actionable intelligence: - AI identifies which learning experiences actually drive on-the-job performance - It spots engagement patterns before completion rates drop - It recognizes content effectiveness across different learning styles Most importantly, it connects learning directly to business outcomes - the holy grail for any L&D leader trying to demonstrate ROI. What's your biggest challenge with learning data? Are you getting the insights you need or just more reports to review? #LearningAnalytics #AIinELearning #WorkforceDevelopment #DataDrivenLearning