Improving Learning Outcomes in Life Sciences Through Data-Driven Benchmarking

Whether onboarding new commercial staff, refreshing regulatory requirements, or preparing clinical teams for new protocols, the goal of training remains the same: equip people with the knowledge and skills they need to succeed. 

During our recent webinar, Jessica Peyser, Senior Director at TransPerfect Life Sciences, shared a striking data point from the National Law Review: “only one-in-five employees in regulated industries feel that their training is preparing them for the job.” In a field where the information being taught directly impacts patient safety and treatment access, training effectiveness becomes a non-negotiable priority.  
 
Much like the life sciences training programs that inspired it, the goal of this webinar was straightforward: to share data-driven strategies and insights necessary to improve learning program outcomes across the industry. Peyser was joined by Amanda Hernandez, Director of Sales Training & Effectiveness, and Barrett Gaylord, Sales Training Lead, both from Telix Pharmaceuticals. Here’s what they had to say: 

Why Benchmarking Matters in Life Sciences Training 

Benchmarking provides more than a set of performance numbers. An effective process gives leaders the yardstick to measure whether training is achieving its goals.  

 “Sales training, and life sciences training in general, is notoriously hard to quantify,” explained Amanda Hernandez. “Benchmarking gives you a way to tie numbers to what’s often considered a ‘soft skill’ so you can actually measure progress over time.” 

Without this framework, training often relies on subjective impressions of trainee understanding, which can mask problems or misdirect resources to programs that aren’t delivering results. Accurate benchmarks can help define what strong performance looks like, making it easier to spot when adjustments are needed.  

In highly regulated environments, where mistakes can lead to compliance issues, lost productivity, or safety risks, this level of insight is essential. Benchmarks help justify investment in training programs by giving decision-makers concrete evidence of impact, ensuring resources and time are allocated effectively. 

Using Data to Identify Gaps and Trends 

Once benchmarks are set, data analytics can reveal trends that aren’t always obvious to training teams.  

“When you start looking at the data, you see trends in how different roles engage with training,” said Barrett Gaylord. “That tells you not just what content is being used, but whether it’s driving the right behaviors.” 

Tracking completion rates, assessment results, and post-training performance creates a fuller picture of training effectiveness. Adding learner feedback—collected through surveys or other open forums for discussion—provides critical context. Together, these insights reveal which materials are working well, where knowledge gaps remain, and how engagement differs between teams or roles.  

In practice, this means organizations can respond faster and more precisely when training needs change. 

Turning Insights into Action 

Collecting data is only the first step; the real value comes from applying it to improve learning outcomes.  

During the live session, Hernandez shared an example from Telix: “When we saw certain topics weren’t sticking, we didn’t just refresh the same content. We rethought the delivery method, added role-specific examples, and gave managers the tools to reinforce it.” 

This shift reflects a more agile approach to training design. Instead of repeating the same materials in the same format, teams can vary the length, delivery style, or depth of content to better fit the audience. That might mean breaking long sessions into shorter modules, incorporating real-world case studies, or enabling manager-led follow-up discussions. Making training more relevant to each role improves retention and on-the-job application. 

Collaboration and Culture Change 

Benchmarking succeeds when it’s supported by a culture that values data-driven improvement.  

As Barrett Gaylord noted, “You can’t just measure for measurement’s sake. The organization must be ready to use the data to make real changes, even if that means rethinking long-standing training traditions.”  

Shifting to this mindset may require moving beyond subjective feedback and toward making evidence-based decisions. 

Building this culture also requires collaboration. Sales trainers, compliance experts, marketing teams, and leadership all play a role in shaping and delivering effective learning programs. Coordinating across these groups ensures that content aligns with business goals, regulatory requirements, and learner needs. It also creates shared accountability for training outcomes, making benchmarking a tool for collective success rather than a task owned by a single team. 

Building a Continuous Improvement Cycle 

Benchmarking is not a one-time project—it works best as part of a continuous improvement cycle where results are regularly measured, analyzed, and applied to refine training.  

This process keeps training relevant as job responsibilities evolve, regulations change, and new market conditions emerge. With this mindset, training transforms from a static requirement into a dynamic capability that supports long-term organizational performance. 

To hear the full conversation and learn how your team can leverage benchmarking to improve learning outcomes, watch the webinar Improving Learning Outcomes in Life Sciences Through Data-Driven Benchmarking.