CoverStory
In an era where rapid adaptation is key to success, Bayer has taken a monumental step forward in training efficiency and effectiveness. Faced with the challenge of preparing multiple field teams for various launches, Bayer’s learning and development (L&D) team turned to innovative training solutions powered by artificial intelligence (AI). This strategic move not only ensured that our field teams were well prepared but also set a new standard for scalable training practices in the organization.
“Embracing innovation means finding practical, sustainable ways to help our teams grow and succeed. Implementing an AI-powered verbalization tool has been a game-changer — not only have we rebalanced the workload for our L&D team, but we’ve also introduced consistent, scalable practice and verbal certification for our customer engagement teams.”
Peter Frank, Director, L&D, CardioRenal
“Leveraging AI in our certification process allows us to be more targeted in our training initiatives. We know exactly what and where the knowledge and skill gaps are, allowing us to tailor training initiatives where the team needs it most. Our learners also get immediate and detailed feedback, better equipping them to own their development.”
Roseann Kovelman, Director, L&D, Oncology
“Effective sales training must always prioritize achieving tangible business outcomes. We craft our AI learning solutions through cross-functional co-creation and a test-and-learn methodology, ensuring we measure and validate their impact on business performance.”
Kathy Driscoll, Associate Director, L&D, CardioRenal
With national sales meetings and launch meetings on the horizon, there was a sense of urgency to equip the sales force with the necessary skills and knowledge to execute on new messaging. Traditional training methods, often slow and resource-intensive, were not a reasonable option.
Bayer’s L&D team embraced AI technology, implementing advanced training simulators that allowed representatives to engage in more than 4,500 practice sessions. This dynamic approach enabled representatives to refine their messaging and hone key conversational skills, all while receiving real-time feedback tailored to their individual performance.
The results were nothing short of remarkable. For example, our cardiovascular sales team had a 100% participating rate, an impressive 97% of participants scored four or five on a five-point scale, demonstrating mastery of the key material. This high level of proficiency not only boosted the confidence of the team but also streamlined the coaching process, ensuring that field readiness was achieved immediately after the meeting concluded.
Bayer’s L&D team identified key components of the AI experience as we worked with our selected supplier partner. The components were:
Interactive practice sessions: AI-powered simulators allowed field teams to engage in realistic role-playing scenarios. These simulations mimicked real-life sales conversations, enabling field teams to practice delivering the new marketing message in a safe and controlled environment.
Real-time feedback: The AI system provided immediate feedback on performance, analyzing factors such as tone, pacing and content accuracy. This instant feedback loop helped field teams identify areas for improvement and adjust their approach on the fly.
Personalized learning paths: The AI technology adapted to each person’s individual learning style and pace. By analyzing performance data, the system could recommend specific microlearning resources or practice scenarios tailored to the needs of each representative, ensuring a more personalized training experience.
Data analytics and insights: Bayer leveraged data analytics to track engagement levels, practice frequency and mastery rates. The insights gained from this data allowed the L&D team to refine training materials and methods continually, ensuring that the training remained relevant and effective.
Scalability: The AI training platform was designed to scale efficiently, enabling the L&D team to train multiple customer-facing colleagues simultaneously without compromising quality. This scalability was crucial given the tight timeline leading up to launches and national meetings.
We kept the learner at the center of our AI initiative, with three distinct goals for their initial experience on the platform. During the test phase, the video submission method outlined below showed significant improvement across all users, indicating its effectiveness in enhancing selling skills. The qualitative feedback was overwhelmingly positive, with reps appreciating the opportunity for self-reflection.
The quantitative impact on business outcomes was equally remarkable. During the test phase, there were 30% more representatives in the active group demonstrating business growth. In terms of losses, the active group experienced 177% less business loss compared to the control group.
The main objectives were:
Focus on selling skills: Each representative was required to submit a video of 2-10 minutes and receive a 24-point assessment of their selling skills. This platform was also available as an invited bot for Microsoft Teams meetings between representatives and their managers, offering managerial coaching insights.
Individual assessments: Avatar simulations were designed to measure brand messaging accuracy and completeness. This realistic practice allowed representatives to know exactly where each message point was located, resulting in full messaging to customers and quick selling pivots in response to customer responses. The videos were assessed individually, allowing for personalized feedback. This assessment included strengths and areas for improvement, giving reps insights into their performance.
Coaching resources: The use of avatars and video submissions facilitated a unique self-realization process. Through these engagements, reps could identify their performance gaps and take steps to improve, effectively taking them from good to great. Along with the individual assessments, reps received tailored multi-modal, microlearning coaching resources.
Soon after Bayer launched its AI platform for message practice in the cardiovascular division, it piloted an automated certification process for 20 new hires in the oncology division.
Traditionally certification is conducted by a trainer following the completion of the Phase 1 class, in a one-on-one scenario with the new hire. The certification is used to assess the rep’s mastery of the Phase 1 class content, specifically messaging and objection handling.
As our field force grew and new hire numbers increased, these certifications became labor intensive and prevented our L&D team from conducting other work for days at a time. An intervention was needed to manage L&D capacity and deliver an autonomous and asynchronous certification process for the new hire.
The Oncology Phase 1 Class featured a rigorous training program that required participants to engage in three simulations as part of their final certification process. This AI-powered approach allowed the customer engagement team to practice real-life scenarios on the platform, ensuring they were well-prepared to communicate effectively about their promotional product once they entered the field.
The program brought noteworthy results in terms of certification and resource optimization:
In the first class where AI was leveraged, 20 class participants engaged in 152 individual practice sessions on the AI platform then successfully certified on their own time, including nights and over the weekend.
The average score achieved by participants in the practice sessions was an impressive 4.5 out of 5, indicating a strong grasp of the material and readiness to engage in field conversations.
The time that the L&D team would have spent — approximately 40 hours — on pre-certification practice and certification completion was redirected to other critical activities. These included:
Training preparation for an upcoming product label extension.
Conducting a Phase 1 class on a different oncology product.
Legal & medical review of new and updated training content.
Managing routine training needs on our learning experience platform (LXP).
This strategic reallocation of resources underscores the potential of AI-driven training solutions to not only enhance certification outcomes but also to free up valuable time for other essential initiatives.
The data from the AI oncology certification process reveals several key insights for future training programs:
Scalability of training: The success of the AI-driven simulations demonstrates a scalable model that can be applied to future training initiatives across various therapeutic areas.
Continuous improvement: The feedback and performance metrics gathered from the AI-powered certification process can inform ongoing curriculum development and refinement, ensuring that training remains relevant and impactful.
Based on the success of our pilots, AI-powered practice and certification has been scaled to become the standard learning methodology at Bayer. Our AI experience exemplifies the transformative power of innovative training methodologies in the pharma sector.
By leveraging AI-driven solutions, organizations can not only enhance the proficiency of their customer-facing teams but also optimize resource utilization, ultimately leading to improved customer engagement effectiveness and better patient outcomes.
As our training community continues to evolve, embracing such advancements will be crucial for maintaining a competitive edge and ensuring that field teams are equipped for high-impact customer engagement from the moment they leave their first training class.
Tracey DeSilva is vice president, learning & development, U.S. pharmaceuticals, for Bayer. Email her at tracey.desilva@bayer.com or connect through linkedin.com/in/tracey-d-a2a5011b6.
