NLP Workforce Assessment Solution

 

Challenge

Call center technicians for a Fortune 100 Telecom were often trained in hands-on sessions with instructors and follow-up “team huddle” events that lacked structured practice. This was time consuming, costly, and ineffective, resulting in high turnover rates due to employees being unable to meet the demands of the job.

Approach

I evaluated several Natural Language Processing (NLP) technologies alongside trainers and developed implementation strategies for the recommended platform. NLP allowed students to be presented with a wide variety of scenarios and test their outcomes based on video responses that scored them on a rubric including sentiment analysis and several other key measures. Additionally, I proposed users become engaged through gamification, allowing them to increase their scores by redoing a simulation and with a leaderboard showing their ranking.

Outcome

Students were able to see what aspects of their customer interactions needed work and were provided with a wider range of scenarios than could be included in classroom training. Through the NLP’s scoring system, employees had the ability to improve scores with the leaderboard encouraging re-takes to gain a higher level which resulted in users being driven to practice more. This approach showed clear improvement over traditional leader-led training, and fewer hours had to be spent in the classroom. This had an impact on the preparedness of call center representatives; it also greatly reduced employee turnover and related costs.