With vast and growing engineering teams it became imperative to maintain parity in the quality of mentorship and training delivered to both new recruits and seasoned developers. Our senior leaders and instructional trainers’ resources simply were not scalable at the level. As such CodeGen DigitalMentor was born out of a critical need we were facing. The value proposition was simple- “deliver top-notch training at-scale, with controls in place to measure performance, weak links, and provide an environment for continuous learning to occur”. Simple doesn’t always come easy, unfortunately. But we built a system that led to some of the biggest increases in workplace satisfaction year over year, a helpful by-product of this was sharp decreases in Go2Market time, improved code quality, and efficiency in resource allocation across projects which led to cost savings across the board.
How does it work? Each engineer had a pre-built profile that included the history of the various projects that they had been core members of, as well as included the core responsibilities which they had overseen. Engineers were allowed to edit these profiles and import all their current certification history and add their own expertise. New recruits were given profiles and were notified that whenever they run into issues that couldn’t be solved within their own team, they could utilize the DigitalMentor to tap into our company’s broad expertise at any time. Queries were then run through NLP models which could direct their needs to the best-suited candidate and connect them via Remote Desktop, Video Chat, or call. If the issue was a quick resolution, both parties could be on their way, or if necessary users could request a mentorship, that allowed more long-term support from leaders. The platform offered two-sided reviews that allowed metrics to measure the success of this innovation at scale.
How to scale even more? With the newfound ability to keep a pulse on the day to day to issues many of our teams were facing, it became apparent where our core problems surfaced and allowed us to perform needs-analysis at scale with high levels of detail. Top-performing “problem solvers” on the platform were taken to develop micro-courses and training sessions for issues that were arising most frequently on the platform. With large-scale access to data, it became apparent that there were patterns in the follow-up requests and problems many of our engineers were facing. We developed a recommendation engine that paired with our micro-courses library to recommend engineers to course paths to learn vitals prior to requesting follow-up live mentorship. Digital Mentor also allowed for us to host company-wide, or division-wide learning sessions and opportunities, rapidly and easily, with fun features such as the ability to crowd-source learning objectives prior to sessions allowing for the voice of the employee to take a prominent position.
- Technical Learning Design
- e-Learning Development
- Engaging Training
- Idea Development
- Project Management
- UI/UX Design
- Course Authoring
- Needs Analysis
- Mentor Engineers & Instructors/Trainers
- Technical Review and Feasibility Testing
- Coordinate Engineering Team
- Quality Control