Tangible Business Value
We recognize the importance of the creation, assignment, and management of employee and team training at the organizational level. While this is often the role of a training manager and their team, we’ve discovered that people in other positions often must also manage those important learning management tasks.
These recruiters, HR managers, direct supervisors and people of other positions join training managers in the category of what we call ‘trainers’. Providing value for these trainers is necessary in order for MARi to succeed, since these trainers will provide the backbone of cohesive organizational upskilling and new platform content generation.
Summary of Work
As requested by MARi, we developed a high-level workflow for a trainer to upload a training course, add and edit attributes that align with it, and define the logic behind each attribute, including what content from the course aligns with what attribute. The primary purpose of this is to provide an understanding of the most critical flow for trainers, what it might look like, and what parts of the UI are necessary to have a successful first iteration.
To land on our final design, we have iterated and explored concepts through three previous iterations, all of which have provided valuable insights.
Final Design
The goal of this prototype is to fulfill the need of reaching a shared understanding of what the most critical component of the trainers’ journeys are, based on the research and insights we have gathered over the course of our 8 months of work.
Design Dive
Content Creation
Creation of new training content within MARi begins with adding learning materials into the system, be it through a file upload or parsing resources other members in the organization have added previously and marked as accessible. After selecting the desired content, they are then able to populate the course by directing what type of data is being used, as well as entering basic information such as content titles.
Content Task Adding
Granular bubble graphs do not clearly align with the attribute mental models of more than 80% of participants.
In addition, almost 90% reported unclear recommendations due to lack of alignment with previous/current practices. MARi’s AI Agent should parse the training material and return with a list of skills and tasks that it identifies. The flow then allows the user to edit, add, and remove items from these lists, if they determine that the AI has not discovered all items or named them properly.
Task Attribute Population
Once they’ve confirmed the skills and tasks, the AI agent will attempt to populate each item with a set of attributes, as it sees fit. The user will be able to edit attributes, replace them with ones currently in the organization’s database, or allow them to create new attributes.
Visual Attribute Logic
Lastly, we’ve suggested a logic flow canvas that should allow for a more visually intuitive way to create assignment-logic with the help of AI-suggestion.
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Archetype Needs
From the trainer archetypes that we researched and created, we learned the essential need across manager users is to create high-performing teams. Addressing this through our prototype to support managers in delivering effective training materials that address employee skill gaps precisely became a primary goal of ours.
For us, this came in the form of working to assign needs-based, personalized training to users with the help of MARi’s AI systems.
MARi is also concerned with understanding the nuances behind visualizing employee growth and skill improvement for those trainers that want to see how their experience and work enables a broader impact. While we have begun working around this problem, this will require further research and iteration to solidify.