lyearn • shipped • 2026

Re-architecting org setup to work at scale

Turning Lyearn's rigid, one-dimensional org model into a flexible system that mirrors how companies are actually structured, to reduce set-up time significantly.

my role

Owned research, end-to-end design and finalised the new architecture concept (with backend lead).

team

1 Product Designer (Me), 1 Design Lead, 2 Engineers

project type

Full-Time

duration

3 Weeks

what’s the issue?

One rigid structure, and most companies couldn't fit

1

Fixed depth

2

Inconsistent Duplicate Job Profiles

but, of course, were not the first ones to solve this

findings from market research

How did established HR platforms solve this?

and we had to make it flexible, yet structured, because our clients were diverse

brain dump

So I went to the board and dumped all ideas, good or bad

I benchmarked Workday against SMB-focused tools like HiBob and BambooHR. Every platform picks a side on flexibility. Only ours fused the two structures into one, and the fusion was what broke.

but only 3 made the shortlist, and 1 became the anchor

Figma inspired component and variant system for job-profiles

Separate the 3 structures: Orgs, jobs, and employees (reporting structure)

Interpret reporting structure from org hierarchy

the new structures

The answer was to split the structures and connect them with a container

Instead of one chain doing three jobs, I built three independent structures and connected them with a single container called “Position”.

introducing positions

Position is the container that connected the 3 structures

A Position is a seat inside an org. A job profile is applied to it, and an employee is assigned to it. The employee gets their responsibilities from the profile on their seat. That lets the three structures stay separate but still connected.

now, lets look at some behind the scenes

list v/s tree view

I conducted a task analysis to see what the users preferred

I had both views made, but I had to decide which view deserved the first look from the user, and it wasn’t very simple.

task 1

Create an Org of your choice

task 2

Add 2 Positions in that Org

task 3

Edit the Org and any 1 Position

group 1 (list → tree)

Avg. task completion was ~25% faster in the list view than in the tree view

group 2 (tree → list)

Avg. task completion was ~43% faster in the list view than in the tree view

The list view won, but 6 users said they need the tree view once or twice a month

so, I added a mode toggle, with list view as default

overshoot animation graph

the org card

Juggling model clarity, compact layout, and clean UI

For the tree view, the node card was important to get right. I had to represent the real data structure, keep the UI clean, all while maintaining compact cards for optimal tree view experience.

I explored many layouts for the Org card

Demoting the hierarchy of org info made cards blur together: the org is the grounding element and needs top hierarchy.

Most recognisable, but flips the structure: the position contains the employee, and vacant positions had nothing to anchor to.

Count and Add Position relate to the positions, not the org: in the header they read as org-level and crowd it.

Only compact for tiny orgs: titles truncate and the card balloons. Anything other than rows was unreadable.

after more refining, I landed on the final card design

1

The Org

Org was the grounding node, so I treated it with the highest hierarchy.

2

Position

Position came first in the row because it was true to the real model.

3

Employee

Since names and photos are more recognisable, I gave them more weight.

So, how did this redesign affect the numbers?

impact

First time Org-setup time reduced and we received fewer support tickets

59% less time for first time set-up

From avg. 2 weeks to 5.6 days. Tracked from arriving on set-up page to import completion state.

75% less support tickets

Avg. 28/month to 7/month. Tracked over 2 months. Testing is still ongoing.

Thank you for reading!