RASHMI
PADMANABHA

The process was as risky as the label itself: personal naming conventions stood in for version control, AI flags carried no rule or confidence so reviewers closed every one, approvals moved by email reply with no audit trail, and print operators received files with no confirmation of approval status.

Data gathered: 80+ people across three role groups, 400+ data points across two usability rounds, and a full mapping of exactly where the artwork "lost its identity" between handoffs.

Insight → Decision: Users had already workarounded the broken system into something simpler — the real workflow was invisible inside three disconnected tools.

Scored against the personas' pain points — Impact on trust & compliance risk vs. Effort to ship.

The product runs on Roboto throughout — chosen for its neutral, highly legible letterforms and tabular figures, which matter when reviewers are scanning version numbers and rule codes under time pressure.

• AI trust is earned through transparency, not capability.
• Design the shared data model before the first screen.
• The last person in the chain defines whether the system worked.

• Visitor / Client — needs fast entry, clear guidance, and a premium hospitality experience.
• Host / Employee — needs visit planning, tracking, room readiness, and coordination visibility.
• Receptionist — needs reduced manual workload and better prioritisation during peak times.

Data gathered: Logged reception overload during visitor peaks, host follow-through on food/room/access arrangements, and where clients lost confidence in the flow after check-in.

Insight → Decision: Check-in was not a single kiosk interaction — it was a chain of dependent moments across people, access, space, and hospitality. This reframed the design problem from "screen design" to system design.

• System design was more valuable than isolated screen design — the experience depended on multiple teams acting at the right time.
• Automation reduced cognitive load for visitors, hosts, and receptionists alike.
• End-to-end thinking made the experience feel premium, because support continued after the check-in moment.

Insight → Decision: After empathising with users, their needs, pain points, and frustrations doing daily activities became clear — different people had different needs, which a single portal redesign wouldn't solve. That pointed toward a conversational assistant available anywhere, not another screen to navigate.

Scored for immediate release against the full backlog of requested features.

• Meeting employees inside a tool they already have open all day removed more friction than any portal redesign could.
• Designing directly in the bot framework's own tooling surfaced platform constraints early, before they became rework.
• Close collaboration with developers was essential to shape a good experience around the real limitations of a chatbot.

Data gathered: Observed employees performing common tasks to surface pain points and confusion, paired with survey data for measurable, quantitative validation of what the sessions showed.

Key findings:

• Navigation issues — employees struggled to locate apps and information in a complex structure.
• No responsive design — the portal wasn't optimized for mobile, blocking access on the go.
• Inconsistent layout — poor visual hierarchy made the experience confusing and overwhelming.
• Limited access to information — critical content like policy benefits was buried deep in the IA.

Employees were invited to perform specific tasks on the redesigned portal while I observed their interactions, collected feedback, and measured task completion time and success rates. Results were positive — the simplified navigation, mobile optimization, consistent layout, and search functionality streamlined processes and improved employee satisfaction.

• Session analysis paired with survey data gave both the "why" and the measurable "how many" — neither alone was enough to prioritize confidently.
• Grouping by task, not by system or department, is what actually reduces navigation confusion.
• Mobile access isn't a nice-to-have for a self-service portal — it's where a large share of quick tasks happen.

• Director of Assets — portfolio-wide KPIs, Decent Homes Standard score, cost analysis.
• Void Manager — void pipeline by stage, re-let time vs target, rent loss exposure.
• Compliance Officer — certificate status, overdue escalation flags, regulatory risk.
• Repairs Manager — work order queue, SLA status, contractor assignment.

Data gathered: Measured average void re-let time against target SLA, tracked how often compliance deadlines were missed due to lack of visibility, and mapped duplicate data entry happening independently across teams.

Insight → Decision: All four roles needed the same underlying data but conflicting views of it — so the decision was one shared data model with role-based dashboard routing, instead of building four separate apps.