Hospitality Analytics and Insights · Souha Sakly
Souha Sakly
All work
03 / Hospitality BIAnalytics & AI

Infor Hospitality Analytics & Insights

Designing the analytics and insights experience for Infor's hospitality BI platform — dense, configurable dashboards and Rover, the conversational AI assistant that lets anyone ask their data a question in plain language.

A note on visuals. This is a confidential enterprise product, so production screens aren't shared publicly. This case study tells the story through the design problem, the work, and the outcomes.
Role
UX/UI engineer
Design & frontend
Domain
Hospitality
business intelligence
Focus
Analytics & Insights screens
Rover conversational AI
Methods
IA, data hierarchy
Usability testing
Palette
#0E1014
#0A3D33
#0A7D5F
#7CF25E
#F98300
#6600FF
Tools
Figma Angular IDS Enterprise NG ECharts ag-Grid HTML / Sass
The product

Infor Hospitality Analytics and Insights is a next-generation BI platform built specifically for hospitality — hotels, resorts, restaurants, casinos, and event venues. It unifies data from property management, POS, sales, and catering systems into a single source of truth, then turns it into clear, visual analytics teams can act on.

Unlike generic BI tools, it ships preconfigured dashboards and KPIs that already speak the language of hotel operations, revenue, and guest behavior. My work focused on the analytics and insights screens — and on Rover, the conversational AI assistant at the center of the experience.

01 — The challenge

Hospitality data is complex and fast-moving, and it lives in many systems at once. The promise of the platform is that anyone — not just an analyst — can make a confident decision from it. That's a hard interface problem: surface the few things that matter without burying them, and make the deep data reachable without demanding technical skill.

The design had to do two things at once: present dense, preconfigured analytics that revenue and operations teams trust, and offer a far simpler way in for everyone else.

02 — Information architecture

I structured the analytics screens into tiers of attention, so the eye lands on what needs a decision now, then trends, then the full detail — and reserved color for signal rather than decoration.

TIER 1
Alerts & outliers
Pace, pickup, and pricing signals that need attention today.
TIER 2
Core KPIs & trends
Occupancy, ADR, RevPAR, and revenue, with direction and context.
TIER 3
Transaction-level detail
Granular data and Report Builder — reachable, not always shown.
03 — Rover, the conversational AI

Rover is the conversational layer over the data: users ask a question in plain language and get a real-time, visual answer — no queries, no technical skill. I worked heavily on the Rover experience inside the analytics and insights screens, designing how a question becomes a trustworthy answer.

RRover
How did weekend occupancy compare to last month?
Weekend occupancy is up 6 points versus last month, led by Saturday. ADR held steady, so the gain is genuine demand.
PRINCIPLE 01
Plain language in, visual insight out — the answer is a chart and a sentence, not a data dump.
PRINCIPLE 02
Answers stay transparent and grounded in the real data, so people trust what Rover tells them.
View Rover in Figma ↗
04 — Make it theirs

A platform meant for everyone has to bend to each role. The screens are built around customization: drag-and-drop dashboards, a Report Builder, and widget-level control — so a revenue manager and a GM can each shape the view to the KPIs they care about, and share it without waiting on IT.

Drag & drop
Compose a dashboard from widgets, no setup ticket required.
Report Builder
Build and personalize reports at any level of detail.
Share freely
Publish and share across departments without IT bottlenecks.
05 — Outcome & learnings

The result meets two kinds of user in one product: dense, trustworthy analytics for the people who live in the numbers, and Rover — a plain-language way in for everyone else. Treating conversation as a first-class part of the interface, not a bolt-on, is what makes the platform feel approachable rather than intimidating.

What I took from it: in BI, the design job isn't only visualizing data — it's lowering the cost of asking a question. The closer you get that cost to zero, the more people actually use their data to decide.

NEXT PROJECT →
Infor Revenue Management System