Enterprise Analytics · AI/ML Interface

ORBIT Analytics

From Data Overload to Decision Intelligence — ~40% Faster Decision Cycles

RoleLead UX Architect
ScopeEnd-to-end: Research → IA → Wireframes → UI → Validation
IndustryQSR / Restaurant Operations (2,800+ locations)

The Challenge

“Too much data. Not enough decisions.”

The legacy ORBIT platform suffered from fragmented dashboards across modules, high cognitive load due to dense data layouts, lack of prioritization where everything looked equally important, and minimal guidance on what action to take next.

Impact on Users

Slower decision cycles across all management levels. Increased dependency on analysts for basic insight extraction. Low engagement with dashboards — managers avoided the platform entirely, reverting to manual spreadsheet analysis.

UX Strategy

The core insight: Users don’t need more data — they need direction. Every screen must answer: “What should I do next?”

Prioritize What Matters

Shift from data-heavy layouts to priority-driven dashboards. Highlight critical KPIs and anomalies first.

Reduce Cognitive Load

Chunk complex data into digestible modules. Improve scanning and comprehension speed.

Make Insights Actionable

Transform static numbers into contextual insights with recommendations.

Design for Roles

Different users have different needs. Created role-based views for Admin, Manager, Analyst, and Viewer.

Build for Scale

Established a consistent, token-driven design system for future module expansion.

The Solution

Modular Dashboard Architecture

Clean, card-based layout with logical metric grouping and progressive disclosure for deeper insights.

Insight-Driven Interface

AI-powered recommendations, contextual alerts, anomaly detection, and clear “Focus Areas” guiding user actions.

Real-Time Data Visibility

Live performance tracking, trend visualization across timeframes, and immediate feedback loops.

Personalization & Control

Custom dashboards per role, configurable widgets, and flexible data views that adapt to each user’s mental model.

ORBIT Analytics redesigned dashboard

Impact & Results

~35–45%Reduction in time-to-insight
Dashboard engagement increase
ZeroDependency on manual reporting
ScalableDesign system for future modules

“Rajesh has a deep understanding of user behavior and applies user-centered design principles to solve complex business challenges. His ability to conduct usability testing, heuristic evaluations, and competitive analysis ensures that every design decision is backed by data and insights.”

— Abhimanyu Verma, Agile Coach & Transformation Consultant

Key Decisions & Trade-offs

Chose card-based progressive disclosure over dense data tables — sacrificing information density for scanability. Prioritized role-based view customization over a single universal dashboard, increasing development scope but dramatically improving adoption across management tiers. Data visualization followed “clarity over decoration”: each chart type was chosen to answer a specific business question, not just display data.

Reflection

Good dashboards show data. Great dashboards drive decisions. ORBIT evolved from a reporting tool into a decision intelligence platform, enabling users to move from analysis to action faster than ever. In retrospect, I would have introduced micro-animations for state transitions earlier — the static-to-dynamic shift caused some initial user confusion during rollout.