WaveScape

WaveScape SFU Redesign

Transforming large-scale mmWave network planning into a seamless, scalable experience for global telecom carriers.

+60% Faster Planning Time

-40% Fewer Errors

3x Less Support Tickets

+83% Coverage Rate

Scaling Network Planning for Suburban Complexity

When planning fixed wireless access (FWA) networks, speed and precision are everything — especially across large, suburban environments where 5G mmWave signal behavior can vary block by block.

WaveScape was already powerful for small-scale deployments, but as enterprise customers expanded to 100+ km² rollouts, the cracks started to show.

Users struggled to preview where coverage would succeed or fail before committing to a full run.
Candidate site management became overwhelming — especially without GIS support or bulk tools.
Most critically, the workflow wasn’t built to scale. It assumed a linear setup process in a world where engineers needed flexible experimentation and data-driven iteration.

It was clear we needed a new experience — one purpose-built for regional-scale deployments and collaborative planning cycles.

I led the end-to-end redesign of WaveScape SFU, crafting a new user journey from area definition through optimization — and aligning it with how RF engineers actually work.

Collaborative Impact

As demand surged for suburban FWA coverage, our legacy tools hit a breaking point. They struggled with large-scale planning areas, international GIS formats, and rigid, manual workflows—limiting our ability to scale.

Planners were losing time wrestling with data prep and unclear results. We needed a smarter, faster experience—purpose-built for scale, flexibility, and global deployment.

My Role

Lead UX Designer

Duration

6 months

Team

Cross-functional team of 12

(3 UX, 4 Engineering, 2 Product, 3 RF Domain Experts)

Key Responsiblities

Defined the end-to-end UX strategy for a new SFU planning workflow

Facilitated alignment across product, engineering, and RF stakeholders

Designed scalable site configuration and signal visualization

Shaped MVP scope and tradeoffs in collaboration with PM and RF leads

UX

Product

RF

Engineering

Cross-functional collaboration was essential—from system architecture to on-the-ground workflows.

The Challenge

As demand for suburban FWA grew, our current tools struggled to keep up. They weren’t designed to handle massive coverage areas, international GIS formats, or complex site workflows—especially at scale.

The Core Problem

Planning teams were spending 4–5 days on tasks that should’ve taken 2–3. The interface lacked support for bulk workflows or reusable site logic. New users took weeks to ramp up, and international teams struggled with GIS file compatibility and terrain data issues.

Operational Issues

Metrics & Friction

Manual site selection and prep slowed down planning

Projects ran 40–60% slower than expected

Poor GIS integration limited global use

3x more support tickets than similar tools

New users struggled with onboarding

User satisfaction fell in the bottom 25%

Legacy interface didn’t support 100+ sq km areas

International teams blocked by terrain data constraints

Legacy interface:

No overlays, presets, or GIS upload options—users had to input parameters blind, slowing down work and increasing support tickets.

Research & Discovery

To understand the full scope of the problem, I led foundational research with field teams to uncover real-world workflows and usability gaps. While we had a single setup flow, it became clear we were serving two very different types of users with very different needs.

Methods

23 Contextual Interviews

Conducted across 2 telecom organizations to observe planning workflows, friction points, and team dynamics

Competitive Analysis

Benchmarked 5 enterprise and adjacent planning tools to uncover UI/UX gaps and best practices

Technical Deep Dives

Collaborated closely with RF engineers and architects to understand system logic, constraints, and user edge cases

User Types & Insights

Expert RF Engineer

Needs

Full control, advanced configuration, detailed outputs

Pain

Pain: Rigid tools slowed down power users and introduced unnecessary friction

Pain

Network Planner

Needs

Guided workflows, clear progress visibility

Pain

Confusion around parameters and interpreting results

Key User Pain Points

Too many settings shown at once

Users felt overwhelmed by too many settings at once

No context preservation

Context preservation was critical for workflows that spanned multiple days

Rigid GIS support

Workflow flexibility was needed to support localized GIS data constraints

Project Information

Coverage data

Site Configuration

SFU Parameters

U.S. → “Nearmap-supported”

Germany → “KML Upload Required”

Brazil → “Terrain file workaround used”

Design Principles

Progressive Disclosure

Only reveal advanced controls when users need them, keeping the interface approachable without limiting expert capabilities.

Contextual Relevance

Surface only the tools and options relevant to the user’s current step — minimizing distractions and decision fatigue.

Workflow Continuity

Preserve user inputs and selections across multi-day sessions to support real-world planning cycles.

Design Goals

Scalable at Any Size

Support planning areas of 100+ km² without sacrificing performance — essential for suburban and regional deployments.

Clear, Guided Flow

Help users move confidently through each step of the setup process with structured progression and visible status.

Built for Flexibility

Support a wide range of configurations including GIS uploads, bulk candidate site edits, and site-specific filters.

Instant Visual Feedback

Provide immediate signal qualification overlays — reducing uncertainty and helping users iterate faster.

Workflow Redesign

The legacy SFU experience wasn’t built to scale. Users jumped between disconnected tools, struggled to configure large areas, and lacked feedback when they needed it most.

We reimagined the entire workflow as a guided, end-to-end experience — supporting international formats, flexible site configurations, and scalable deployment planning.

Redesign at a Glance

Phase

Old Experience

Redesigned Experience

Define Area

Polygon tool only, no live stats or GIS support

GIS upload, AOI stats, and fallback support for global users

Configure Sites

Rigid CSV import, no bulk edits or visual validation

Map-based selection, bulk actions, and real-time input validation

Optimization Setup

Overwhelming list of parameters with unclear impact

Guided vs Expert modes with smart presets and tooltips

View Results

Data-heavy outputs with little clarity

Visual overlays, structured insights, and exportable summaries

1. Define Area

The Problem

Users often drew oversized or inefficient coverage areas, blindly guessing boundaries due to a lack of feedback. This not only slowed them down but introduced significant rework. For international users, GIS compatibility was another barrier—especially when Nearmap coverage was unavailable.

Our Approach

We reimagined the entry point of the workflow to empower users with immediate insight and flexibility. By layering in contextual cues and supporting diverse GIS file types, we helped users start smarter and adapt globally.

Key Improvements

Live AOI statistics show area, perimeter, and building counts as users draw—enabling better scope estimation.

GIS upload support allows teams outside Nearmap regions to bring their own data, removing blockers for global users.

Visual overlays (qualified buildings, polygon boundaries, heatmaps) provide real-time validation for better decisions.

The Result

Users were able to confidently define target zones on the first try—saving time, reducing rework, and unlocking SFU planning for non-U.S. deployments.

2. Configure Sites

The Problem

Candidate site management was rigid and error-prone. Users had to upload CSVs with no easy way to visually select, edit, or validate sites. Any change meant going back to spreadsheets—slowing down workflows and increasing the chance of mistakes.

Our Approach

We redesigned site configuration to be map-first. Users could now select, filter, and bulk-edit sites directly within the UI. We also introduced validation cues to reduce trial and error and increase confidence before optimization.

Key Improvements

We redesigned site configuration to be map-first.

Users could now select, filter, and bulk-edit sites directly within the UI.

We also introduced validation cues to reduce trial and error and increase confidence before optimization.

The Result

Users configured sites 2–3× faster with fewer errors. The ability to fine-tune directly on the map improved precision, and first-time success rates increased—especially for large or international deployments.

3. Optimization Setup

The Problem

The legacy setup panel overwhelmed users with dozens of technical parameters—no guidance, no presets, and no clear connection to results. Even expert users struggled to predict the impact of changes, while newer users felt paralyzed.

Our Approach

We restructured the panel around a Guided vs Expert Mode toggle. Guided Mode provided smart presets and helpful tooltips, while Expert Mode gave advanced users full control. We also grouped parameters into logical categories to reduce cognitive load.

Key Improvement

Mode toggle let users switch between a simplified view and full parameter control.

Presets and tooltips guided users through configuration without external documentation.

Grouped inputs (e.g. signal, placement, cost) made the form more intuitive and faster to complete.

The Result

Both novice and expert users completed setup with greater speed and confidence. Guided Mode reduced reliance on support, and Expert Mode unlocked deeper experimentation for power users—helping teams scale planning across different skill levels.

4. View Results

The Problem

The legacy results panel was data-heavy but insight-light. Users had to interpret raw tables and disconnected layers without visual summaries or decision-ready outputs—slowing down deployment and causing confusion during stakeholder reviews.

Our Approach

We redesigned the results panel to prioritize clarity, context, and exportability. Key outcomes were visualized directly on the map (e.g., coverage overlays, LOS lines), and summaries were grouped logically for fast insight. We also made exports more useful with downloadable reports and geospatial files.

Key Improvement

Results now appear instantly on the map with qualified/unqualified buildings, coverage zones, and site relationships

Summary metrics (e.g., coverage %, cost per unit) provide quick insights for decision-making

Export tools support multiple formats (PDF, KML, CSV) for cross-team use

The Result

Users could now understand optimization outcomes at a glance and confidently share results with internal and external stakeholders. This improved decision speed and made WaveScape a more trusted tool across organizations.

Results & Measurable Impact

Quantitative Results

The WaveScape SFU redesign delivered significant, measurable improvements across all key success metrics, directly enabling strategic business initiatives and international expansion.

60%

Faster planning time improvement

Network planning projects: 5 days → 2 days average

89%

Increase in user satisfaction

User rating improved from bottom 25% to top 10% of enterprise tools

12x

International market expansion

From 1 region to 12+ international carriers supported

64%

Reduction in support ticket volume

Fewer configuration errors and user confusion

Business Value

Enabled strategic international expansion

GIS flexibility and workflow scalability opened new markets

Delivered $2.3M operational savings

Annual cost reduction through improved efficiency

Lesson Learned

By balancing usability with power and laying down scalable patterns, this project became more than a redesign—it became a foundation for future growth.

Expanding GIS compatibility removed regional blockers, enabling international teams to plan deployments independently—unlocking new markets and reducing support friction.

I’d invest more upfront in performance testing with large datasets.

Involving field engineers earlier would have brought key operational insight to the research phase.

This modular workflow is now being adopted across the broader WaveScape platform.

By balancing usability with configurability and laying down scalable patterns, this project became more than a redesign—it became a foundation for future growth.