Panorama

Enterprise Tool • End to End • Data Visualization

Panorama is an internal tool designed for Uber to monitor, diagnose and resolve ride-sharing marketplace issues.

! Important: data in this page is for illustration purpose only and doesn't represent any real business numbers.

time

2019/2020

client

Uber

role

Lead Designer

data in this page is for illustration purpose only and doesn't represent any real business numbers.

Project Summary

Panorama is a brand new product that we designed from scratch in 2019. I was involved from the very beginning of the product planning, and led the key design activities throughout this project.

 Phase 1
Product Vision
Concept Design

My Role: Team Lead

 Phase 2

Fundamental Research

My Role: Support

 Phase 3

Product
Definition

My Role: Support

 Phase 4

MVP
Design

My Role: Design Lead

Where it all started

What is our Product Vision for 2020?

Asked by our head of product. To answer his question, we hosted a 3.5-day Design Sprint to collect insight and generate ideas. After the Design Sprint, I led a team of 3 designers to develop high fidelity concept and craft a storyline for the northstar experience

Picture: slides from the Design Sprint and Concept DesignSlide (intentionally blurred)

Slides Blurred.png

What happens after concept design

Turn Vision into Reality

We started from one of the concept directions. With a vision that got buy-in from leadership, we got the resource to do fundamental research so that we can validate the problems and dig into the details of use cases.

Research Outcome

3 Personas

3 Problems

01

Fragmented Workflow

Constantly jumping between many data sources, copy & pasting information, and resetting filters to obtain desired views hampers productivity.

02

Siloed Intelligence

Each existing tool offers only a slice of the domain, and altogether painting an incomplete view of the markets.

03

Insufficient Dimensionality

Deeper analyses are not possible due to the lack of suppor tin slicing and comparing the data in a meaningful way.

9 User Needs

Seasonality

Extended Data Source

Trust

Metric Standardization

Segmentation

Latency and Outage Info

Contextual Information

Data Comprehension

Reliability

Design Principles

Holistic

Standardization

Dimensionality

Framework

3 Tiers

Territory, City, Neighborhood

4 Exploratory Modules

Data Table, Time Series, Geo, Map, Heatmap

4 Segmentation Types

Product, Geo Location, Time, User Cohort

More details available upon request.

© 2020 by Fiona (Muyao) Ding. All rights reserved.