How I transformed a static dashboard
into a flexible data playground (that profits!)
How I transformed a static dashboard into a flexible data playground (that profits!)
During my time as the Founding Designer at Avnet, I led a strategic design shift of our supply chain platform, Proscal, transforming it from a free Power BI host into a scalable, revenue-generating SaaS product with features comprehensive enough to support a tiered pricing model.
This case study walks through one of the key 0→1 features I designed and launched that empowered analysts to make data-driven decisions with greater flexibility and confidence.
During my time as the Founding Designer at Avnet, I led a strategic design shift of our supply chain platform, Proscal, transforming it from a free Power BI host into a scalable, revenue-generating SaaS product with features comprehensive enough to support a tiered pricing model.
This case study walks through one of the key 0→1 features I designed and launched that empowered analysts to make data-driven decisions with greater flexibility and confidence.
Role
Founding UX Designer
Founding UX Designer
Timeline
Launched in 3 months
Launched in 3 months
Keywords
#SaaS, #0 to 1, #Strategic
#SaaS, #0 to 1, #Strategic
Impact
Impact
This feature among with other design initiatives led to a significant increase in user engagement. The platform began attracting more enterprise customers across EMEA and APAC, with potential to generate up to 3% of their annual contract value as recurring revenue. These outcomes reflect a successful shift from passive data extraction to active in-platform analysis.
This feature among with other design initiatives led to a significant increase in user engagement. The platform began attracting more enterprise customers across EMEA and APAC, with potential to generate up to 3% of their annual contract value as recurring revenue. These outcomes reflect a successful shift from passive data extraction to active in-platform analysis.
150%↑
Average session duration
92%
Satisfaction rate
20+
Global enterprise customers
3%↑
Recurring revenue potential
Context
Context
Proscal is a supply chain platform with dashboard + analytical features that could unlock new revenue in a tough market
Proscal is a supply chain platform with dashboard + analytical features that could unlock new revenue in a tough market
The platform began as a free service add-on built on customers' requests. Supply chain analysts would select dashboards and features they wanted and track performance. However, as competitors began monetizing similar platforms in a tough market, our market share was at risk. We saw the opportunity to turn Proscal into a revenue-generating product, helping Avnet stay competitive and create a new revenue stream.
The platform began as a free service add-on built on customers' requests. Supply chain analysts would select dashboards and features they wanted and track performance. However, as competitors began monetizing similar platforms in a tough market, our market share was at risk. We saw the opportunity to turn Proscal into a revenue-generating product, helping Avnet stay competitive and create a new revenue stream.
The Problem
The Problem
Users abandoned the platform for Excel,
causing low engagement and low perceived value
Users abandoned the platform for Excel,
causing low engagement and low perceived value
Although 45.2% of MAU use the product on any given day, they were not actively engaging with it. Average engagement time per user is less than 5min, and most users only visited 20% of the dashboard pages. Users left the platform to do their work. The experience fell short of what users would expect from a paid product.
Although 45.2% of MAU use the product on any given day, they were not actively engaging with it. Average engagement time per user is less than 5min, and most users only visited 20% of the dashboard pages. Users left the platform to do their work. The experience fell short of what users would expect from a paid product.
Why It Happened
Why It Happened
The root causes and its chain reactions
The root causes and its chain reactions
Data visuals
were not enough
Dashboards cannot be tailored to individual analysts' needs. When their questions went unanswered, they switched to Excel to run their own analysis.
Dashboards cannot be tailored to individual analysts' needs. When their questions went unanswered, they switched to Excel to run their own analysis.
Long
turnaround
Long
turnaround
Users had to wait for dashboard updates. Maintaining all those custom dashboards also became a hassle.
Inefficient
collaboration
Inefficient
collaboration
Since all collaboration happened through emails, multiple file versions made it hard to collaborate.
Data
exposure risk
Data
exposure
risk
Communicating through emails exposes sensitive data to unauthorized access and increases the risk of breaches
From Vision to Action
From Vision to Action
What if users can create their own dashboards within the platform and share it with others?
What if users can create their own dashboards within the platform and share it with others?
With the team inspired by the IKEA effect and aligned on a vision of "proactive intelligence," I started analyzing our users’ workflows to make the transition to this feature frictionless, especially for non-technical users.
With the team inspired by the IKEA effect and aligned on a vision of "proactive intelligence," I started analyzing our users’ workflows to make the transition to this feature frictionless, especially for non-technical users.
Behind The Scene
Behind The Scene
Prototyping, testing, and more
Prototyping, testing, and more
How I aligned with the team using rapid prototyping?
I kicked off the design process by rapidly prototyping the chart creation feature with developers. This prototype refined requirement to let users to build multi-chart dashboards to tell a story. Involving developers from the start also accelerated the MVP process later on.
I kicked off the design process by rapidly prototyping the chart creation feature with developers. This prototype refined requirement to let users to build multi-chart dashboards to tell a story. Involving developers from the start also accelerated the MVP process later on.
How I decided on visual structure through experiments?
I created multiple versions of design elements and tested with the internal team and users. Through filtering the feedback and iterating, we landed on the final structure.
I created multiple versions of design elements and tested with the internal team and users. Through filtering the feedback and iterating, we landed on the final structure.
Final design: left edit panel
Maximizes space for charts, enables real time edits
Version 2: bottom edit panel
Occupies too much screen space
Version 3: Pop-up edit panel
Disrupts editing flows
How I ensured scalability and accessibility?
I explored different color options and panel layouts to support additional chart types and ensured the colors were accessible and compatible with diverse chart palettes.
I explored different color options and panel layouts to support additional chart types and ensured the colors were accessible and compatible with diverse chart palettes.
Final design
Ensures accessibility, maximizes content
Version 2: different color combo
Not compatible with customers' theme colors
Version 3: different layout
Shows less information, not suitable for more chart types
Final Design
Final Design
Playground: A dynamic space to
build, customize, and share data visualizations
Playground: A dynamic space to
build, customize, and share data visualizations
A frictionless transfer to the new workflow
To help our non-technical, Excel-centric users seamlessly create visualizations in Playground, I designed the workflow to align with their existing habits.
To help our non-technical, Excel-centric users seamlessly create visualizations in Playground, I designed the workflow to align with their existing habits.
Edit panel
Reflecting users’ existing habits, the workflow begins with choosing a chart type, and configuring the visualization by assigning the X and Y axes.
Reflecting users’ existing habits, the workflow begins with choosing a chart type, and configuring the visualization by assigning the X and Y axes.
Main view responsive grid
To balance user flexibility with development feasibility, we introduced a default responsive grid system. Each row can fit up to 4 KPI cards, 2 visualization components, and 1 data table.
To balance user flexibility with development feasibility, we introduced a default responsive grid system. Each row can fit up to 4 KPI cards, 2 visualization components, and 1 data table.
Filter panel
The filter panel draws inspiration from a tool users know well, Power BI. It remains minimal by default, yet gives users the flexibility to filter data across the entire page when needed.
The filter panel draws inspiration from a tool users know well, Power BI. It remains minimal by default, yet gives users the flexibility to filter data across the entire page when needed.
Creating a fully customized dashboard with ease
Playground lets users follow familiar Excel-like steps to explore data visually by picking a chart type then plotting the data. It lowers the learning curve and empowers users to illustrate what they need.
Playground lets users follow familiar Excel-like steps to explore data visually by picking a chart type then plotting the data. It lowers the learning curve and empowers users to illustrate what they need.
Collaborate with consistency and data security
Once users build charts, they can turn it into a shareable dashboard and send it to teammates. This promotes transparency, reduces duplicated work, and keeps everyone aligned.
Once users build charts, they can turn it into a shareable dashboard and send it to teammates. This promotes transparency, reduces duplicated work, and keeps everyone aligned.
Two-level filtering for flexible analysis
There are page-level filters that apply across all charts, and individual chart filters for more granular analysis. This structure allows analysts to view trends while still enabling deep dives into specific datasets.
There are page-level filters that apply across all charts, and individual chart filters for more granular analysis. This structure allows analysts to view trends while still enabling deep dives into specific datasets.
Start Fast with Dashboard Templates (Future iteration)
During MVP testing, I uncovered a common use case: analysts frequently used this feature to create with consistent visual structures. Inspired by tools like Notion, I designed a phase 2 update that provides pre-designed dashboard templates to help users skip the setup and focus on insights.
During MVP testing, I uncovered a common use case: analysts frequently used this feature to create with consistent visual structures. Inspired by tools like Notion, I designed a phase 2 update that provides pre-designed dashboard templates to help users skip the setup and focus on insights.
Results
Results
Driving user engagement and platform value
Driving user engagement and platform value
High satisfaction, high engagement
After launching the MVP to 3 customers and testing with 89 users, the majority agreed that the feature effectively addressed dashboard limitations and streamlined their workflows.
After launching the MVP to 3 customers and testing with 89 users, the majority agreed that the feature effectively addressed dashboard limitations and streamlined their workflows.
150%
average session duration
increase for adopters
92%
Satisfaction rate
among early adopters
7/10
Value score
of willingness-to-pay
2
dashboards created
per user per week
Creating potential revenue stream
This feature marks the first step in our strategic transformation from a passive dashboard service to a standardized, revenue-generating analytics platform. It lowered the internal operational effort, and brought a positive revenue forecast.
This feature marks the first step in our strategic transformation from a passive dashboard service to a standardized, revenue-generating analytics platform. It lowered the internal operational effort, and brought a positive revenue forecast.
70%
less support tickets
related to dashboard customization
3-5%
incremental revenue increase
once fully launch with upcoming premium offering
Reflection
Reflection
What users want ≠ need:
We needed to break out of the reactive pattern
What users want ≠ need:
We needed to break out of the reactive pattern
Through a series of research and user feedback, we realized that simply “building what they requested” was not enough to create a product worth paying for. The team needed a strategic shift to set the direction for the next stage of development and actively expand feature offerings.
Through a series of research and user feedback, we realized that simply “building what they requested” was not enough to create a product worth paying for. The team needed a strategic shift to set the direction for the next stage of development and actively expand feature offerings.
From executer to initiator
From executer to initiator
Leading this project allowed me to step beyond executing assigned tasks and take ownership of the product vision. I drove research, synthesized insights, and translated them into strategic design decisions that balanced user needs, business goals, and technical feasibility. These requirements encouraged me to think critically about prioritizing the product roadmap and to constantly evaluate which new features would deliver the most value without overextending the team and the timeline.
Leading this project allowed me to step beyond executing assigned tasks and take ownership of the product vision. I drove research, synthesized insights, and translated them into strategic design decisions that balanced user needs, business goals, and technical feasibility. These requirements encouraged me to think critically about prioritizing the product roadmap and to constantly evaluate which new features would deliver the most value without overextending the team and the timeline.
Up Next
Designed by Hailey Yixuan Li
Up Next
Designed by Hailey Yixuan Li