Led the design of a VFX studio analytics application for Autodesk, based on feedback from user needs
Project Summary
While leading Shotgun's product design, my team and I regularly conducted 6-8 customer and potential customer interviews each week. It was imperative for me to ensure that my team had a deep understanding of customer needs and stayed informed about customers' perceptions of Shotgun and our competitors. During our research, we began to notice feedback from key customers who were either utilizing expensive tools like PowerBI or Tableau for managing analytics in their film/VFX projects, or were improvising their own analytics tools using a combination of Excel, PowerPoint, and other office tools.
Upon discovering these insights, I initiated discussions with our VP of Product and VP of Engineering to address the feedback from customers. Consequently, we swiftly assembled a small team to delve deeper into the challenges and explore the possibility of offering an add-on analytics service for Shotgun that was tailored for the industry and seamlessly integrated into the core platform.
Project Details
Role :
Product Design Lead
User Research Lead
Design Systems Lead
Product Designer
Duration :
1 year
Tools :
Miro, Figma
Challenges
Data Viz
User Experience
The platform was initially created 10 yrs ago and was showing its age. Originally built to be utilized by large film studios, it hadn’t changed to provide tools for smaller and more nimble studios like Netflix and streamers.
Shotgun's platform of products had been steadily increasing, causing their experience to become sluggish and difficult for new users. This led to a massive amount of "design debt," which negatively impacted the onboarding experience; consequently, prospective customers were left confused and frustrated as they struggled through an overwhelming setup process that required too many steps. As existing users found themselves spending excessive amounts of time configuring projects in Shotgun, it was perceived only beneficial for large-scale operations rather than smaller ones - we needed to make changes fast!
Results
Quickly utilized by 12/14 key customers in the beta
CSAT of 87 in the first 30 days as a MVP
Process
The framework we used to conduct the redesign of Shotgun’s core platform was a design thinking process, slightly modified for Lean UX to work with the product team better.
EMPATHIZE
DEFINE
IDEATE
PROTOTYPE
PROTOTYPE
TEST
Key
Team Members
Product
Design Lead
(me)
User
Researchers
Product
Designers
Design System Designers
Research
Drawing upon our research and insights gained from working closely with key customers, we crafted a vision for the analytics platform: to provide a robust tool for visualizing production data through Shotgun Production Insights, a new suite of analytics and reporting tools empowering studios to visualize essential production metrics, monitor project progress, and make crucial business decisions proactively.
In our pursuit to refine the analytics platform, we researched various report types and defined key metrics. Leveraging Shotgun's extensive database of tracked metrics and insights from industry publications on production data, VFX pipelines, and workflow efficiency, we acknowledged the pivotal role of individuals in the production process. The flexibility to scale production teams based on workload fluctuations emerged as a crucial factor in maintaining operational efficiency.
Subsequently, based on our research findings, we initiated a sprint to rapidly develop a minimum viable product (MVP). Emphasizing data visualization accuracy, we began with sketching before diving into design tools. Through an iterative process, we rolled out a beta version to key customers, followed by a 1.0 MVP release, and continued to enhance features based on user research-driven development.
We converted technical specs into loose personas.
Shotgun has a wealth of data to extract, analyze, and visualize to provide meaningful information. We recognized an opportunity and had already done some research by the this project got started. We condensed their research into digestible personas to gain alignment and define our scope.
Design
The increasing demand and intricacy of visual effects projects have prompted production companies to explore various methods to optimize their workflow. Accomplishing tasks efficiently and economically necessitates seamless coordination among multiple sites, departments, artists, and locations.
Producers are dedicating significant efforts to meet scheduling requirements, yet the existing array of tools available in the market falls short of adequately addressing their needs.
My design team needed to translate dense engineering requirements into an intuitive, out-of-the-box experience. The goal was to give studio leaders a high-level overview of the health of their projects, with the ability to dive into details to see how time and resources are used. We wanted to help streamline studio operations by removing the guesswork, and turning production data into real insights to make better decisions, faster.
After expanding our scope and securing team approval, we explored integration possibilities to create a cohesive system rather than an overly customizable dashboard. By carefully selecting which metrics to analyze and how to present them, we aimed to establish industry standards and enhance user experience within the Shotgun ecosystem. Our goal was to facilitate early bottleneck detection, enable detailed analysis, and prompt necessary corrective actions within Shotgun
Recognizing the varied user motivations for accessing the app, whether out of curiosity or specific information needs, we prioritized highlighting areas requiring immediate attention. This approach ensured that users could swiftly identify and address critical issues within their projects.
Our initial focus was on burndown charts, particularly in the realm of game development. To ensure accuracy in our visualizations, we developed a spreadsheet with idealized values to test the system's integrity at its most basic level. We identified hierarchy as a major challenge, understanding the significance of viewing both task breakdowns within a sprint and forecasting progress across the entire project.
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