data kit
A persona-led service-design project that sets up the Autodesk data community for success by enabling self-sufficiency
Project Challenge
The Autodesk Data Platform (ADP) serves as the centralized in-house system to deliver trusted data that powers the company's ability to understand and engage our customers. However, ADP lacks a standard process or toolkit for the community, specifically Business Intelligence teams, to be self-sufficient when onboarding their data sets and leveraging the platform's services.
As design lead for Autodesk, I put on both design and manager hat to hep lead this $500K project with Fjord Design Consulting. I worked closely with Fjord designers and researchers over the next 3 months to conduct interviews, moderate participatory workshops, prioritize and deliver solutions, and create a product roadmap for stakeholders and teams moving forward.
Product Solution
The research was documented and synthesized into key themes and a holistic journey map that we still reference today. Based on output from the workshop, we then developed:
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Getting Started Toolkit: A set of onboarding tools and material
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Product Offerings - A web portal for teams to understand the core components of the platform and guiding them towards next steps
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Data Quality Playbook - A vision and extensible data visualization tool teams to see all the health metrics of their data.
Involvement
UX Design/Research
Service Design
Design Thinking Workshops
Client
Autodesk
timeline
Apr-Sept 2018
teamates
Krizten Zhou - Product Manager
Daniel Chen - UX Researcher
Josh On - Interaction Designer
Jeffery Catania - Lead Data Designer
Meghna Dholakia - Service Designer
Divya Khane - Service Designer
Danielle Bergman - Project Manager
Annie Lin - Visual Designer
ux challenges
How might we set up teams for success by onboarding onto our data platform and utilizing our services in the most self-sufficient way possible?
the big picture
Interviews, User Journey Map
Before we dove into solutions, it was important to first align on the current state understanding of the ADP Onboarding process. That meant:
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Understanding from the perspective of Users how they thought and felt about the process of getting onto ADP, as well as
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Understanding the challenges and constraints faced by Stakeholders.
Because these two groups have completely different goals, we created appropriately tailored interviews. Stakeholders have a common wish to know the customer better so that they can create more meaningful and personalized communications but also to understand what triggers them to subscribe. Based on previous research, we also understood that the typical team is made up of three core roles--Data Engineers, Data Analysts, and Team Leads. These roles share a common goal but engage in different parts of the ADP system and therefore have different problems. First, we sought to understand and refine their role--collaboration structure, learning methods, tools used, etc. Secondly, we sought to deep-dive into their specific functions throughout the ADP engagement journey. Again based on previous research, we were able to identify 8 high-level phases. Not all users have been through each step of the process so we focused the interviews on appropriate steps of the process.
Finding Patterns
The following five Research Themes were a recurring pattern we saw throughout our findings. They helped give us a lens through which to look at the current state. We found them to be a valuable way of communicating our high-level findings. We also used these themes in our workshop and journey map.
Sharing One journey
Our User Journey Map expands on these themes by cataloging responsibilities as well as surfacing painpoints of both Users and Stakeholders throughout the entire ADP onboarding and engagement process. We used this artifact to develop a shared understanding of the current user experience
ideate, prioritize, deliver
Design Thinking Workshop
"Problems cannot be solved with the same thinking that created them," Albert Einstein once said. We brought this spirit into our workshop, as it was necessary to overcome antiquated structures and expert blindspots. Discover, Describe, Define, and Deliver: the iterative, four-step process was used to guide the workshop participants towards human-centered, innovative services and products that were based on the user insights that we surfaced over the past couple weeks.
Think Big!
We custom created 'How Might We' probes to start shaping responses to key opportunity areas. After sorting ideas based on similarity and identifying emerging themes & solution spaces, we then teams to generate, communicate and evaluate service ideas and concepts using Concept Card templates.
Let's Prioritize and refine
Teams then prioritized their Concept Cards into a cost value relationship in order to help build an understanding of trade-offs. Teams then picked a concept to deliver as future state experience.
Now Narrow and Deliver
With a heap of valuable qualitative information, we sought to make sense of it all. Our core team then conducted our own internal workshop to identify and develop core product solutions.
product solutions
Product Offerings
Design Thinking, Data Visualization
We created an internal product offerings catalog for ADP that would live on the Data Portal--which continues to serve as the sole webpage for all things ADP. It guides the Business Team to understanding the core components of the platform and guiding them towards next steps.
Driving Painpoints
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Teams are aware of ADP, but not clear on the best way to leverage it.
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Business Teams reach out directly to varied contacts within ADP based on personal relationships.
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Teams may have insufficient information to create accurate engagement request. This causes Stakeholders to have differing perspectives on how to prioritize teams, leading to confusion
Getting Started Toolkit
Design Thinking, Data Visualization
We created a core set of touchpoints for rapid enablement of Business Intelligence for Business Teams, and to help a Team to set clear data and platform dependencies and track build progress.
Driving Painpoints
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Understanding what resources are required means understanding the end-to-end ADP process. Teams are not given clear instruction of what resources they will need or where to find them.
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Wiki has a lot of available content, but is difficult to search and find relevant content. Direct links are prized and shared between users.
Data Quality Playbook
Design Thinking, Data Visualization
We established a vision for Business Teams and data readers to see all the health metrics for ADP data. The ecosystem is table-centric, extensible, and allows for real-time notification of failure.
Driving Painpoints
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The ADP data catalog is highly complex, and business teams struggle identify which tables are useful
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Data lineage is critical to understanding how data can be used, but that meta-information is hard to find.
Data Quality Workshop
Data Quality Dashboard
The dashboard itself was meant as an intuitive interface for all levels of data users to see all health metrics for ADP Data
Trusted System
We created a system that would let users understand the credibility of various data sources data tables, and dashboards.
We understood creating a data quality dashboard and system was essential. However, we needed to generate valuable scenarios, narrow down information architecture, and represent information in a way that would meet our user's needs.