Data experience

The Product

The platform is an Operating System (OS) that brings together all of the services and products available to all 14 agencies in the company, becoming a daily destination for its 114k employees in internal teams and their clients. 

This OS helps maximize the company’s internal know-how. The number 1 goal is to unify the multitudes of ways agencies work and streamline their collaboration, especially when jointly delivering on client projects. The platform offers shared core functionality such as: authentication, administration, project management, product market place, developer hub, data catalog. An advanced design system powers it all, unlocking tenant theming and enabling agency teams to build their products. 

To support daily business needs such as pitching, running campaigns, collaborating with clients, the platform offers a project management solution, with products/applications that can be added to the workflow and run directly inside the OS. It lets users add team members, due dates, tasks, workflow templates etc. Here employees and clients collaborate and coordinate in fully customized and themed environments.

In this case study, we’ll focus on the data catalog, where data scientists can find answers to their clients problems by discovering data available across the company and from providers, getting access and learning about how it’s used by  interacting with colleagues through data communities.

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The Problem

The current data experience is problematic for many reasons.

1. Data resources in the company are distributed across agencies, teams, and individual colleagues, resulting in poor visibility into available resources. 

2. A competitive spirit and lack of channels between agencies leads to poor collaboration.

3. Lack of best practices leads to networking and personal knowledge being prioritized instead of process. Communities could help get support and knowledge sharing 

4. Access approval and provisioning process happens manually and is not transparent. Users don’t understand how to get access to data and when they do the approval process turns out to be lengthy.

5. Currently, a 3rd party solution is used for data cataloging and management. This poses some problems: little or no room for customization; a tool that’s not part of the OS results in a broken experience; users struggle to find it unless they’ve been told about it. 

6. To address these problems agencies have been building their own proprietary products.

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The Goal

Design a central solution which would cater to the needs of data teams across agencies, improving the discovery, access approval, and knowledge sharing experiences.

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My Responsibilities

• Conducted extensive research, crafted user journey maps and service blueprints. 

• Formulated key problem statements using How Might We's. 

• Validated solutions through usability testing.

• Structured the Information Architecture and user flows.

• Created a clickable prototype illustrating the UX Concept.

• Facilitated workshops and ideation sessions with stakeholders from multiple organizations. 

• Collaborated closely with product teams that developed similar solutions. 

• Regularly communicated progress, research findings, and future steps to C-Level stakeholders.

• Prepared and delivered demo presentations to the wider company and gathered feedback through surveys.

 

My Approach

1. Product discovery

2. Competitor analysis

3. User journey map

4. Service blueprint 

5. General structure/information architecture

6. UX design concept prototype

7. Usability testing, insight synthesis and analysis, formulate HMWs

8. Present to C-Level stakeholders

9. Ideation with stakeholders and users

10. Iteration on the UX design concept prototype

11. Demo video and feedback 

Step 1: Product discovery

In January 2023 my team and I did an extensive discovery phase. We ran 25+ interviews with data users, which helped identify pain points and opportunities. We spoke to data producers and consumers, including data scientists and analysts, data strategists and managers, product managers and owners.

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Step 2: Competitor analysis

Next, taking the initial research findings into consideration, I reviewed the existing solution. Users were mainly complaining about an inefficient search, lack of a transparent access request process, and an outdated UI. Some users didn’t even know the product existed and was being used across the company. Others were saying they thought it was long abandoned and out of use. Clearly, the data experience had to ultimately become part of the central OS.

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Also, I reviewed the proprietary products that agencies were building internally to solve the problems which most affected their business, e.g. one agency built access provisioning software, while another agency built a proprietary data catalog for one of their clients. I connected with these teams so that I could learn about these solutions and the problems they were solving, to make sure the new solution would solve them too. 

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Aside from this, I reviewed popular data catalogs such as Kaggle, Datarade, Snowflake Marketplace and others to see how they were solving the discovery, access and community pieces.

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Step 3: User journey

Aside from the standard swimlanes on the user journey map (steps, actions, emotions, needs, pains, opportunities) I usually add a couple very important swimlanes that give more context: 

• Quotes. Here I paste direct quotes from user sessions in correspondence to each step. This allows anyone who’s reading the user journey map to step into the user’s shoes, promoting empathy. 

• How Might We’s. In this swimlane, I try to distill the actual design problem, by piecing together the information from other swimlanes. 

• Ideation. This is where I paste solution ideas as they come to me throughout the design process (which as much as I’d like it to be, isn’t always linear) or in ideation sessions.

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Step 4: Information architecture

To show where the data experience would sit on the platform among other services, I put together a very high level general sitemap. This exercise helped navigate the conversations with stakeholders who had conflicting opinions.