Data Catalog

Unifying data discovery and access across WPP

In this case study

As a Senior Product Designer, I created a future vision for the Data Catalog experience on WPP's enterprise platform, which is a daily destination for 150K+ employees globally. Teams across the organization relied on fragmented resources and personal networks to find and access data. Incosistent data access approval flows and long access approval times were also a problem. Through 25+ interviews with data producers and consumers, I discovered that users rarely knew exactly which dataset they needed. This insight shifted the initiative from improving search to reimagining the broader data experience.

My role

Senior Product Designer

Year

June 2023 - June 2024

The client

WPP

The Product

WPP Open is an enterprise platform and daily destination for WPP's 150K+ employees, bringing together services, products and data in order to streamline collaboration and delivery.

In this case study, we’ll focus on the Data Catalog, where data scientists can discover data across the company to help solve client problems.

The Problem

Data teams lacked a centralized way to find data available in the organization.

The existing third-party catalog was poorly integrated into the WPP platform.
Requesting data access was manual and difficult to track.
Cross-agency collaboration was challenging because of a lack of established communication channels between siloed agencies.

The result was fragmented data discovery, duplicated internal solutions, and limited team collaboration.

The Goal

Help teams across agencies more easily discover and access relevant data resources.

My Role & Ownership

I led UX discovery and concept development for the Data Catalog. I conducted and synthesized research, defined the information architecture and key flows, built and validated the prototype, and translated a complex access process into a service model spanning requesters, data owners, approvers, legal and technical teams.

I also facilitated working sessions with stakeholders across agency teams and regularly presented research and product direction to C-level stakeholders.

Product discovery

My team and I conducted an extensive discovery phase, including 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. Here is what we learned:

Users struggled to find relevant data across fragmented agency resources.
Users were struggling with access approval: lengthy wait times, opaque processes, multiple roles involved, difficulty tracking their own requests.
Some teams were already building local tools to meet their own needs.
Users struggled with the third-party solution currently in place: an inefficient search, lack of a transparent access request process, and an outdated UI. Some users didn’t even know the product existed; others thought it had long been abandoned.

Competitor analysis

Taking the initial research findings into consideration, I did a UX review of the existing third-party solution, data.world.

I collaborated with internal WPP teams building proprietary products to solve the problems which most affected their business, for example:

one agency built access provisioning software,
another agency built a proprietary Data Catalog for one of their clients.

This exercise helped me understand the problems they were trying to solve and ensure I took them into account.

I reviewed popular data catalogs such as Kaggle, Datarade, Snowflake Marketplace and others to see how they approached discovery, access and community.

The opportunity wasn't just to build another catalog. The existing solution struggled with discovery and access transparency, agency-built tools solved individual pieces of the problem, and external marketplaces offered stronger discovery. None of them addressed WPP's cross-agency governance and knowledge-sharing needs.

User journey

While mapping the current user journey, aside from the standard swimlanes, I added direct user quotes from user sessions alongside each step. This helped stakeholders connect to the user’s actual experience.

Defining Data Catalog's place in the platform

Stakeholders had different views on where the experience belonged: some saw it as part of Marketplace, while others saw it as part of Developer Hub. I mapped the wider platform and core journeys to clarify the product's primary user and purpose. This helped align stakeholders around Data Catalog as a distinct experience centered on data discovery and access.

First concept & validation

I translated the initial research into a testable end-to-end concept covering data discovery, dataset evaluation and requesting access.

Usability testing and insights

In sessions with 7 data scientists, we looked at the existing solution and validated the new UX concept. I asked users to complete prompt-based tasks around searching, filtering, browsing and viewing dataset details, and explain how they decided which dataset to choose. The main insight was:

Users didn't need search.

They needed to find data solutions to client problems.

They have a client problem that they don't know how to solve, so they are more likely to browse, not search.
When selecting a dataset, users need to understand how a particular dataset has been used before and reach out to those colleagues to ask specific questions about the dataset.
When selecting a dataset, users need to understand what data it contains, in which format and how it's structured.
When looking for datasets, users need to see what resources are readily available to them and their agency, so that they can use them immediately in client proposals.
They want a more transparent access flow, so that they know what to expect when requesting a dataset and so that they can track their access requests.

How Might We questions

Finally, I defined three How Might We questions to guide ideation sessions with teams.

How might we create a meaningful discovery experience for users who browse, search, or don't yet know what to search for?
How might we create a seamless access approval and data provisioning flow?
How might we connect users to knowledge, experts and necessary support?

Ideation sessions

To solve the access problem, I brought subject-matter experts from multiple agency teams together for an ideation session to address one of the HMWs: How might we create a seamless access approval and data provisioning flow?

Design - Ideation workshop - affinity groups (2).jpg

Service blueprint

After the ideation session, I synthesized the input into a service blueprint showing the actions of the dataset requester, the corresponding system events, and the actions of other users, including approvers, managers, data owners, legal and technical teams.

Access Management blueprint: Requesting dataset

UX Design Decisions

Design discovery around client problems, not only dataset names

Testing showed that users often didn't know what to search for. Users don't need another data catalog. They need to find data solutions to client problems. I expanded the catalog concept beyond search and filters to include curated browsing and AI-assisted natural-language discovery.

Show access conditions before users commit

I surfaced access signals such as availability, expected approval time and cost earlier in discovery so users could judge whether a dataset was realistically usable before starting a request.

AI-assisted natural-language search ("How can we promote plant based milk?") and curated categories (Free, WPP Recommended) that support browsing.

Enable easier decision-making and knowledge sharing

Users evaluating a dataset wanted to understand three things quickly: “Is it relevant?”, “What exactly am I getting?”, and “Can I trust it?”

I surfaced key decision criteria upfront, made the actual dataset contents visible before access, and added evidence of real-world usage through client applications, case studies and reviews.

Discussions, contacts and related datasets then supported the broader goal of turning the catalog into a place for discovery, expert knowledge and cross-agency collaboration.

Standardize the experience, not the approval process

Each agency had different governance requirements and approval chains, so a single fixed workflow wouldn't scale across WPP.

Instead of standardizing the approval process, I designed an approval workflow configurator that could support any agency's underlying governance requirements and approval processes.

I introduced request management for dataset owners, configurable approval flows and request-status visibility so requesters could understand where a request was blocked and who owned the next step.

For owners, I designed:

an approval workflow configurator to help them build custom access approval flows,
incoming request management,
provisioning configuration: manual or automated, with conditional rules.

For requesters:

estimated approval time, helping users understand how long getting access is likely to take,
visible request status, so that they can track each request,
owner of each approval step, so that they can contact the right person directly if a request is blocked.

Access request details where the user can see the step status and the owner of each step. In case the request is blocked, the user knows who to contact.

Takeaways

Users weren't looking for datasets.

They were trying to solve client problems.

A better search box was not going to help them – they didn't know exactly what they were looking for. The answer could come from many places: browsing, searching, filtering, asking a colleague, asking the AI Assistant, stumbling across a case study that talks about how a particular client problem was solved in the past, seeing a post that mentions a particular dataset in the community discussions, etc.

This insight changed the initiative from search improvement to problem-led solution design. Search was important, but discovery also needed to support exploration, natural-language questions, existing use cases, expert knowledge and a clear path to access.

Impact

Validation & organizational reach

My team and I conducted 25+ discovery interviews with data producers and consumers to understand how teams found, evaluated and accessed data across WPP.
I validated the concept with 7 data scientists, influencing product direction around discovery, access transparency and knowledge sharing.

Cross-agency alignment

Worked across agency teams with different products, priorities and governance processes to define a shared target experience.
Prototyped the competing product-positioning directions, helping align stakeholders around Data Catalog as a standalone product.
Shared the concept company-wide through a demo video published on the platform homepage, broadening awareness and gathering more feedback.

The concept became a reference point in WPP’s discussions with the existing supplier.

I shared my concept with WPP’s data catalog provider, data.world, as an example of the experience WPP wanted to achieve.
After leaving the project, I learned that the supplier improved its product offering, and WPP ultimately continued with the existing solution.