Brad Tober

The Publicis PeopleCloud Analytics Environment tackled a critical challenge for data scientists and analysts across the organization: obtaining secure, scalable access to analytical tools while maintaining cost controls and appropriate governance. I led the design of a comprehensive system with user permission controls, client-project hierarchies, and instance (a secure computing environment containing data and analytical tools) management capabilities that enabled analysts to provision their own computational resources within established guardrails. By spearheading both the design strategy and hands-on prototyping, I created a solution that dramatically reduced time to insights while providing management with visibility into resource utilization, resulting in significant savings on cloud computing costs while accelerating analytical output.

Business challenge

Prior to developing the PeopleCloud Analytics Environment, Publicis faced several key challenges revealed through user research and journey mapping:

• Fragmented infrastructure: Data scientists worked across disconnected systems, leading to inconsistent approaches, duplicated efforts, and variable security practices.
• Resource provisioning bottlenecks: Users required manual IT intervention to access computational resources, creating significant delays.
• Cost visibility issues: Decentralized cloud usage made it difficult to track, attribute, and manage analytics costs across clients and projects.
• Governance concerns: Limited oversight of data access and inconsistent security practices created the potential for compliance risks, especially for sensitive client data.
• Collaboration barriers: Analysts couldn't easily share instances or insights across teams, reducing knowledge transfer and best practice adoption.

The journey mapping exercise revealed that data scientists experienced significant friction at every stage of their workflow, from initial project scoping (the "entice" stage) through delivery (the "exit" stage) and maintenance (the "extend" stage). These challenges culminated in a situation where analytics capabilities were underutilized despite significant investments having been made.

Strategic approach

As the design lead, I developed and implemented a multi-phase methodology to address these complex challenges:

Discovery and user research

• Conducted in-depth interviews with data scientists, IT administrators, and business leaders.
• Facilitated the creation of a comprehensive journey map documenting the data scientist workflow across five stages: entice, entry, engage, exit, and extend.
• Synthesized research findings to identify key pain points and established core requirements for the solution.

Information architecture and feature planning

• Led cross-functional workshops to develop the client-project-instance hierarchy that reflected organizational structure.
• Architected role-based access controls with appropriate permissions for various user types.
• Designed a cost estimation system to provide transparency during resource provisioning, addressing financial accountability concerns raised by leadership.

Prototyping

• Instead of focusing on traditional static mockups, I transformed low-fidelity wireframes into a high-fidelity functional prototype in code using the Publicis Design System.
• This coded prototype served dual purposes as both detailed design documentation and a testable interface that stakeholders could interact with.
• Created user flow diagrams showing navigation paths between all system components, establishing a clear mental model for the system.

Implementation

• Collaborated with engineering leads to define MVP scope based on maximum value and feasibility.
• Directed the phased rollout plan, beginning with core functionality before expanding to administrative capabilities.
• Presented the solution to key stakeholders, securing buy-in for the approach and continued investment.

Team and collaboration

I collaborated with a cross-functional team including UX designers, frontend and backend developers, data scientists, IT operations personnel, and business stakeholders. My approach focused on:

• User-centered workshops: Designed and facilitated collaborative sessions with data scientists to validate designs and refine workflows.
• Alignment on technical feasibility: Established weekly meetings with development teams to ensure designs balanced user needs with implementation realities.
• Executive engagement: Prepared and delivered monthly steering committee updates to senior leadership, maintaining momentum and support.
• Building bridges: Actively worked to translate between technical and business stakeholders, ensuring all parties understood constraints and opportunities.
• Cross-platform integration: Partnered with the broader PeopleCloud ecosystem team to ensure a coherent and consistent user experience.

Outcome and impact

Under my design leadership, the PeopleCloud Analytics Environment delivered significant business results:

• Enhanced productivity: The self-service provisioning system I designed reduced environment setup time from days to minutes.
• Cost optimization: My instance lifecycle management features led to a significant reduction in cloud computing costs incurred by our users.
• Governance improvements: The role-based access controls I architected improved security posture and compliance.
• Accelerated insights: Analysts delivered client insights faster using the streamlined workflows I created.
• Improved collaboration: Project-based resource sharing increased cross-team knowledge transfer.

My innovative approach to prototyping was a key factor in the project's success and fundamentally changed how design was communicated across the organization. By creating a working model in code, I provided engineers with precise specifications that reduced misinterpretations and accelerated development. The result was a new standard for design documentation across the organization that bridged the gap between creative intent and technical implementation. This hands-on technical approach also built credibility with both the data science and engineering teams, positioning me as a leader who can advocate for users with respect to technical constraints.

Ultimately, user feedback validated my design decisions:

• "I can test ideas immediately without waiting for ad-hoc approvals."
• "Understanding costs upfront helps me make better decisions about resource allocation."
• "Being able to quickly stop and restart instances, rather than having to rebuild them, saves hours of setup time."
• "The interface is intuitive and feels like a natural part of our PeopleCloud ecosystem."

Experience the full coded prototype (with username protected and the password you used to access this page)

Reflection

This project shaped my leadership philosophy in several fundamental ways:

• Technical empathy: By immersing myself in both data science workflows and IT infrastructure concerns, I cultivated a leadership style that connects different technical specialties while preserving detailed understanding of each discipline's distinct requirements.
• Design as system thinking: I approach all design challenges by examining the entire ecosystem, not just isolated touchpoints (a perspective that was reinforced through the journey mapping exercise in this project).
• Coded prototyping as communication: Building prototypes with code has become central to my leadership toolkit—it creates clarity that static documentation simply cannot achieve on its own.
• Strategic influence: My ability to communicate complex technical concepts to executive stakeholders evolved significantly during this project, as I learned to frame technical decisions in terms of business outcomes.

My innovative approaches yielded several methodological advances that I've since applied to other initiatives:

• Journey-driven problem definition: The comprehensive mapping process I developed exposed systemic issues, allowing us to address root problems rather than symptoms.
• Design systems as accelerators: By leveraging and extending the Publicis Design System, I demonstrated how design systems can be platforms for innovation, rather than solely function as constraints.
• Prototype-driven development: The coded prototype approach I pioneered became a template for how complex user experiences could be documented and communicated across disciplines.

This project represents a pivotal moment in my leadership journey—where I combined technical expertise, design thinking, and strategic leadership to transform how an entire organization approached the creation of infrastructure for critical data science work.