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Korn Ferry

Korn Ferry Assessment Analytics

Product

Korn Ferry's Assess is a talent assessment tool that helps you predict whether your organization's workforce can deliver on its future strategy by examining skills, behaviors, and mindset individuals need for any given role.

Platform
Web app

Project timeline
This case study is currently a work in progress. Final deliverables and outcomes will be added once the project is complete.

My role
Senior UX Designer

Team
Designer, Product Managers, Engineers, Talent Consulting Experts, UX Researcher

Skills
Data analytics, UX design, UI design, user research, visual design

Tools
Figma, Make, 

Background & Problem

Develop an interactive analytics tool to evaluate potential talent

Korn Ferry is a worldwide firm that assists organizations in aligning talent with their strategic goals by matching to suitable roles, ensuring equitable compensation, and strong leadership.

Assess aims launch Interactive Analytics, a series of new data analytics reports and features that helps HR and hiring teams evaluate employees' potential by analyzing their behaviors and skills based on completed assessments. For the first time, we will collaborate with Tableau to enhance our analytics, offering a different approach than our in-house engineering team.

Bringing structure to a sea of unknowns

In my role as the UX Design Lead for this project, I oversee the discovery phase, plan and define epics, explore solutions, and manage product maintenance and iterations post. I work closely with product managers, Tableau engineers, and our consulting team on a weekly basis to ensure our designs align as we refine them. Currently, are in the test and prototype phase, where I take on a consulting role with our engineers to whether their software can accommodate our designs.

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Research & Insights

Collaboration with our stakeholders from the start

I conducted several UX kickoff workshops to align with our cross-team stakeholders, focusing on balancing user needs and business goals from this request. The workshops included a diverse group of product managers, consulting experts, UX researchers, and designers, allowing us to brainstorm initial thoughts and expectations for the initiative's desired outcome. Additionally, I facilitated an Assumptions Mapping workshop with a smaller team of involved in the decision-making process. This session helped us organize and prioritize our certainties, assumptions, and about the initiative, which helped us to identify gaps in our knowledge.

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Our UX kick off meeting involved everyone's input to gather perspective on the Interactive Analytics intiative.

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The Assumptions Mapping session helped us determine which questions to pose for each team involved.

Establishing design principles

 As we solidified our partnership with Tableau, we worked alongside our design system team to develop design principles that will steer our decision-making. We also created documentation to provide Tableau with the essential components and patterns that were crucial to our designs.

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  • Design for our users. Understand our users and advocate for the best user experience. Speak their language and use industry standard terminology where available.

  • Design for clarity and visual simplicity. Create a visual hierarchy for user tasks where needed. Reduce clutter and embrace white-space. Give our content room to breathe.

  • Design for focus. Keep our experiences focused. It should be clear to our users what they should do, no guessing.

  • Design for consistency. Our products are different, one size doesn't fit all. But achieve the same look and feel.

Build & Iterate

Understanding requirements and prioritizing user flows

We utilized Confluence to outline report requirements and FigJam to create task flows for each feature of Interactive Analytics. This initiative was divided into three projects, all existing within the same interactive analytics environment, but each with distinct objectives: Group Reporting, Talent Grid, and Talent Scorecard.

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Working alongside Tableau, we prioritized the order project development, and these task flows assisted us in identifying which projects were deemed more urgent by both our internal team and users.

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The exporting task flows for the word cloud report for both advertiser and creative ads

Different approaches with wireframing

A key piece of feedback from users is their desire for answers to their business questions. How can I evaluate this employee's skills and competencies against a specific Success Profile? Where can I find a consolidated view of this group's individual scores? What are the main strengths and areas for improvement for this individual?

Given the complexity of addressing all these inquiries in one place, I gravitated towards the concept of incorporating natural language into the data analytics field. This approach is straightforward, easy to comprehend, and provides evidence-based data that directly addresses users' questions. More so, we were able to utilize this method throughout all three projects, providing the user with consistency and familiarity with the Interactive Analytics space.

In addition to developing wireframes from scratch, I used Figma Make from prompt based designing as a sounding board to create more complex dashboards that fulfilled our project requirements.

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Wireframes that utilized natural language and modular configurability

Iteration from all angles

Our cross-team of Tableau engineers, consulting experts, product managers, UX researcher, and designer (including myself) meets twice weekly to synchronize on evolving requirements and project scope. We discuss updates from all teams and their potential impact on the project. In these meetings, I present mockups and guide the team through the anticipated user. Given the visual nature of data analytics, I collaborate with our accessibility design expert to select suitable colors that adhere to WCAG 2.2 AA standards or higher.

Implementation

Approved designs

As of right now, these designs have been signed off and are currently are in the development stage with our Tableau engineers. I consult with them daily to test the functionality of our designs within their software and adapt the designs if their functionality cannot support. 

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Conclusion

Key learnings & next steps

A need for the agile process
We worked in a more waterfall process that 
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