Paige Searles's portfolio

Bringing visibility to staffing data

Impact: Defined how staffing data should be structured and surfaced to HR and store leaders in an enterprise platform.

Methods: UI/UX design, conversation design, AI content design

Timeline: 4 months

Certain details of this case study have been modified to protect proprietary information.

Background

At a major U.S. grocery retailer, an open shift marketplace launched that enabled grocery store employees to view and request to work an open shift. This created a multitude of new data that grocery store leaders and HR leaders had not been able to access before. Due to the amount of data, how the data was presented in a meaningful way within the HR chatbot was a top priority. The project evolved to include a new AI layer within the experience that brought visibility to crucial data that could help leaders make faster, more informed decisions around staffing.

An open shift marketplace launched that enabled grocery store employees to view and request to work an open shift. This created a multitude of new data that grocery store leaders and HR leaders had not been able to access before.

Due to the amount of data, how the data was presented in a meaningful way within the HR chatbot was a top priority. The project evolved to include a new AI layer within the experience that brought visibility to crucial data that could help leaders make faster, more informed decisions around staffing.

My contributions

I collaborated with the design lead on this initiative and focused on the following:

Crafted conversation design flows, including dialog structure and suggested actions, within the HR chatbot to make the experience feel intuitive.
Designed UI for data on multiple levels like store level view, district view (group of stores) and for multiple personas.
Presented designs with the business often to get feedback and align the team on designs that would go into production.
Crafted AI output of open shift data to make it more readable and communicate expectations around the output of the tool.

I collaborated with the design lead on this initiative and focused on the following:

Crafted conversation design flows, including dialog structure and suggested actions, within the HR chatbot to make the experience feel intuitive.
Designed UI for data on multiple levels like store level view, district view (group of stores) and for multiple personas.
Presented designs with the business often to get feedback and align the team on designs that would go into production.
Crafted AI output of open shift data to make it more readable and communicate expectations around the output of the tool.

Views of the chatbot interface and store views of open shift data.

The approach

I crafted designs to focus on the open shifts available in the current week and upcoming week and leaned on data structure that the team had already used in the HR chatbot app to create design consistency across features. Focusing on showing data for the current week and upcoming week was a systems constraint. With the designs I crafted I presented initial designs to the business and development team to get alignment and make changes early in the design process and avoid rework later.

With the designs I crafted I presented initial designs to the business and development team to get alignment and make changes early in the design process and avoid rework later.

Design iterations of open shift data in the HR platform.

Challenges with edge cases

During the development stage it was found that some parts of the data took a long time loading which required careful thinking around how to present this data in the UI. I brainstormed with the design team to think through how data could be progressively loaded and then updated the final designs for handoff to the development team.

Surfacing an AI summary

The next phase of the project focused on incorporating generative AI component that would summarize data and call out data highlights. The main challenge now became how to create a seamless experience that made the open shift data feel connected to the AI component.

One of the main goals of the design was to communicate to Leaders that they could ask a follow -up questions through the chat about the AI data insights. I crafted many iterations using color, symbols and language to tie these two pieces of the experience together.

Accessible designs

During a design review it was identified that the colors chosen for the AI component could create an accessibility issue for those who have color blindness. This prompted the team to test color accessibility based on WCAG standards and make sure that the design did not use color as the only way to communicate that the AI content was tied to the open shift data.

Open shift data and AI summaries screens.

Outcomes

The open shift data experience and the generative AI data in the HR chatbot were launched and piloted at three grocery stores. This experience gives leaders visibility into this type of staffing data for the first time.

If I had more time on this project I would want to measure what parts of the tool are most frequently used by store and HR leaders and if having this data available does save them time with making staffing decisions.