Feature :

Data storage

Client

Pihr

2025

My role

UX UI

Pihr, a Stockholm-based SaaS company, offers the Pihr Pay Equality™ tool to help organizations address and manage pay gaps. The software provides automated analysis to identify salary disparities based on gender, race, and ethnicity, and generates action plans with salary adjustment recommendations, cost calculations, and more.

Pihr’s solutions also support job mapping, data drilling, reporting, and additional features. This helps HR professionals address pay disparities, ensure compliance with local and international regulations, and promote workplace equity and transparency.

My role at Pihr

I joined Pihr in 2022 as the sole in-house UX/UI designer. My initial focus was to redesign and repackage the Pihr Pay Equality™ software from the ground up. This involved creating a scalable and flexible design base to support both current needs and future growth.

From there, my work was centered on enhancing and expanding the software. Collaborating closely with stakeholders, I focused on improving existing features and introducing new ones. I worked to make the platform effective, user-friendly and intuitive for managing complex tasks like equal pay audits, compliance reporting, addressing pay gaps, analyzing trends, and more—all in one place.

Overview

01 Problem

Users performing Equal Pay audits faced manual, error-prone data management—preparing, editing, and storing data without system support. Errors required re-uploading, causing friction. There was no way to track versions, reuse sources, or share data efficiently. Without a clear data management system, users struggled with inconsistencies, limited traceability, and increased risk of unreliable audit results.

02 Solution

The focus of the solution was to redesign and extend the user flow from data upload to audit while introducing storage and mapping capabilities. Additionally introducings a comprehensive data management system to streamline Equal Pay audits.

03 Impact

The new data saving and mapping features greatly streamlined the audit workflow, reducing user friction and improving data consistency. This led to higher user engagement, fewer support issues, and a stronger competitive position. A key takeaway was the value of iterative development, which enabled effective problem-solving even without full initial clarity.

04 Deliverables

The updated workflow includes:

Upload & Data Storage: Save, reuse, and manage data sources within the system.
Data Source Table: Edit, handle errors, and map data directly in-platform.
Audit Integration: Link data sources to specific audits for full traceability.

Upload & Data Storage

Previously, data uploads were temporary, requiring users to re-upload data for each session—causing friction, especially for larger audits. There was no built-in support for traceability, version control, or data reuse.

To address this, a data storage feature was introduced, allowing users to upload, store, and reuse editable data sources within the system. This simplified data management and improved consistency across audits.

01

The new upload flow supports file uploads, data integrations, and selection of previously saved data sources. The system adapts automatically based on user context, streamlining the experience whether it’s a first-time upload or storage is already in use.

02

The improved upload flow supports file uploads, integrations, and reusing saved data sources, with the system automatically adapting to the user’s context for a smoother, more intuitive experience.

Data Source Table

A new in-system data source table allows users to view and manage data in one place before starting an audit, replacing the need for external tools. It introduces four key functions: error handling, data mapping, data editing, and data preview, reducing mistakes and improving efficiency.

01

The new error handling feature lets users identify and fix issues directly within the system, supported by an error list with links to affected cells and tips. Errors don’t need to be resolved immediately—users can save progress and return later, making the workflow more flexible and user-friendly.

02

Data mapping ensures mandatory PPE columns are correctly aligned by letting users match their data to the required format, fix errors, and create reusable templates. While most rely on the auto-mapped default template, users can edit or build custom mappings. Dynamic options simplify the process, adjusting based on data type (e.g., selecting “Group” enables Job Structure mapping), streamlining audits and saving time.

03

Users can edit data directly in-line, such as adjusting job structures or salary components—key for addressing pay gaps before reporting. Editing is especially important in the Actions tab, where individuals are linked to the data source, ensuring accurate and up-to-date audit results.

04

Data sources are directly linked to tables, allowing users to review and edit them anytime for greater flexibility. When multiple files are used in an audit, they’re organized into tabs within the table view for easier access and management.

Audit integration

The final step ensures that audits are fully integrated with stored data sources, allowing users to pick up where they left off without having to re-upload data. Also, it allows to track and compare l past audits as well as easily access and manage data sources from the audit page.

01

EXAMPLE

Process

Timeline: 12 weeks including development time.

01 Discovery

Due to an initially tight deadline, the project this time followed a process where design and development progressed in parallel, with design having a short head start. The product team provided a rough brief outlining the problem and required functionalities. Exploration and research began simultaneously, leading to a feature wishlist.

02 Definition & Development

Solution exploration, wireframes, and possible user flows went through multiple feedback loops and alignment sessions with the Tech and Product teams. Through this iterative process, wireframes were refined. To fast forward progress, high-fidelity mockups were created early, allowing direct iteration. Documentation and user flows were prepared for further refinement and developer handoff. However, the project was postponed due to an extended previous development cycle.

03 Definition, 2nd round

With the project delay, the Product team introduced new requirements and functionality extensions. While the screens remained largely unchanged, workflows needed to be restructured and functionalities expanded. To facilitate alignment and accelerate development, the design was broken into smaller, manageable chunks. Wireframes were iterated until all teams reached agreement.

04 Development & Delivery

High-fidelity designs were developed alongside the ongoing development process. Documentation details were handled through live alignment sessions with developers and design notes. Arising issues were resolved collaboratively with the Tech team through continuous iteration.

Constraints

This project was particularly large and complex, requiring multiple redesigns due to shifting requirements, with the latest iteration spanning several development cycles. The scale of the project posed challenges not only from a technical perspective but also in terms of product and design alignment. Ensuring that all stakeholders remained on the same page required numerous alignment sessions, which proved to be a significant challenge. To streamline discussions and maintain focus, it was decided to tackle one part of the user flow at a time.

Iteration

Future iterations could focus on enhancing historical data comparison, enabling users to analyze trends over multiple years. Data versioning is another potential key improvement, as users currently need to upload and map a new data file each year without the ability to build on existing sources while maintaining change tracking. Additionally, market specific mapping might allow users to save and reuse mapping templates per market for greater flexibility.