background
Pulsely specialises in providing actionable insights to enhance business performance through Diversity, Equity, and Inclusion (DEI) initiatives. They help organisations understand their workforce demographics and inclusion mindsets, offering data-backed strategies to identify gaps and areas for improvement in DEI initiatives. This enables businesses to create impactful programs that foster a more inclusive environment.
The problem
general Survey Platform
Pulsely deploys confidential organisational surveys through SurveyMonkey to assess inclusion gaps and their business impacts, with data analysed by their science team. Although the SurveyMonkey platform is effective for general surveys, it lacks specialised DEI diagnostic capabilities such as advanced equity analytics, inclusion indices, and longitudinal progress tracking.
Time-Consuming Process
One significant limitation is the extended timeline, which spans several weeks or months from survey design to final analysis, resulting in the delay of actionable insights and strategic adjustments. This bottleneck undermines organisations’ ability to implement timely interventions, particularly when monitoring incremental DEI improvements against performance benchmarks.
The Challenge
Admin first
This project will be divided into 2 phases. The initial phase will focus on crafting Pulsely's SaaS DEI platform architecture strategy from the admin perspective, addressing the limitations of SurveyMonkey's generic infrastructure. Specifically, it will tackle the absence of integrated frameworks for analysing DEI metrics and specific data related to the client, as well as the lack of mechanisms for continuous progress tracking.
Reduce process timeline
Anticipates an 50% reduction in manual data reconciliation, accelerating the report processes and reducing the time spent on manual matching, insights and corrections.
Research & Discovery
Data Collection Methods
In order to simplify the arduous and time-consuming aspects of report preparation. It was essential to conduct a thorough examination of the data collection procedures in collaboration with the science team. In particular, identifying distinct characteristics and variations between each product and their respective scientific frameworks.
Automatisation process
Understand the structure in which the science and delivery team navigate through the end-to-end process timeline; (Survey design → Collection → Analysis → Reporting).
To implement the best practices by respecting the same methodology within the product, to ensure the accuracy and relevance of the final reports.
Design & Development
As part of this process, I performed a competitive analysis to identify strengths, weaknesses, and opportunities for innovation. Additionally, I analysed and determined the most effective data visualisations to apply in specific analyses, improving user understanding and clarity.
The creation of detailed user personas to represent the target audience was obsolete in this particular phase, considering the admin part of this software will only be available for Pulsely internal use.
To better understand the product goals, I compiled insights from stakeholder interviews and aligned them with the methodologies shared by the science team. A basic information architecture and sitemap were created to clarify the content and from here, I began building low-fidelity wireframes for validation and approval with the stakeholders.
Testing & Refinement
Although, this first stage of the project is intended for a particular group of individuals at Pulsely organisation. I conducted a series of usability tests directly with the science team to pinpoint issues and user journeys that require improvements due to friction or lack of understanding of the flows.
Conclusion
Handover
My task in this project concluded at this juncture, just before the beginning of the second phase. In preparation for the handover, I meticulously documented the findings from the internal usability tests and communicated them to the relevant stakeholders. This included identified issues, potential solutions, and recommendations for the next steps. Additionally, I facilitated a documented design system and a series of Figma prototypes in order to ensure a seamless transition and provide clarity on the refined user flows for those who will continue the project.
What I learned
Certainly, I gained a significant amount of knowledge regarding DEI and its potential impact on motivations within an institution, as well as the ease with which knowledge and information can be promoted throughout the organisation.
The complexity of these reports is staggering. The structure is well-defined by the science team and there's no room to change it or the results might be compromised. As an UX designer, it may not make sense, but it definitely makes sense to them, and we have to align our way of thinking to meet their structures. Otherwise, the final goal can be compromised.