USER EXPERIENCE RESEARCH AND VALIDATION
Data Story Definition
Define themes that connect organizational strategy with metrics and measures to aid in the determination of outcomes and insights.
The Challenge
The project involved working with small cohorts of regional workforce boards to understand their data, systems and processes to find comparisons. We then developed a data storytelling framework and used it to define a set of strategic themes of value across cohorts to query aggregated data and uncover multi-regional outcomes and insights.
Users / Audiences
For the purposes of the project, our cohort partners, the regional workforce boards, were the primary audience. But the data storytelling results were publicly shared on a website.
Scope and Constraints
The project was scheduled to run for 2 years, starting with a very small team and adding team members along the way. We were constrained by data governance agreements, availability of our cohorts, and the challenge of finding comparable data sets across cohorts that could be aggregated.
Organizations
JFFLabs, Brighthive, Google.org (funder)
My Role
UX Design Lead, Product Manger
Date / Duration
Sept 2020 - July 2022
My Process
We conducted discovery sessions with cohort participants.
We surveyed how they collected, managed and and used their data, then conducted a series of interviews to gather additional understanding. I co-led the interview sessions with a BI Analyst.
We proposed a set of metrics.
We identified a unified data set of metrics and measures, then refined and validated them with the cohorts.
We formulated a data story framework.
As a team we created a data story framework to help outline important data story intersections to tell relative and impactful data stories for the workforce boards.
We leveraged the framework and metrics to build a data story grid.
Combining data elements, metric and measures and the data story framework, we identified a set of data stories questions that can be generated with the shared data set to tell impactful stories.
Outcomes and Learning
We found collecting data across organizations was more difficult than we anticipated.
We found large variances in processes and tools among our cohort members. Additionally, only a portion of data they collect could be aggregated.
Collaborating effectively with groups that have varying skill levels can be challenging.
We observed a wide range of proficiency in data literacy and data management, along with a lower-than-expected availability of data tools.
New York Office of Strategic Workforce Development
The newly initiated (2022) New York State Office of Strategic Workforce Development tasked HR&A and JFF to provide guidance with the creation of a strategic development framework including uniform metrics and measures of success.
The Challenge
We were asked to aid the initial formation of the New York State Office of Strategic Workforce Development (OSWD), to set-up the office for long-term success. The HR&A work stream focused on the strategic framework and JFF’s work stream focused on the development of uniform metrics and measures as well as data storytelling guidance.
Users / Audiences
The project stakeholders included OSWD and the Office of the Governor.
Scope and Constraints
My team's portion of the project consisted of developing an initial set of metrics and measures and a plan for their use by the new office. We were constrained by the lack of availability of our stakeholders as well as in-state partnerships that were not yet fully formed.
Organizations
JFF, HR&A
My Role
UX Lead
Date / Duration
Sept 2022 - May 2023
The Process
Create a plan with our partner organization for workstream activity.
The schedule was tight, and we had to balance the work with the availability of the client.
Review the mandate of the new office and the Governor’s strategic goals for the state.
In partnership with a JFF BI analyst, we leveraged the proposed set of metrics and measures to create an initial data story question set that would align OSWD impact measurements with state strategy.
Facilitate a working session.
We walked through our data story generation process with OSWD to help familiarize them with it and the data story question set we created. I conducted an activity to include the OSWD team in the data story generation process by refining and validating the data story questions we proposed and generating new ones.
Conduct a second session to refine our output.
We gave OSWD offline time with the activity board to allow their team time to work with it further. Then we met again to walk through changes and additions to build a data story questions set we could leave with their team.
Outcomes and Learning
What we generated could have been stronger.
Our teams made a planning error. We would have been more successful if our project teams had staggered the work streams to allow OSWD to more fully formulate its strategic perspective before we attempted to leverage it for data storytelling. Additionally, staggered work streams could have resolved the problem of stakeholder availability.
