Data, Program Measurement, and Research OKR:
Continue development of a data dashboard to provide the community with a snapshot of ongoing digital equity work in Mecklenburg County.
From the early stages, the CDE has tried to anticipate what the community will need to ensure our collective success. Thus, it was apparent to the CDE data pilot team that sharing accurate and timely data would be of paramount importance in identifying priorities and advancing policies. Because the State does have a central repository of digital equity research and resources (see our collaboration with the State in the 2024 midyear report), the CDE felt that it could supplement the State’s efforts by continuing to work on its own data dashboard and library of resources.
The backbone of the data dashboard is a shared data governance model across all workstreams, and included data collected from many and various different partner organizations. This, along with a robust resource library, can give a more complete picture of the current state of digital equity and the impact that the ecosystem’s activities have over time.
This has been a challenging project, with multiple layers of complexity including data governance, research libraries, and methodologies to vet the data. We knew that we would not be able to measure our strengths or gaps without collecting the data from multiple partners, so we brought in three to pilot, build, and assess the integrity of the system. This included work on data visualization, data integrity, and much more.
The one big red flag we saw here was data accuracy. As resources were brought together and the data dashboard tested, it became apparent that something was off. Numbers reported were inconsistent, and this was apparent with even a casual glance. This prompted the team to really dig back into the CDEs systems to see what was reported, how, and when.
The simple question, “Why are we reporting this bit of data this way instead of that way?” can be a powerful one. We thus saw the need for a data dictionary. More than just a set of definitions, the data dictionary sets a standard procedure for collecting and reporting data in a systematic way. Such a dictionary provides much needed scaffolding for populating the data dashboard and identifying gaps in data collection. Only then would the dashboard results be a comparison of apples to apples, as the saying goes.
With this done and with the data formatted correctly—and together with consistent data collection from partner organizations—the data dashboard is well on its way to reporting accurate data and trends.
Now, with the maturation of the dashboard, the data will begin to tell a story of patterns and opportunities. As we continue to add new partners this year, we will begin sorting the data into literacy outcomes for the community and adding compelling state and national data as comparative resources.
