Throughout this series we have discussed the concept of resilient analytics – the need to build early childhood integrated data systems (ECIDS) that can adapt to and ultimately meet the emerging needs and everyday challenges we see in the field.

At times, creating and managing an early childhood integrated data system (ECIDS) can feel like piloting a ship at sea. As we’ve discussed in previous blogs, project teams need to choose their crew carefully and assign appropriate duties, and they must navigate the uncertain waters of piecemeal funding and shifting state priorities.

You’ve heard it before: “Include stakeholders early and often.” But what if, by doing so, you lose momentum? What happens when those energized early conversations – where everyone is excited over the prospect of a new analytic tool – begin to cool down? How do you pace the engagement, so stakeholders can see growth over time while working for years to bring an integrated data system to fruition?

Effective early childhood integrated data systems (ECIDS) must be designed and managed with purpose. Yet we know, after years of experience, that strong data systems must also be resilient to change. This might seem to be a strange choice of words, as “resilience” isn’t readily thought of as an organizational priority. But as most ECIDS leads and project teams know by now, change is all too often the standard operating condition.

In recent years, America has seen a renaissance in early childhood data use. New tools have been built, new strategies have emerged, more states and stakeholders have realized the potential of a strong early childhood integrated data system (ECIDS). The COVID-19 pandemic, however, has cast that work in a new light. Never before have we seen a clearer need to understand where our children are, how they’re faring at home and in their communities, and what supports they need to grow, thrive, and succeed in the coming years. Never before have we seen such a need for resilient, integrated early childhood data systems that producing useful analytics.