Making Space for Bold Ideas

Aligning change at CDC will ensure modernization is executed well

woman climbing an outdoor rock wall with sky and mountains in the background

With DMI, we’re taking a team approach designed to help enhance collaboration within CDC, encourage adaptability, and create a space where bold ideas and creativity can thrive to meet the modernization challenge.

“It has been enlightening to have conversations with others who I would not normally interact with – to know that we aren’t alone in the data and system problems we’re facing, and then to work together to find the common ground.”
– Lyndsay Bottichio, Priority Team Co-Lead, August 2022

In 2022, we stood up cross-agency Implementation Teams to work together on specific DMI priorities and objectives. This means that staff who work at many different jobs on all different diseases and conditions are now in one place, sharing their unique perspectives and coming up with common solutions. These diverse teams are helping to unlock the answers to large public health challenges.

In January 2022, a session was held to begin developing the next phase of Objectives and Key Results, or OKRs, for data modernization at CDC. OKRs are a collaborative goal-setting model used by organizations to achieve challenging, ambitious goals. The teams also identified 15 essential activities to prioritize the work and resources to achieve DMI goals.

Teams then began working collaboratively to review objectives, update key results, and start activities for the next phase of DMI. As DMI embarks on this next phase, teams are transitioning from planning to actively learning, piloting, and testing so that we can modernize effectively together.

By the numbers

10
Priority Teams aligned to 5 DMI priorities


15
Essential activities identified


200+
CDC staff actively engaged

Did you know?

Over time, much of the work public health does has become separated, or “siloed,” because programs are usually funded and set up to address only a single disease or condition. An important job for data modernization is to take the disconnected data streams and areas of expertise and bring them together — what we call “breaking down silos.”