If you are a Head Start program manager or director, you’ve heard about continuous quality improvement (CQI) under various names over the years. You’ve been told to do it. ECLKC is full of reports on its importance. If you are a program manager or director you have probably attended panel sessions, training programs, and seminars on it. You might have even included one of the diagrams from the ECLKC reports in your annual performance review materials.
You have learned to speak the mantra of data-driven, evidence-based CQI.
But do you actually do it? Really do it?
The study “Understanding Data Use for Continuous Improvement in Head Start” (OPRE Report #2015-33) suggests that you don’t. The report reviews the implementation of CQI in a number of fields and surveys the state of CQI in the Head Start community. The report concludes that the Head Start community is faced with four major challenges:
- Lack of human capacity
- Organizational and institutional obstacles
- Head Start tools are not designed to support CQI
- Lack of demonstrated link between existing CQI efforts and actual outcomes
The first three deal with structure and tools. Human capacity is the combination of skills and time required to implement CQI. Few people have strong data analytics skills and those that do often lack the time to tackle significant data issues while doing their other jobs.
The fourth focuses on the links between CQI and practice. To address the fourth challenge requires addressing the first three. To demonstrate something, you have to be doing it and measuring it well.
There is not going to be a magic solution to these challenges that works the same way for every grantee and delegate. The problem requires adaptation in multiple areas. It also requires rapid action to address these challenges with the advent of new performance standards with much stricter requirements for the use of data analysis.
One method for addressing these issues is to look outside the organization for help from specialists. A data science partner can help to address some of these challenges.
Firms like Acorn Evaluation provide specialist services that help with data analytics expertise, management consulting, and data integration experience. These address the first three of the challenges of implementing real CQI. A data science partner with skills in program evaluation can address the fourth challenge through working with you to demonstrate outcomes on a solid foundation of high quality, accurate data.
In the tight budgetary environment, the selection of an outside data science partner can help Head Start organizations meet the challenges of the new performance standards without the need to hire significant additional staff members or reassign existing staff with specialized expertise.
Real data-driven CQI, grounded in best practices and adapted to local grantee and delegate conditions is easier with a partner to carry some of the workload with you.