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Data-informed decision making to drive improvement
By Katie Murray / August 25, 2017 /   Loading Disqus...

This is the second in a series of occasional blog posts on the topic of evaluation. See the earlier post: Evaluation: It's about improvement, learning with others.

“Data-informed decision making” is a term used widely these days by organizations of all types – for-profit businesses, government agencies, nonprofit entities, funders. At the Rhode Island Foundation we have the privilege of learning from and with many organizations that use data to guide their decisions and increase their impact. We also see the tremendous variation in the sources, methods, and application of data. 

Over the next several months, we will share what we are learning by highlighting the work of community partners and the many different ways that data inform and improve their services. We will include organizations that work across our core issue areas – arts and culture, children and families, economic security, educational success, environment, healthy lives, and housing – to illustrate the commonalities and differences by sector. We also will describe data activities that are performed by staff and those requiring in-depth research and analysis by external evaluators. In all examples we will highlight both quantitative and qualitative sources. 

Before diving into the details of particular organizations and programs, we want to first highlight the kinds of data sources that organizations use in their evaluation and improvement efforts.

Administrative datasets

Many organizations take advantage of existing forms and processes to collect data that can serve evaluation and learning purposes. This is advantageous since the data exist without the need for additional resources or staffing for collection. Some organizations have found that simple changes to a routine form can transform it into a useful data collection tool.

In-person or electronic surveys

Surveys are used by organizations of all sizes and focus areas, usually administered in writing or electronically. A great advantage of surveys is the cost in relation to the amount of data an organization can gather. Important considerations in surveying include the literacy and language needs of respondents, and ensuring sufficient response rates.

Formal screening and assessment data

In some of our core sectors, such as education and health, organizations routinely collect data as part of their services and as required by federal and state programs or regulations. In these settings, such as public schools where assessment data are collected annually across subject areas and grade levels, data can serve as points for intervention, for gauging progress, and describing impact. 

Secondary data

Many organizations reference and/or analyze secondary datasets that are collected elsewhere and made available through a public interface or special data sharing agreements. Federal and state agencies are a key source for secondary data. Organizations often use the data as indicators of progress or persistent challenges and as benchmarks for targeted activities.  

Focus groups 

Focus groups are commonly used to obtain detailed feedback from beneficiaries, key partners, or other stakeholders about needs and concerns. Successful focus groups generate rich information through the conversation among a small group of participants, and help in program creation, adjustment, or expansion.


Interviews offer the opportunity to explore questions more deeply with an individual than a written survey or a focus group. Like surveys, they use a standardized instrument but are conducted by a data collector in person or by phone. 


While utilized less frequently, observations capture information about behaviors, interactions, or physical site conditions. Observations use trained data collector-observers who adhere to formal guidance on whom or what to observe, when, and for how long.  When done well, observation is considered a strong method because of its ability to generate firsthand, unbiased information.

Iterative design process

Finally, design thinking is emerging as a process relevant to evaluation because of its emphasis on rapid feedback loops to improve user experiences and identify critical needs. While not common as an evaluation practice, design thinking is gaining momentum in program design and improvement. As such, its use offers valid lessons that are similar to more typical evaluation and data collection methods. 

We hope you will find the blog posts relevant to your work and interests. In the meantime, does your organization have a preferred method or source? Please add your comments below. 

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