2 Sep, 2026

Ask Nicole: Your Data Is Only as Strong as the Hand-Offs

By Nicole Clark, LMSW|2026-09-02T09:05:55-04:00September 2nd, 2026|Categories: Research & Evaluation|Tags: Ask Nicole, Collaboration, Data Driven|0 Comments

Ask Nicole blog graphic featuring a smiling woman in a yellow top against a purple background, with the text “Your Data Is Only as Strong as the Hand-Offs” and Nicole Clark Consulting branding. — Have a question you’d like to be featured? Let me know.

Organizations encounter data in many forms.

Research findings, program participant feedback, interviews, community stories, website analytics, service records, donor information, observations from frontline staff, and conversations with partners can all help an organization understand what is happening and what deserves its attention.

Because data takes so many forms, no single person or department can hold responsibility for everything an organization learns. Program staff gather information directly from participants. Researchers or evaluators examine patterns and help make sense of the findings. Development staff use that information to answer funder questions or strengthen a funding proposal. Communications staff translate a finding into an infographic, social media post, annual report, or story. Leadership rely on the same information to make decisions about strategy, staffing, partnerships, or resources.

Each person interacts with the data differently, and those differences matter. The strength of your organization’s data practice depends on how well people connect these roles.

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26 Aug, 2026

More Data Doesn’t Lead to Better Decisions

By Nicole Clark, LMSW|2026-08-26T12:16:44-04:00August 26th, 2026|Categories: Research & Evaluation|Tags: Accountability Data, Data Driven, Learning Data, Nonprofits, Philanthropy|0 Comments

A woman with a medium brown skin tone sits at a desk, appearing to be overwhelmed, while reviewing a stack of papers, with the text “More Data Doesn’t Lead to Better Decisions” displayed over the image. — ***Collecting more data does not guarantee better decisions if you can’t explain why it exists or how you plan to use it.***

If your organization stopped collecting a particular data point tomorrow, who would notice, and what decision would become harder to make?

Over time, “we’ve always collected this” starts to function like a justification, even when nobody can explain what decision it informs, or whether anyone would notice if it disappeared. A question can remain on a survey for years. A reporting template still asks the same metrics long after a program’s activities have changed. Staff may spend hours entering information into a database simply because the organization has built a routine around collecting it. Eventually, the process itself can make the data feel necessary.

For staff responsible for overseeing data collection, questioning those routines feels risky. You may inherit reporting systems that existed long before you joined the organization, manage requirements established by funders or leadership, or oversee information that several departments use differently. Still, regularly asking why your organization collects something is important. Data should have an identifiable purpose, whether that purpose involves learning, accountability, decision-making, or some combination of the three.

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19 Aug, 2026

Try This: The Purpose-Meaning-Action Data Framework

By Nicole Clark, LMSW|2026-08-19T12:44:37-04:00August 19th, 2026|Categories: Research & Evaluation|Tags: Accountability Data, Data Driven, Learning Data, Nonprofits, Philanthropy, Try This|0 Comments

On the road to becoming data-driven, collecting useful data starts with understanding why you need it.

Some data helps organizations demonstrate accountability to funders, boards, leadership, participants, and other stakeholders. Other data supports learning by helping staff understand what’s working, where challenges are emerging, and how programs might improve.

Often, the same data can contribute to both purposes. The important part is determine the role the data is playing.

Understanding the purpose of a metric is a first step. Programs staff may need to consider what the information actually means and what conclusions it can reasonably support. Attendance may tell you how many people showed up yet offers limited information about what participants learned or experienced. Likewise, collecting meaningful information has limited value if no one uses it to make decisions.

The Purpose-Meaning-Action Data Framework brings these considerations together so your team can examine whether the data you’re collecting is helping you understand and strengthen your work.

Try this exercise with your staff and let me know if it’s useful for you.

Objective:

This exercise is designed to help teams examine the purpose, meaning, and potential action behind the data they routinely collect.

This Activity Is For:

Nonprofit program, evaluation, communications, development, and leadership staff who collect, review, or use organizational data
Philanthropy staff who develop reporting requirements, review grantee data, or work directly with funded organizations
Data and evaluation staff who want to engage colleagues in conversations about how information supports learning and decision-making

What You’ll Need:

Plan for approximately 50 to 60 minutes for this exercise. If your organization collects a significant amount of data, focus on one program, reporting process, survey, dashboard, or other manageable set of measures rather than trying to review everything at once.

For an in-person session, you’ll need:

A current report, survey, data dashboard, tracking form, or list of metrics your team regularly collects
Sticky notes
Pens or markers
Three sheets of flip-chart paper labeled Purpose, Meaning, and Action
A timer

For a virtual session, you’ll need:

A digital copy of the data collection tool or report you’re reviewing
A shared virtual whiteboard, spreadsheet, or collaborative document
Three sections labeled Purpose, Meaning, and Action
A timer

Before the session begins, select approximately three to five data points for the group to review. Choosing a smaller number allows the team to examine each one closely instead of rushing through a long list.

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12 Aug, 2026

When the Numbers Don’t Tell the Whole Story

By Nicole Clark, LMSW|2026-08-19T11:29:48-04:00August 12th, 2026|Categories: Research & Evaluation|Tags: Accountability Data, Data Driven, Learning Data, Nonprofits, Philanthropy|0 Comments

A woman wearing glasses reviews a document in front of a laptop, with charts in the background and the text “When the Numbers Don't Tell the Whole Story” displayed beside her. — **Your numbers can tell you what happened, but do they tell you whether your program is making a difference?**

Collecting data with a clear purpose is an important first step. Once you know why you’re collecting it, you can now ask: What does this data actually tell us?

Nonprofits collect plenty of information about their work. Staff track participants served, events held, trainings delivered, community members reached, referrals made, resources distributed, and countless other activities. These numbers can provide useful information about what a program is doing and whether it’s reaching the people it intended to reach. However, problems arise when we expect those numbers to tell us something they can’t. A measure of activity isn’t automatically a measure of impact.

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6 Aug, 2026

Ask Nicole: Data for Learning vs. Accountability

By Nicole Clark, LMSW|2026-08-19T11:30:00-04:00August 6th, 2026|Categories: Research & Evaluation|Tags: Accountability Data, Ask Nicole, Data Driven, Learning Data, Nonprofits, Philanthropy|0 Comments

Have a question you’d like to be featured? Let me know.

In 2017, I facilitated a focus group for participants involved in a leadership project. As part of the project, some participants received funding to implement small scaled engagement events in their local communities. One participant hosted an event to engage community members, and while the host anticipated over 100 attendees, the actual number was a quarter of that.

Based on the attendee numbers, the host shared that she didn’t think her event had been very successful because “not many people” attended.

At first glance, that conclusion made sense. We’re socialized to believe that attendance is the most visible measure of success. Fewer attendees could easily feel like a missed opportunity.

But as the conversation continued, a different story emerged.

The participants who attended remained engaged throughout the event. They asked thoughtful questions, contributed to meaningful discussions, and continued interacting after the session ended. What initially looked like a disappointing turnout became evidence of something much more valuable: The event still fostered genuine engagement.

That experience has stayed with me for years because it illustrates an important lesson about data: The numbers we collect don’t always tell the whole story.

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Ask Nicole: Your Data Is Only as Strong as the Hand-Offs

More Data Doesn’t Lead to Better Decisions

If your organization stopped collecting a particular data point tomorrow, who would notice, and what decision would become harder to make?

Try This: The Purpose-Meaning-Action Data Framework

Objective:

This Activity Is For:

What You’ll Need:

When the Numbers Don’t Tell the Whole Story

Ask Nicole: Data for Learning vs. Accountability

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