Staff want to engage with data-driven decision making, but they don’t always have the time or space to do so.
When organizational leaders make decision-making processes transparent and collaborative, it supports staff, even if they can’t act on every idea right away.
This week, we’ll take a more hands-on approach. I’ll walk you through an activity you can use with your team to turn raw data into clear, actionable insights: The Data-Driven Decision Tree.
The Data-Driven Decision Tree is one of two activities taken from “Prioritize This: Data-Driven Decision Making“, a free resource provided to my newsletter subscribers. This activity helps break down program and service evaluation data into actionable steps based on feasibility and impact.
Objective:
Help your team turn data into clear, actionable next steps by exploring feasibility, mission alignment, and participant impact.
This activity is ideal for:
- Staff who design and implement programs
- Leadership responsible for strategic decisions
- Any staff who collect, analyze, or share participant feedback
What you’ll need:
- A copy of the Data-Driven Decision Tree. (Sign up for my newsletter to access the full exercise (including the decision tree visual) from Prioritize This: Data-Driven Decision Making.)
- Program or evaluation data you want to analyze
- A notetaker or facilitator to guide discussion
- Time allotted: 30–45 minutes, depending on group size and number of data points
The steps:
Step 1: Understand your data
Take one data point and review it together. What trends or patterns do you see? Are there recurring themes or outliers? Encourage each staff member to share their perspective based on their role.
Step 2: Assess feasibility
Ask: Is this change within our program’s scope or mission? Do we have the resources, budget, staff, and time to address it? Capture the idea for future review instead of discarding it outright if the answer is no.
Step 3: Identify impact
Ask: How many participants would benefit from this change? Does it address an immediate need or contribute to a long-term goal? This helps surface the changes that matter most to your participants.
Step 4: Decide next steps
Use the responses from feasibility and impact to sort the data point:
- Quick Win: Feasible now and high impact.
- Long-Term Goal: High impact, yet currently not feasible.
- Secondary Priority: Low impact, but still feasible.
- Not a Priority: Neither feasible or impactful right now.
Let’s process
This data sense making activity helps staff determine whether a potential change is feasible and aligned with program goals. As you walk each data point, encourage staff to share their observations and interpretations, from their role’s perspective.
Once you’ve identified potential changes, discuss their feasibility by evaluating the program’s available resources. Explore realistic options, and guide staff to focus on changes that can be effectively implemented within current constraints.
Encourage staff to share their interpretations openly, explore realistic options, and focus on improvements that align with your mission and vision. Even disagreements or feelings of overwhelm are opportunities for reflection and collaboration as they can surface blind spots and help staff strengthen its evaluative muscles.
Key takeaway
The Data-Driven Decision Tree isn’t just about sorting ideas—it’s about creating a structured, transparent process for making tough choices together. Using this activity helps staff see their role in moving from data collection to meaningful action, even in an environment where time and capacity are limited.
Raise Your Voice: How can you use this activity to make data-driven decisions? Share your experience in the comments section below.
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