Leveraging Data the Goldilocks Way: Part 1 — Measurement That’s Just Right
If you’ve been following along with my Goldilocks series on strategic planning and goal setting, we’ve talked about how to build a process that’s balanced — not overbuilt, not underwhelming, but just right for your size, capacity, and aspirations. Now it’s time for the next step.
Once you’ve set your goals and outlined your plan, how do you make sure it actually teaches you something?
That’s where Measurement, Evaluation, and Learning (MEL) come in. Over the next few posts, we’ll explore each part of that framework:
Measurement — what to track and why
Evaluation — how to interpret what the data is really telling you
Learning — how to turn insights into better decisions and stronger teams
Think of MEL as the nervous system of your goals — the mechanism that helps you sense what’s working, what’s not, and where to adjust. Done well, it keeps your plan alive and adaptable. Done poorly, it just creates noise.
Let’s start with the first piece: measurement.
📏 What to Measure (and Why It Matters)
It is not unusual to see people flinch when they hear the word measurement. They imagine dashboards, spreadsheets, and an endless rabbit hole of data — and they’re not wrong to worry. I’ve seen systems that track everything but progress, and I’ve seen leaders give up on data entirely because it felt like too much.
That’s why the Goldilocks principle applies here too:
Too much data, and it owns you.
Too little, and you’re flying blind.
Just right means tracking what truly helps you make smarter decisions — and letting the rest go. Here is the secret:
Data (and data collection) is neither universally useful nor completely useless - it is useful only when it helps your organization know itself better and empowers your stakeholders make better decisions about what to do next.
🎯 Start With Why
Before you pick what to measure, ask why you’re measuring it — and make sure it ties back to your strategic goals. Your goals identify what matters most. Measurement shows whether your efforts are actually moving you closer. If a metric doesn’t tell you something useful about your progress or impact, it doesn’t belong on your dashboard.
Each indicator should help you answer one or more of these questions:
Are we doing what we said we’d do?
Is it making the difference we hoped?
What are we learning that can make us better next time?
📚 Measure for Insight, Not Inventory
Measurement should not just produce a list of numbers or an impressive-looking dashboard. It should tell a story about whether your efforts are creating the results you set out to achieve.. That story often unfolds in three layers:
Inputs and Effort: what you’re putting in — people, time, and resources
Outputs and Reach: what’s happening — who or what is being reached
Outcomes and Impact: what’s changing — and what specific difference are you actually making.
🔎 Measure What Helps You Decide
Here’s a rule of thumb I use when collecting data: If the data won’t influence a decision, don’t collect it.
If the data you’re collecting doesn’t help you understand progress or spark meaningful decisions, it’s just noise. And worse, it can be demotivating — because when people spend time tracking things that don’t matter, they start to lose faith in the process. Every measure should serve a purpose. Ask yourself:
What decisions will this information inform?
How does it connect to our goals?
Who will use it — and when?
Keep it simple. Most organizations need only a few well-chosen indicators for each goal. If your measures help you see where you’re on track, where you’re not, and what you might adjust, you’ve done enough.
📊 Check the Feasibility: Can You Actually Measure It?
In my experience, this step often gets overlooked because teams are eager to move from planning to action. However, if your team doesn’t have the capacity to collect or analyze the data reliably, it will only create frustration and erode trust in the process. It is always better to have a few credible indicators that connect clearly to your goals than a dozen that no one trusts or uses.
Therefore, always take the time to ask:
Do we already have an accurate and reliable source for this data?
Can we collect it easily and consistently?
Do we have the tools to make sense of it?
Will the right people get this information in time to act on it?
⚖️ Balance Quantitative Data With Qualitative Data
When people have space to make meaning from data, they’re far more likely to see measurement as a tool for learning, not just reporting. Quantitative data shows what’s happening, qualitative data explains why. You need both. A good mix of data presents quantitative evidence as well as stories, reflections, and observations that answer the following:
What’s behind these numbers?
What surprised us?
What changed along the way?
🌱 Sustainable Measurement
Whether your organization is data-rich or resource-limited, one truth holds: there’s only so much time, money, and energy available for tracking.
The key is sustainability.
Data is most useful when it fits your culture, capacity, and rhythms — when it becomes part of how you live your goals, not an administrative burden beside them.
Start small. Build simple systems people can maintain and believe in. Use the data you already have. Look for measures that can do more than one job. And don’t be afraid to stop collecting information that no longer helps you make better decisions.
Sustainable measurement isn’t about perfection — it’s about rhythm. It’s about creating an ongoing, manageable way to learn and adapt without burning people out.
🔄 Coming Next: Evaluation
In the next post, we’ll explore evaluation — how to interpret what your data is really telling you, how bias can creep in, and why clarity about who’s responsible versus who’s accountable can make or break your process. Because as anyone who’s ever worked with data knows — numbers don’t lie, but our assumptions about them often do.