Data without tears: Building a Data Strategy that serves your mission

For many not-for-profit organisations, the phrase “data strategy” sounds intimidating. It conjures images of endless spreadsheets, IT consultants, or expensive systems that only big corporations can afford. But at its heart, a data strategy is simply about being intentional: knowing what information you need, how you’ll collect it, and how you’ll use it to serve your mission. 

Too often, data ends up scattered. One staff member has a spreadsheet of attendance, another has a notebook of feedback, and someone else has survey results tucked away in their email. Each piece might be useful, but when they’re disconnected, they don’t add up to a clear picture. The result? Missed opportunities, duplicated effort, and frustration when reporting time rolls around. 

A simple data strategy can prevent all of that. It doesn’t have to be complicated, and it doesn’t have to cost a fortune. It’s about creating a shared understanding of what information matters, making sure it’s collected consistently, and using it to guide decisions. 

Why a data strategy matters

At its most basic, a data strategy helps you avoid drowning in information you don’t need while making sure you don’t miss the evidence that really matters. 

Without a strategy, it’s easy to fall into one of two traps.  

The first is collecting too much: endless forms, duplicated surveys, or mountains of numbers that nobody has time to analyse. The second is collecting too little: realising at the end of the year that you don’t have enough information to show your outcomes convincingly. 

A strategy keeps you balanced. It clarifies what’s worth gathering, and why. It also builds confidence - in your team, your board, and your funders - that you know what you’re doing with the information entrusted to you. 

Starting small: the basics of a strategy 

So, what does a data strategy actually look like? It doesn’t need to be a 40-page document full of diagrams. For many organisations, it can be a one or two-page plan that answers three simple questions: 

1. What do we need to know? This comes straight from your mission. If your aim is to reduce isolation among older people, then you’ll want to know whether participants feel more connected, not just how many turned up. 
2. How will we collect it? Decide on the methods that work for your context. That could be a simple attendance sheet, short post-session surveys, or occasional interviews. The key is to be realistic about what staff and participants can manage. 
3. How will we use it? 
   Data is pointless if it just sits in a folder. Think about how it will feed into reports, funding applications, or internal reviews. If you know you’ll need stories as well as numbers, plan for both from the start. 

By answering these questions, you create a roadmap that stops data from being random and turns it into a resource. 

Making it part of the culture 

One of the biggest mistakes is treating data as something only one person is responsible for - usually a staff member who ends up buried in spreadsheets. When that person leaves, knowledge disappears with them. 

A stronger approach is to build a culture where data is everyone’s business. That doesn’t mean everyone needs to be an analyst. But it does mean that staff and volunteers understand why information is being collected, how it helps the organisation, and how they can contribute. 

For example, facilitators might jot down observations after each session, not because they love paperwork, but because they know those notes will feed into stories that show outcomes. Program coordinators might check attendance sheets carefully, because they know those numbers matter for funding renewals. When everyone sees the bigger picture, data collection becomes purposeful, not a chore. 

Tools and systems that work 

There’s no one-size-fits-all system.  

For small organisations, a shared spreadsheet might be enough - as long as it’s consistent and backed up. For others, a database or customer relationship management (CRM) system may make sense, especially if you have large numbers of participants. 

The important thing is that the tool fits your needs and capacity. A sophisticated system that nobody understands will be less effective than a simple spreadsheet that everyone uses. What matters most is clarity: everyone should know where to put information, how it’s stored, and how to find it later. 

Data quality: keeping it clean 

A data strategy is only as good as the data itself. If relevant names are misspelled, dates are missing, or surveys are inconsistent, the picture will be fuzzy. Cleaning up data may not be everyone’s idea of fun, but it saves headaches later. 

Build small habits into your routine: double-check entries, set standard formats for dates and names, and avoid keeping duplicate versions of the same file. Even little things, like agreeing to always record “January” as “Jan” or “01,” can make a surprising difference when you’re trying to pull reports. 

Learning from the data 

The ultimate point of a data strategy isn’t to fill reports. It’s to help you learn. If you’re only ever collecting information to tick boxes for funders, you’re missing out on the immense value it can bring to your own organisation. 

Data can highlight patterns you didn’t expect. Maybe attendance is higher on certain days of the week. Maybe certain types of workshops consistently draw more repeat participants. Maybe people are dropping off after three sessions - why? Each of these questions can spark improvements. 

When you see data as a mirror for your work, rather than just a burden, it becomes something you want to use. 

Keeping it achievable 

It’s worth repeating: a data strategy doesn’t have to be complicated. In fact, the more complicated it is, the less likely it will be used. The best strategies are grounded in practicality, shaped by your organisation’s size, goals, and capacity to deliver. Start with what you can manage, test it, and build gradually. 

If you overreach - that is, you attempt to collect every possible piece of information - you risk exhausting staff and participants. Better to do a few things consistently and well than to attempt too much and end up with gaps. 

Final thoughts 

Data has a reputation for being impersonal or intimidating, but when handled with care, it’s simply another way of telling the story of your work. A good data strategy doesn’t replace stories or relationships - it supports them, giving you reliable evidence that complements lived experience. 

When you strip away the jargon, a data strategy is just a plan for paying attention. It’s about noticing the things that matter, keeping track of them carefully, and using them to learn and improve. And when you do that, data stops being a burden and becomes an ally - helping you show the difference and impact you make in your community.