Some scribbles on a piece of paper, that look like a map of different types of data. There is a green logo in the bottom left corner and the words 'The Data Place'

7 techniques, 6 questions and 5 resources to help you improve your charity’s data quality. So you can make better decisions.

Humans have three ways of making decisions.

Body-based - when you make a decision without even thinking. Your body’s system has already made a decision for you. Whether you want to or not.

Feeling-based - when you make a choice based on how it feels, perhaps your gut. It's hard to explain why you’re making that decision, but on some level it feels right. Intuition.

Data-based - when you make a choice based on a logical analysis of information. Your mind is guiding your thinking. Data is driving your decision.

What does this mean for charities?

Better data means better decisions

You will be using all these ways to make decisions at your charity. But while experience and personal development will help you with the first two, only better data will help you with the third. 

The better your data, the better your decisions are likely to be. 

In 2021, The Data Place delivered three data workshops for charities. This article summarises two sessions:

  • Ensuring your data is good quality
  • Using your data well

The third is a GDPR training session that will help you manage data in your charity in a compliant way.

“Data goes to the heart of your organisation and touches every single aspect of it on the way.” - Lucy Knight, Data Lead, The Data Place

6 questions about your data 

Ask yourself these questions. They will help you think about whether you are collecting the right data, enough of it, and why you are collecting it.

  1. What data are you collecting and why? 
  2. Is your data collection sufficient to generate insights and inform your decision-making? 
  3. How easy is it to produce a report on what you need to know from the data? 
  4. Do you need more detailed data? 
  5. Do you have the capacity to take on and migrate to a new data system if needed? 
  6. Does your means of collecting and using data meet your organisational needs or will you end up creating workarounds?

7 tips on using data

Your data needs to be accurate, complete and legible in order to be useful.

It needs to be clean and easy to store. 

It needs to be structured and ready to use. 

Here’s 7 tips on how to do this.

1. Know what insight you need to get out of your data. 

There are many ways you can use your data. For example:

  • To understand the needs of your service users
  • To inform your service marketing so as to improve service take-up
  • To analyse your financial performance or staffing requirements
  • To build a case for more funding by evidencing the change you’ve made on people’s lives

When you know what insights you want, it's easier to decide what data you need to plan for. Think about what type of reports and charts you will want to produce. Then work backwards until you have a list of the right data.

2. Spend more time working out the right data than creating nice systems. 

80% of any data project is finding the data, cleaning it and shaping it for your needs. Spend more time on solving this than bringing in a newer, faster (and possibly more costly) system. 

3. Create reference lists for entering accurate data terms

When inputting data, you often need to enter the same input multiple times. However if the terms used for that input are inconsistent with one another (e.g. Y, Yes, and yes) then you’ll end up with errors in your data and reports. Manage this by creating a reference list. Then use this list to select data via a dropdown option for that data field. This will help you avoid errors. 

4. Standardise your data

One of the most common input errors is incorrect geographical addresses. But it doesn’t need to be. You can use an address validation service that uses data from postal authorities. They are a simple and free addition to online forms. You simply enter the postcode and choose from the addresses it displays. This ensures standard input and again mitigates errors.

5. Use charts or pivot tables to check data quality

Charts and pivot tables help you cross check if a data table shows the insights you want. They can also reveal data problems. For example, they may flag up that you have fewer volunteers in a database than you expected. They will also show if cells have been omitted, have incorrect data or if data hasn’t pulled through correctly from a signup form.

6. Clean up messy data 

Messy data leads to less informed decisions. Rather than manually editing to clean the data you can use a tool instead. Open Refine is a free, secure open source tool which, with a few clicks, can clean up messy tables and organise your data.

7. Use Open Data sources to fill in gaps and gather more insights

Open Data sources have many advantages. They are free to access, well-maintained, derive from authoritative sources and are recognised by funders. Using them can save you time and money.

5 useful data resources

  1. Using your data slideshow: how to have good quality data, stored in the right formats and collected for the right reasons, so you can get the most out of it. 
  2. Data quality slideshow: see examples of bad quality data, learn techniques needed to overcome these issues. How to make a data action plan.
  3. Office of National Statistics (ONS) for population projections or employment statistics.
  4. Open Corporates - a global business database to look up particular businesses in a region, for example.
  5. Spend Network - a directory of public procurement data to see what governments and public authorities are spending their money on. 

Attribution

This resource is based on content created by The Data Place for the Beyond programme in 2021.


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