The four big reasons why charity data strategy fails

Are you in danger of hitting a brick wall with your charity data strategy? We take a look at some of the possible reasons why, and what charities can do it fix it.

Chloe Green | 22nd Nov 19
charity data strategy fail

Charities who are great at data wizardry nearly always have a solid data strategy underlying their efforts. Our recent article ‘Why your charity needs a data strategy and how to get started‘ gives charities an idea of the processes and policies that will give them grounding for their data strategy.

But even if you’ve got a strategic framework in place, it doesn’t guarantee you’ll be successful in your data use straight away. IT analyst Gartner estimates that as many as 50% of all data analytics projects fail to meet their goals. The reality is that data is a journey that requires preparation and continuous work, and any one of the roadblocks below could have charities’ efforts to become ‘data-driven’ met with frustration.

Here are the top reasons why data strategies often fall short of their aims:


You aren’t asking the right questions

As Ross McCulloch, Director at Third Sector Lab explains, many charities start off on the wrong foot by not having a clear enough idea of the problem they’re trying to solve. Prescribing a solution before having a well-defined problem in place is a common mistake, and means you often end up without a meaningful direction.

Forget about data for a minute and spend some time trying to define the top three practical questions you want to answer. High-level questions might be:

  1. Are our services effectively reaching all sectors of the community and the people who need them?
  2. Are we having better outcomes with Group A over Group B?
  3. Is this programme the best use of our money, or should we be focusing on something else?


Your data is siloed

Do you have barriers to remove when it comes to the flow of information in your organisation? Data that is stuck in separate systems or departments that don’t communicate with one another is not much use to anyone.

If you bring in a new data source or system, the first thing to check is whether it will be compatible with the data you already plan on using. Ideally, you should have one centralised management system in place, and have policies in place for data formats and collection processes that are unified across all departments – more advice here.


Data is bad quality

So the data you’ve collected or have access to is not consistent, there are bits missing, or it’s just a mess. This can prove to be the death of many good intentions with data.

There’s no getting around it – you will need to plan a good chunk of time to getting your data into a good state before it’s useful. Be prepared that this may be a tedious and lengthy task. Identify the gaps and take some time to clean up your database, before making sure that any future data you use sticks to the same rules and policies.


You lack the skills

Don’t be afraid to ask for outside help. There is lots of it out there specifically for third sector organisations – like DataKind UK and Data Orchard who help charities use data science and provide expertise.

Their Data Maturity Framework is a good place to start in understanding what stage you are at on the journey and what support you might need.

The accompanying Data Evolution report also includes the findings from a study of hundreds of charities and social enterprises on data maturity so you can benchmark yourself against others.

We’ve also listed some of the best data resources for charities including places to access training and specialist support.