Data. Big data, aggregated data, personal data, traffic data, analytics, statistics – we hear about it all the time. As aware as we are of the great potential of data, and the need to use it more and better, the question remains – how can we harness it for our advocacy work?

Eva Bille
Consultant

The power of data is obvious – the more we have, the more informed our decisions can be. But when does it become too much? How can we prevent data overload in this information-centric data-driven society? There is no perfect, and certainly no “one-size-fits-all” solution.

Data is everything

Where can we use data? The short answer is: Everywhere. Data can be used to inform strategy, generate content and measure results. Data shows value, spots trends, backs up arguments, measures impact, and tracks progress. Measurable Key Performance Indicators (KPIs) are excellent to show value and progress. Very few things show the true cost of a policy decision as well as a well-constructed impact analysis. Quantified trend reports, of media mentions for example, can give a quick overview of how a specific issue or organization is being portrayed and how tone of coverage and share of voice are evolving over time.

Data collection can be anything from quantitative and qualitative content analysis to surveys and focus groups, as well as more complex online sentiment measurement techniques.

Data can enrich and provide evidence for almost everything – but that doesn’t mean it’s always a good idea to collect it.

Purpose is king

Before collecting data, it is paramount to have a clear objective in mind. Data-collection can be very time and resource intensive, and it is easy to get caught up in repetitive and tedious data-collection routines. Data is pointless if we don’t know what we are going to do with it. For personal data, there is are even more grounds for having a solid purpose after 25 May when we enter the age of the new GDPR regulation. As with everything, a good data project starts with asking the right question – and it is a good idea to reassess data collection and analysis continuously, to see if they still respond to their purpose.

Don’t “collect and run”

Don’t do your data the disservice of not communicating about it properly. Transparency is key – especially regarding your data gathering methodology and potential gaps. Being honest about any existing shortcomings makes the output less vulnerable to attack. You can even go as far as to making the raw data available for further scrutiny for those interested.

Don’t expect people to dig in and understand the complexities of the data immediately –communicate about the data and make it “shine”. Design and visualization techniques are your allies when it comes to presenting data in a crisp and attractive way.

Data can enhance, engage and explain, but it can also confuse, contradict or convolute. Use data, but use it well!