By Emma Prest of DataKind UK and Lauren Bernard of NCVO
This post originally appeared on on the KnowHow Nonprofit blog.
Most of us agree that data is important in any organisation. We need to collect and analyse data to estimate the demand for our services, understand who our users are, find out which services are working for which people, and much more. In fact, there are few areas of work where the smarter use of data doesn’t make us more effective. And the future holds out even more opportunity - the ability to predict need and effectiveness, and to use data to design and innovate new services. But first you need to know where you stand at the moment, and how to move forward in a way that suits your organisation and its existing capabilities.
Research into data maturity shows that there are seven key areas that you need to consider when improving your organisation’s use of data. And perhaps unsurprisingly, the most important are people and culture! This guide looks at those key areas, and suggests the signs that you should look out for to determine if you are on the right track.
The attitude of leadership is one of the most essential ingredients to becoming data driven. If your leadership team sees data as a vital resource and is able to incorporate past, present and forward-looking data into business planning and decision making, then you’re on the right path. If the leadership team tends to make decisions based on individual experience, anecdote or gut feeling, then there’s work to do!
A willingness to invest in increasing the organisation’s capacity to work with data is a first step. In order to do this, a charity will need a broad range of people with data expertise and understanding, from admin roles through to board level.
Becoming more data driven is ultimately about changing a culture and inspiring your colleagues to be interested in data. In our research some respondents saw data as the responsibility of ‘someone else’, whereas in more data savvy organisations data was seen as a team effort and a critical asset for every part of the organisation.
An organisation that is hungry for feedback and strives for continuous improvement is more likely to embrace data. A subtle pointer is the way that questions about data are asked. If staff ask (positive!) questions that challenge practices and preconceived notions, as opposed to just looking for data to support and confirm existing beliefs, then you are culturally well placed to become more data driven.
Being able to share data and results across the organisation is another essential element. But be aware that both internal and external data sharing requires strong data protection and security practices. There must be regular training, and trustees and senior management should be aware of current legislation and best practice.
To collect and manipulate data you need the right skills in house (or at the other end of an email). Not only do you need staff who can conduct the right analysis, but your colleagues need a certain level of data literacy to understand the results produced.
In organisations that are more data mature there is often a dedicated person or team in charge of data, with skilled data people across other teams and departments. With the right in-house data chops you become the experts in your sector that other organisations turn to and use as a resource, building your credibility and influence.
Ensuring you have the right tools is hard. Software requires updating; technology changes and better products come on the market; migrating databases and training staff in a new tool is always a headache. And yet, analytical infrastructure is a priority if you want to do more with data. Ongoing investment in tools, systems and infrastructure is key.
Charities that regularly and easily join up different data sets or store data in a singly accessible database are ahead of the pack.
Some organisations even make data accessible to all staff enabling them to explore the data themselves (this also means they no longer rely on the data guy or gal to run reports for them). Dashboards are a common way of democratizing data.
The starting point here is to know what data you hold across the charity. Once you’ve done a data audit and have a data inventory, it is worth reviewing how meaningful, relevant and useful that data is. Do you really need all of it? What are you missing?
Understanding the quality of your data sets and what kind of analysis can (and cannot) be done comes next. Charities that are more data mature monitor their data to check it is complete, accurate and valid. They have tools and systems for cleaning and maintaining it. They are able to join the data up to conduct analysis across teams. Their staff and volunteers are trained in data collection and understand why it matters. Where possible, data collection is automated.
Charities increasingly compare their data with other organisations’ data to benchmark their performance and they look to open data to enrich their internal data sources.
Common uses of data in the voluntary sector include measuring outcomes and impact; monitoring the success of campaigns; reporting on staff and volunteer performance; demonstrating the need for your work; making the case to funders for new services/ products/ campaigns; and running financial models and donor retention. Data analysis is also often part of influencing policy makers, and developing robust evidence to build credibility and influence.
Less commonly, charities run analyses to understand how to make services more efficient; differentiating between approaches - what’s working and what’s not; testing assumptions and understanding client behaviours; analysing user groups to better understand their needs; targeting and optimising services/ products/ campaigns to suit those needs. As a sector we are moving towards a world where charities can predict needs, behaviour and outcomes, maximise income and provide more targeted solutions.
Charities tend to run quarterly reports, which often involves trend analysis of activities and finances. But increasingly charities are not just looking backwards. They are forecasting and predicting to plan for the future.
Some charities use advanced analytics such as clustering, root cause analysis, A/B testing, network analysis or text analytics. Data is brought together in automated ways to provide organisation wide analyses.
Moreover these charities don’t just run analyses every few months. They are able to do it in near real time. They also think about how best to communicate findings to different audiences, whether through simple reports or whizzy data visualisations.
Like acquiring any new skill, using data better involves phases of progression, starting with the building blocks and moving up to more advanced stages. If you would like to take your organisation on a data journey check out the Data Maturity Model produced by DataKind UK and Data Orchard showing the seven key themes for being data driven, across five stages of maturity.