Turning data into intelligence


Tracey Gyateng argues that a better a use of data by charities helps them improve their operational effectiveness, the service they provide to their
beneficiaries and the outcomes they achieve


BIG OR small, all organisations collect data — whether it’s a simple count of service users or a more detailed database of donors and their attributes. Data is required from funders as part of the reporting process, as well as by the management team and also other stakeholders you’re collaborating with. We are all busy collecting data, but are we all collecting insightful data? That is data which can be used to support and improve the functions of our work. If not, or more likely, if the answer is only partially — then how do we move towards making data more effective?

As a sector, we are all at different stages of using data for intelligence. For some organisations, the focus is on the day-to-day deliverables, with data primarily collected to satisfy funder or internal requirements. At the other end of the spectrum, some will be collecting vast amounts of data — but perhaps do not have the resources to make best use of it, or are collecting superfluous data due as processes are not streamlined or funders request it.

The ideal goal is of course to minimise wastage, but also to collect meaningful data that can be used. It is a tricky balance to achieve — but the opportunities we can gain from collecting the right information and the time that can be saved by only collecting data we use is something we should all be striving towards.

Collecting the right data
Intelligent use of data can significantly increase the effectiveness of charities. Broadly, charities can use data to increase their effectiveness in three ways. First, to improve operational effectiveness in service delivery or support functions such as fundraising. We all know that supermarkets use data collected from loyalty cards to understand our grocery purchases, can the same be said for charities’ donor databases? Are we looking at the characteristics and methods of donating for each donor so that we can communicate with them more efficiently? Are we analysing the data collected from social media?

Some charities have large datasets about their donors which are ripe for data
analysis. How about looking at your data to classify your donors? Through our Money for Good1 work we have developed a free to download tool Know your donors which produces typologies of donors. We are working with a number of charities to help them use the tool to better understand their donors. Another idea could be to map where your donors are in the country to see if there are any opportunities for location specific initiatives.

Not only should we look at how we could expand the use of data, but also cut down on data which is not useful. At NPC we use a timesheet system to track how our time is spent. This can be a challenge to complete when you have to recall and then allocate all the time you’ve spent during the week. The management team recognised that only the records related to specific projects were being analysed and used, and so removed the burden of having to attribute time spent on nonproject work.

This has made timesheet completion easier and faster, as staff no longer have to worry about coding their time spent catching up on admin or conversations with colleagues about tasks — or what they did at the weekend. In all seriousness, demonstrating to staff the need for data collection and how it is valued is vital for engaging them and receiving their continued buy-in, and ensuring that the data collected is used is key and removes wastage and saves time. My ten minute reduction in time sheeting each week reclaims a day of my time over a year.

A second reason to use data more effectively is to understand needs or
issues. A recent study by the Centre for Social Justice highlighted that some
areas are poorly served by voluntary organisations.2 Can we be certain that
the areas we are delivering in are those of highest need?

The answer is yes, if we have undertaken a needs assessment. For example, a charity working to support disadvantaged adults could make use of The Centre for Economic and Social Inclusion (CESI) Social Justice Toolkit3 which pulls together indicators at a local authority level and enables benchmarking. And CESI are not alone in creating tools to support needs assessment — Shelter’s Housing Bank4 and Joseph Rowntree Foundation’s data store5 are other useful tools which use open data to help organisations understand need in different areas. The third reason to collect the right data is to improve understanding of results and impact. It’s relatively easy to measure the outputs of a service — how many people were seen, how many courses were conducted — but the real challenge lies in assessing the difference your service make to your beneficiaries. This requires tracking individuals post-intervention, which can be costly and complex.

As a result, many charities only collect data immediately after an intervention and are then reliant on anecdotes for indications of longer-term impact. Often the data needed to measure long-term impact is held by the government — for example, if your intervention aims to support people to self manage a health condition, one outcome could be a reduction in their frequency of A&E visits. Data held by local hospitals and the Health and Social Care Information Centre could help you measure that. To access this and other types of data, you will often need to have collected the consent of your service users first. However there can be tension in gaining consent, especially when working with vulnerable individuals who may be wary of documentation and form filling.

Overcoming barriers
It’s clear that the right data can bring important insights both for the operations of your charity and to help the beneficiaries of your service. It’s one of the reasons why many organisations, including NPC, are excited about the open data and big data agenda. Increasing the supply of data is certainly important to support the effective use of data. The NPC Data Labs project supports charities to get access to government administrative data to measure the impact of interventions.

The Ministry of Justice’s Justice Data Lab was an outcome of this work and means that charities now have a clear process for measuring reoffending rates of their service users compared to a matched comparison group, a vast improvement to the opaque and incoherent process which stood before. We are currently working to expand this project to enable access to data to support impact measurement within employment, substance misuse and health service delivery.

But increasing the supply of data alone won’t automatically lead to an increased use of the data. Firstly charities need to be made aware of the datasets that are relevant to their work and publicly available, or that could be requested, and how to access them. Speaking with academia, infrastructure organisations such as NCVO and working collaboratively with similar organisations can help direct charities to data which will be useful. This of course needs to be preceded by the charity being certain of their mission and understanding how their activity leads to an outcome.

Another barrier to using data effectively for many charities is the lack of staff with requisite skills. At the minimum it requires someone with an aptitude for, and interest in, analysis. For anything more advanced it requires specialist skills and knowledge. Many charities cannot easily recruit for or free up time for staff to dedicate to data analysis. With tight resources, some charities feel they can’t prioritise data analysis.

But for those who need help to understand and use their data there is an increasing number of organisations which can provide free support such as Pro Bono Economics, Operational Research Pro Bono and DataKind UK. Larger charities are also increasingly publishing data visualisation and analysis tools, as are funders such as the Nominet Trust who supported the Global Value Exchange and Data Unity.

There is a missing ingredient however in this call for increased use of intelligent data. Overcoming these barriers — recognising data’s potential, understanding its supply, and having the awareness, capability and capacity to deal with it — is still not sufficient. We know from our experience of encouraging impact measurement in the sector that just because something makes sense and is possible, it doesn’t mean people will do it.

Data does not always give the answers you expect. It might show that your view of the most important needs, or how well your service works, is only partially right, or even wrong, and that you need to change things. Changing established work patterns can be difficult and sometime staff can be antagonistic to change. Charities, or individuals in them, need a real desire to understand whether they are doing the best work possible and to identify how to improve this — however uncomfortable it might be. It requires persuasive and engaging leadership highlighting the benefits of the change and clear communication of how these benefits have been realised to really happen.

Moving forward
Another block is the lack of incentives. Many funders and commissioners do not require charities to use data in an intelligent way. Requests for data, whether on need or results, are generally satisfied with a token effort of inserting a few numbers that offer no genuine insight into the question at hand. This can be compounded by funders and commissioners requesting varying levels of similar but not the same data, which takes time, overcomplicates and can further disengage charities from using the data. Funders could support charities to provide better data by writing clear guidance on what is needed and why and providing training if necessary to skill up charity staff.

Attitudes towards ‘failure’ in the sector act as a disincentive to real scrutiny of data, in case it highlights that something is wrong. Worse, the pervading narrative in the sector of high-performing charities working to tackle acute unmet needs means that any result less than superb, or analysis of need less than disastrous, can be seen as a weakness. The current environment — reduced funding, fierce competition for resources, more resultsrelated payments, and a readiness to criticise charities — creates an even greater aversion to risk, which in turn is a disincentive to data use.

Results-based funding mechanisms, such as payment by results and social impact bonds, provide a reason for some to engage with their data, but a much wider change across the sector is required. Funders have an important role to play in championing the open reporting of data and should support charities to understand why an intervention may not have worked to reduce the fear that charities have about admitting to ‘failure’.

Making use of intelligent data is an essential way for charities to improve their operational effectiveness, the service they provide to their beneficiaries and ultimately the outcomes they achieve. Charities need to continually review the data they collect against their mission and funder requirements, remove unused data and make the most of the increasing amounts of open and big data which is being made available. There’s a risk that if charities don’t do this they limit their potential to provide solutions to those most in need.

Tracey Gyateng is Data Lab project manager at NPC: www.thinknpc.org

Notes
1Bagwell, S., de Las Casas, L., Abercrombie, R. and van Poortvliet, M. (2013) Money for good UK: Understanding donor motivation and behaviour.
New Philanthropy Capital.

2 Centre for Social Justice (2013) Something’s Got to Give. The state of Britain’s voluntary and community sector.
http://www. centreforsocialjustice.org.uk/publications/something’s-got-to-give

3http://www.cesi.org.uk/statistics/tools

4 http://england.shelter.org.uk/professional_resources/housing_databank

5 http://data.jrf.org.uk/

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