The rise and rise of outcomes

With the move to reporting on outcomes gaining pace, Dale Renner, director of Latitude Network, shares advice on what social organisations can do to build an outcomes-focused organisation.

Have you noticed that more and more philanthropic and government funders are asking for proposals to have an “outcomes focus”? Impact investors and service commissioners increasingly want evidence that a program makes a difference.

The move to report on “outcomes” is gathering momentum and for good reason. The purpose of social sector funding, whether in homelessness, mental health or child protection, is to improve the lives of people – to make a difference. That’s also the mission of every social sector organisation. 

An outcome is a way of defining and measuring this important “difference” made in someone’s life – between dropping out of school and finishing school, between being employed or not employed, between mental distress and a sense of wellbeing. By defining and measuring the right outcomes, organisations and funders can focus efforts on what matters most to the service recipient, and therefore make the most social impact.

Funders have been experimenting with different ways to fund for outcomes, particularly over the last decade. A complex form of outcomes funding is a social impact bond (SIB), where a third-party provides an upfront investment to cover program costs in advance of the outcomes being known and outcome payments being made by the program funder (usually government). In Australia four states have funded more than $100 million across a dozen SIBs so far. We are seeing more government interest at federal and state levels in funding programs on an outcomes basis. Even if your funder is yet to raise this with you, the pressure is on to demonstrate outcomes per dollar spent, and to compare this to other programs or organisations. 

Every social organisation we talk to is somewhere on the outcomes and data journey – sometimes one program has lots of good data but isn’t using it for decision making, and another area hasn’t yet decided what data to collect. Many organisations have invested in client databases (CRMs/CMSs) to deliver data that government (or external stakeholders) want, but haven’t thought through what is the right data to collect that will aid continuous improvement and demonstrate impact.

Latitude Network believes that we are on the verge of a data-driven performance jump in the social sector. The manufacturing world went through a data and performance revolution when Toyota adopted the ideas of American Engineer William Deming in the early 20th century. More recently the worlds of marketing and software have used analysis of “big data” to continually improve services and to better tailor services to individual needs. Just as the key to those leaps in quality and effectiveness in the commercial world was access to better and more precise data, we are now seeing tools emerge to enable impact improvements in the social sector. 

Journey to ‘outcomes-focus’ 

Being an “outcomes-focused” organisation goes beyond simply defining some outcomes and commissioning program evaluations. While program evaluations can be important tools to prove point in time impact (especially if you have a counterfactual or control group to test against), other tools are needed for the modern fast-paced challenges of data-driven organisations. One state treasury official we talked to recently stated that they would much prefer to see social organisations investing in their own data capability and generating ongoing insights than in static program evaluations. 

Using data and focusing on outcomes are important not only to ensure an organisation is delivering its mission and continually improving its effectiveness, but also to be competitive when it comes to philanthropic and future government funding. The business case is heart and head, mission and financial.

So what can social organisations do to build an outcomes-focused organisation: 

1. Put outcomes and data on the agenda – this means building the internal coalition of forward-thinking executives to demand outcomes and quality data. Does the board want better metrics and reports to track impact (not just finance or risk-related metrics)? Does the executive team crave visibility over program delivery, performance gaps and risks? Do frontline workers have the information they need to make informed decisions about where to spend their time and what parts of the service model to apply to which clients?
2. Build disciplined program logics for key programs (and possibly a system logic for multiple programs working together) – a theory of change is a theory until you prove it. Program logic uses evidence and practitioner experience to map what activities lead to what changes and what outcomes. It’s hard to improve service models if they aren’t mapped out ready to be tested.
3. Don’t equate data systems with IT systems – a mistake we have seen is organisations investing huge sums (millions of dollars in some cases) in IT and CRM before the thinking has been done on what to measure and how to use the data. There are now off-the-shelf low code database systems that social organisations can use for low risk low cost solutions compared with traditional IT. Even small organisations can be great at data without the price-tag.
4. Decide what to measure, based on your program logic – an outcomes focus means measuring outcomes (which itself can be tricky), but it also means measuring lots of other things to help you identify what’s working and how to improve.
5. Engage staff and clients in the design process – becoming an outcomes-focused organisation is a significant change from traditional social sector approaches, so engagement and bringing people along is vital. But drive from the top and leadership is needed as well – any change, even good change, is hard. Our experience is that once people really start to use data and see how it improves lives, they become converts.
6. Just get started with collection, with an MVP system (a minimum viable product) – before you lock in the design of any databases, collecting data with free- or low-cost tools can be a good idea. We often don’t know the value (predictive value) of a metric until we start collecting it – so we sometimes suggest a three to six month period of “just collect it”. At the end of that test period you can analyse the data to find out what’s useful.

Once you’ve got data, the next phase is to use the data well – easier said than done. This means collating data, building dashboards, visualising the right data, and testing and refining it. And if you have great data with good “before” and “after” measures of outcomes, it might be time for some really exciting analysis – using artificial intelligence tools (machine learning) to identify segments and build predictive models that help you improve impact and become more efficient. But perhaps that’s a discussion for another time.