Four best practices for scaling up effective innovations

Community member post by Amanda Fixsen, Karen Blase and Dean Fixsen

What is involved in effective scaling up of innovations in order to achieve social impact? Here are four best practices, drawn from our experience in scaling up human services innovations and programs for children and families. We also provide definitions of the key terms used.

1. Understand the target audiences

Effectively scaling innovations first requires attention to defining the denominator, or population of interest for the scale-up effort, as well as the numerator, or the number of children and families who are receiving the innovation with fidelity and good outcomes.

2. Purposeful design leads to high-fidelity use

Human service systems are legacy systems comprised of an accumulation of fragments of past mandates, good ideas, beliefs, and ways of work that evolved over many decades as legislators, leaders, and staff have come and gone. These legacy systems can be fragmented, siloed and inefficient.

To realize social impact, organizations and systems need to be designed, or re-designed, on purpose to produce and sustain high-fidelity use of effective innovations.

3. Focus on scaling proven programs

Attempts to scale ineffective or harmful programs are a waste of time, money and opportunity, so programs must reliably produce positive outcomes for the population of interest.

Given that we are focused on scaling interaction-based programs that require service providers to use the program within a larger systems context, there is a great deal of complexity involved in “scaling up.” It may be difficult to assess the quality of the program for the children and families who are receiving it, as good fidelity measures for programs are not common.

amanda-fixsen
Amanda Fixsen (biography)

karen-blase
Karen Blase (biography)

dean-fixsen
Dean Fixsen (biography)

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Good practices in system dynamics modelling

Community member post by Sondoss Elsawah and Serena Hamilton

sondoss-elsawah
Sondoss Elsawah (biography)

Too often, lessons about modelling practices are left out of papers, including the ad-hoc decisions, serendipities, and failures incurred through the modelling process. The lack of attention to these details can lead to misperceptions about how the modelling process unfolds.

serena-hamilton
Serena Hamilton (biography)

We are part of a small team that examined five case studies where system dynamics was used to model socio-ecological systems. We had direct and intimate knowledge of the modelling process and outcomes in each case. Based on the lessons from the case studies as well as the collective experience of the team, we compiled the following set of good practices for systems dynamics modelling of complex systems. Continue reading

Successful implementation demands a great liaison person: Nine tips on making it work

Community member post by Abby Haynes on behalf of CIPHER (Centre for Informing Policy in Health with Evidence from Research)

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CIPHER Sub-group (Participants)

When external providers deliver a complex program in an organisation, it is crucial that someone from that organisation—a liaison person—gives ‘insider’ advice and acts as a link between their organisation and the program providers. What are the characteristics to look for in filling that role? And how can liaison people best be supported? Continue reading

Values, confidence, and time: What researchers should consider when engaging with civil society organisations

Community member post by William L. Allen

william-allen
William L. Allen (biography)

When researchers want to engage or work with groups outside universities—especially civil society organisations—what should they consider as part of this process?

Civil society comprises organisations—large and small—that are outside of the public and private sectors. These include non-governmental organisations, charities, or voluntary groups.

Three lessons emerged from asking civil society organisations what they would tell academics who want to work with them: Continue reading

Overturning the design of outcome measures

Community member post by Diana Rose

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Diana Rose (biography)

Outcome measures in research about treatment and service provision may not seem a particularly controversial or even exciting domain for citizen involvement. Although the research landscape is changing – partly as a result of engaging stakeholders in knowledge production and its effects – the design of outcome measures has been largely immune to these developments.

The standard way of constructing such measures – for evaluating treatment outcomes and services – has serious flaws and requires an alternative that grounds them firmly in the experiences and situations of the people whose views are being solicited. Continue reading

Pro-active learning to improve interdisciplinary processes

Community member post by Laura R. Meagher

Member of Board of Governors
Laura R. Meagher (biography)

I am a firm believer in looking at interdisciplinary collaboration and knowledge exchange – or impact generation – as processes. If you can see something as a process, you can learn about it. If you can learn about it, you can do it better!

I find that this approach helps people to feel enfranchised, to believe that it is possible for them to open up what might have seemed to be a static black box and achieve understanding of the dynamics of how nouns like ‘interdisciplinarity’ or ‘knowledge exchange’ or ‘research impact’ can actually come to be. Continue reading