Following from my last post, I wanted to share a little more about what the RADIQUAL Framework is and why I designed it. I noticed an ongoing need for a unified framework that better integrates my business practices with the values I espouse through my work. As in my last post – I would feel like a hypocrite to support organisations with climate change advocacy if my business uses vendors that aren’t vocal about climate change. Obviously this isn’t going to work for everyone or all businesses, but I wanted a comprehensive framework where I could link my personal and business values together with my work.

RADIQUAL is a framework and a methodology. I use specific tools and approaches in my evaluations or training, and I draw from my methodology toolkit. It’s proprietary, but I wanted to share more about why I’ve found it useful in case other researchers are also interested in designing their own framework.

It is rooted in the idea that businesses and social impact organisations need to be more adaptable, inclusive, and evidence-driven than in the past. This approach includes taking moments to regularly reflect on your work – within a project and as a consultant, your relationships with clients – and to learn from them.

Morbidly, I call them post-mortems, but they are guided conversations within teams, or between yourself and a client, to learn and document new ideas. This is exactly the same as the ‘feedback and response’ mechanisms we build into community-led projects. There’s no reinvention of the wheel; I’ve just applied something from PMEL to my business.

Why is it Needed?

• Mostly, to practice values. I insist on aligning objectives between my technical work and my business, between myself as an individual and my teams, between my and my client’s vision for the work, and making sure we are all agreed on the key ideas.
• Evidence-driven decision making, helping me to ensure that evidence is gathered at each stage of a project so that in an evaluation, we can keep subjectivity to a minimum. I embed validation/triangulation at multiple points during data collection, analysis, and dissemination rather than just during the former, as is common.
• Proper inclusion, by spelling out your aims and principles at the start and inviting people to share feedback with you. This has made me a better PMEL practitioner, since I am constantly learning from others and my clients. Inviting – and encouraging – feedback also demonstrates your expertise, and in sharing my data regularly during a feedback, my project’s conclusions are all the more likely to be accepted.

For example, if I’m working on an evaluation I will host joint validation workshops with my communities and partners to discuss key insights emerging from the data. We discuss what these conclusions could mean for the project or organisation being evaluated, and we develop a holistic understanding. Doing so in a more inclusive way also allows me to maintain my objectivity and role as an external researcher, without forcing my agenda on anyone. This has helped me significantly minimise the areas of potential bias in my work, and meant that my recommendations are all the more likely to be adopted -making my work more successful.

I’d love to hear more about other frameworks you have encountered in PMEL or JEDI work – how have they helped your work, strengthened your skills, and deepened the legitimacy of your work? In using a participatory framework for example, are you as an implementer becoming a more participatory organisation? Or as an evaluator, has adopting a feminist approach made you a more feminist practitioner?