What sets us apart
At Dignity Best Practices, we believe that it’s not just the “what,” it’s the “how.” Local government successes in serving vulnerable populations are sustained not primarily by emphasis on which model for change is chosen (the “what”), but instead rest on strong relationships between actors, effective implementation of core practices, commitment to the spirit of the model, measurement of real results, and ongoing iteration (the “how”). Above all, Dignity Best Practices helps instill this core “how” into each project by keeping plans connected to the dignity of those being served.
1. Our focus: We center vulnerable populations and their outcomes.
- When building new models with clients, we keep home and street-based realities at the front of our mind.
- We build client feedback loops, so local governments can continue to get assessments on the success of their implementations
- We help you monitor equity in outcomes, not just theoretical access
2. Our Method: We promote effective practices rather than being partisans of one model.
- We use information gathered from research, our Learning Communities, case studies, and other successful clients to develop a collection of best practices that can be translated from context to context
- We recognize the success or failure of models is based more on implementation details than the specific model chosen
- We help leadership distinguish essential components of a given strategy from the more flexible elements so that best practices can be successfully implemented without losing impact
3. The Cornerstone: We see relationship-building between actors as vital, not nice-to-have.
- Our programs are co-created through cross-agency working groups and community engagement, keeping everyone involved and bought-in to the process
- Interventions are embedded into social structures to encourage sustainability
4. The Impact: We build an improvement engine rather than a one-off moment of change.
- We build in collective responsibility so everyone contributes
- We build in quarterly iterative checkpoints