Blending Public Sentiment, Data Analytics, Design Thinking and Behavioural Economics

Originally published at cpsrenewal.ca

The Thinker by Darwin Bell

Last year I wrote a lengthy piece that argued that understanding the future of evidence based policy meant understanding the confluence of big data and social media (See: Big Data, Social Media and the Long Tail of Public Policy). Today I want to further qualify my statements, and refine my conceptual model to reflect some of my more recent thinking.

Project Copernicus

To be fair the conceptual model – which I’ve decided to nickname Project Copernicus (See: Towards Copernicus if you don’t get the reference) – is very much a moving target; and while it ebbs and flows as I come into contact with new (to me) thinking, it’s very much about leaning into the hard stuff (See: Lean into it) and “building a better telescope” (See: Complexity is a Measurement Problem).

To recap quickly and push forward

At the outset of the aforementioned piece I offered up a TL;DR summation that was essentially:

And feel that refining that statement is as good as a place to start as any; here’s my latest thinking:

In a sense its a rather simple, back-to-basics model that argues that the sum of what the public wants (sentiment) and what the evidence suggests is possible (data) is best achieved through policy interventions that are highly contextualized and can be empirically tested, tweaked, and maximized (design thinking + behavioural economics) while simultaneously creating new data to support or refute it and facing real-time and constantly shifting public scrutiny.

I have a number of reasons for nuancing the model

• Public Sentiment is broader than social media and it is incumbent on policy makers to be as inclusive as possible when incorporating sentiment. Focusing on social media ignores issues of the digital divide and unduly privileges those with greater digital literacy. This may be one of the reasons that the Deputy Minister’s Committee on Social Media and Policy Development was recast as the Deputy Minister’s Committee on Policy Innovation; social media may be innovative but it doesn’t necessarily follow that innovative ideas flow from social media.
• Data Analytics is broader than Big Data and includes both linked data and open data. These don’t necessarily always fall into the category of big data on their own but will play an important role as more and more data sources start to rub up against each other.
• Design Thinking combines empathy for the context of a problem, creativity in the generation of insights and solutions, and rationality to analyze and fit solutions to the particular context
• Behavioural Economics brings sentiment, analytics, and design to ground by emphasizing what people actual do when faced with a given situation (rather than what we think they ought to do)
• Evidence Based is an important qualifier and cannot be narrowly construed as relating to only one of the variables on the left side of the equation; evidence comes in many forms and it is up to policy makers and elected officials to determine how to weigh the different sources of evidence (variables in the equation above) against each other in a given set of circumstances.

“Here is what we’ve heard from the public, here is what the evidence supports, and here is the most policy intervention we have determined to be the most efficacious. However, it is one we will continue to refine over time, as it creates new data, and is forced to stand up to real world public scrutiny”

When was the last time you heard someone qualify a policy position with that kind of preamble?