Showing posts with label policy development. Show all posts
Showing posts with label policy development. Show all posts

Friday, November 27, 2015

Experimenting with Policy Development

by Nick Charney RSS / cpsrenewalFacebook / cpsrenewalLinkedIn / Nick Charneytwitter / nickcharneygovloop / nickcharneyGoogle+ / nickcharney

A few weeks ago I pitched a experimenting with open policy making at Policy Ignite here in Ottawa with my friend and colleague Todd Julie. The rationale for the presentation was pretty straight forward:
The policy monopoly of elites no longer exists. Opening up of policy process creates competition between options and questionable interpretation of the facts and contexts upon which they are based. In the future, data analytics, social media and citizen consultation should allow the triangulation of different perspectives in a way that respects factual analysis and arrives at common solutions. However in the interim, as policy tools, players and perspectives continue to change, governments must choose between competing policy priorities. Foreseeing the wider implications of these choices is critical to addressing today's "wicked" problems. However, very little is known about the different policy avenues available and the type and quality of policy advice that can be reasonably expected if it is pursued.  

In the presentation we argued that, if you accept the rationale than you are also likely to accept experimentation with policy development to facilitate learning; leading us to propose the following 6 step policy making experiment:

Step 1: Pick a wicked problem

Step 2: Frame the policy question

Step 3: Set a time limit

Step 4: A/B test different approaches:

  • Traditional, internal, institutionally led
  • Open, external, crowd driven
  • Contestable, outsourced, single private firm 
Step 5: Evaluate the results vis-à-vis common characteristics of any good policy:
  • It serves the public interest.
  • It follows appropriate laws and is enforceable.
  • It aligns with the organization’s mandate and direction and accountabilities are clearly defined.
  • It is evidence-based; assumptions, options, risks, and intended outcomes are clearly articulated.
  • Stakeholders were included in the development process and ideas have been tested prior to implementation.
  • It is historically informed and addresses both long-term interests and short-term concerns.
  • It is cost effective and there is capacity to evaluate outcomes.
Step 6: Socialize the findings to spread lessons learned and inculcate a wider culture of policy experimentation

Essentially, if you had to boil the presentation down to a TL;DR it would be:
We don't know what we don't know when it comes to the different policy-making approaches that are available to us; and if we want to know, then we ought to experiment.

Caveats

There's a couple of related caveats worth mentioning re: the need for greater experimentation:

  • We also don't have a good sense of levels of effort related to different policy development approaches and evaluating/implementing their outcomes. This will require some practical study.
  • We might need to rethink our approach to online engagement as a policy input (See: Thinking, Fast and Slow about Online Public Engagement) because the current tool set may fall short.
  • Regardless of what the different outcomes are in a given experiment, the last mile always belongs to elected officials and their senior civil servants, the best the rest of us can hope for is a more robust evidence base to support existing and emerging tools (See: To Govern is to Choose).
Its worth mentioning that while there has been little activity on this front in Canada, the UK has some experience with it. If this is an area that interests you, I'd recommend looking at the details on the UK Contestable Policy Making Fundthe correspondong press release from its first use, and the Institute for Government's assessment of the fund.


Non-Sequitors

Thank you to the Policy Ignite team for putting on a bang up event, screening us in, and moving us up to the first slot (at the last minute, presumably to warm up the crowd, which I think we accomplished).

Thank you to Minister Catherine McKenna for stopping by the event the day after her swearing in to offer words of encouragement.

If anyone is looking to pick up a good thinker and a talented researcher, you should get in contact with my co-presenter Todd Julie. While I've had a blast thinking through many of the issues facing governing institutions in the digital era with him, he's looking to relocate to Toronto for personal reasons and I'd love that to happen for him.

Wednesday, October 14, 2015

Innovation is Information

by Kent Aitken RSS / cpsrenewalFacebook / cpsrenewalLinkedIn / Kent Aitkentwitter / kentdaitkengovloop / KentAitken

In August, the Clerk of the Privy Council delivered a speech titled “A National Dialogue On Policy Innovation.” Elsewhere, #policyinnovation is one of the most used hashtags by Canadian public servants. It’s somewhat of a hot topic right now. But what is "policy innovation" in the first place? 

For starters, it could refer to "new and interesting ways of developing policy." Or, "new and interesting policy." (See: On Prioritizing Policy Innovation) We tend to use both versions almost interchangeably, but this post tilts towards the former usage. I’ve heard the term used to refer to crowdsourcing and challenge prizes, deep dives into technological and social trends, improvements to government services, behavioural economics, and much more.

But within that nebulous concept, I think there's a central core to the entire idea that may be a useful way to think about how we gather and understand evidence, and how we make and implement decisions. It's all about information.

More options means more precise application


To back up slightly, let’s consider another arc of innovation that is both an analogy and a predecessor, that of telecommunications. We’ve gone from letter-writing to printing presses, telegraphs, telephones, the internet, and now to low-cost ubiquitous mobile connections. Every combination of one-to-one, one-to-a-select-few, one-to-many, public forums, with every combination of attributed or anonymous, for every combination of formats, all at a vanishingly small cost.

But here's the key: at one point, to communicate long-distance you had one option: handwriting a letter. Later, you had two: handwriting a letter, or paying to have something reproduced many times on a printing press. You didn't have to rely on a letter when it wasn't the best option. As more and more options became available, you could match your communications goal more precisely to different ways to achieve it.

Likewise, now we have a wider range of policy development approaches and policy instruments, which means there’s a greater chance that we can match the right approach to the right situation. We have a wider range of options partially because we get inventive over time, but far more so because policy development and implementation often is communication and so we’re simply piggybacking on telecommunications advances.

The information


Which isn’t much of an insight, I recognize. Yes, the internet opens up options for how government does things. But if we start to think of policy innovation as communication, instead of as enabled by communication, it starts to shed light on what we’re really trying to accomplish, and where “innovative” approaches fit in more “traditional” approaches. Using the terms in quotations lightly.

Basically, the approaches that get pegged as "policy innovation" often boil down to two key actions:

  • transferring information between people
  • arranging information for people

It’s the crux of crowdsourcing, policy or service jams, innovation labs, open data, design thinking, challenge prizes, and citizen engagement approaches like consultations, townhalls, and social media chats. Someone has information that policymakers can use: ideas, problems, slogans, lived experience, or academic expertise (see: The Policy Innovator's Dilemma). Then it’s a matter of finding the best way to access it, which is a question of format. You just have to learn the formats. Similarly, once you've crossed the threshold and learned a new telecommunications approach (case in point might be parents and grandparents on Facebook), it becomes part of a passive mental algorithm that takes a need or goal and instantly knows how best to accomplish it.

Talk of policy innovation tends to go hand-in-hand with the idea that policy issues increasingly cross jurisdictional or societal boundaries, and are a part of an increasingly complex environment (see: Complexity is a Measurement Problem or On Wicked Problems). Which is where arranging information becomes invaluable.

Let's say  you get ten informed stakeholders of a given policy question in a room, and ask each for their concerns. They each reveal a different way of looking at the issue, revealings its complexity and pointing out legitimate pitfalls for policy options. The problem is that by the time the tenth stakeholder spoke you forgot the concerns of the first five, so it's impossible to understand all ten in context. It's Miller's Law: human beings can only hold seven things, plus or minus two, in our working memory. Which is where techniques like journey mapping, system mapping, and sticky noting everything are crucial for policy. They're the policy landscape equivalent of doing long division on paper so you can remember everything in play - what we might call mental scaffolding

Many approaches include both transferring and arranging information. For instance, a public consultation might include a call for ideas with a voting mechanism that creates a ranking, signaling importance. Some deliberation platforms include argument mapping systems that use algorithms to arrange the discussions for participants, almost like Amazon bringing complementary products to the forefront. ("Are you outraged at your government about X? Many people outraged about X are also outraged about Y, perhaps you should consider lambasting them on that topic too.")

In other cases, governments can (and should) map out what they already know about a given policy issue to get it out of working memory and focus on change drivers and relationships between forces. This will become increasingly important if we truly want to get out of siloed policy-making, find hard-to-see connections between once-distinct policy areas, and genuinely understand entire systems. Our governance model was built for a world we falsely believed was simpler than it was, and within that we're running into our own cognitive limits. We literally cannot hold all the elements of a complex policy issue in our heads without some kind of mental scaffolding, be it tools, other people, or paper.

Metadata

Two notes on metadata, or information about information (an example would be how DSLR cameras automatically include date stamps, aperture, shutter speed, iso, and more information in image files).

First, some approaches that get lumped in with policy innovation don't fit perfectly with the transferring and arranging information categories. Behavioural economics, for instance (and its service delivery cousin of user testing), seems more like creating new information through research. But viewed from a policy lens, I'd suggest it's actually more like metadata.

Let's say government wants to maximize the rate of tax returns, so tweaks the language on letters to taxpayers to see what framing resonates with people. Here's the UK example:

"...replacing the sentence “Nine out of 10 people in the UK pay their tax on time” with “The great majority of people in [the taxpayer’s local area] pay their tax on time” increased the proportion of people who paid their income tax before the deadline."

The core policy instrument here is a law, and the letter sent to taxpayers is supporting education about the importance of filing tax returns. In this case, the information is in the letter. The behavioural economics piece is metadata about that information: how many, and which, people acted upon the information they received. It's still really about transferring information between people, which puts tools like behavioural economics and data analytics in this common framework and may help practitioners navigate between possible approaches.

Second, there's a meta-level to the idea of transferring and arranging information that changes the value of different approaches and formats. We might call it "conspicuous innovation" or "conspicuous engagement." Basically, the transfer and arrangement of information is not the only goal achieved by these approaches - someone emailing a policymaker a vital piece of information for a policy question is worth less than that same person posting it publicly during an official consultation. The metadata for that piece of publicly posted information includes the number of views from other people, the signals about government's attitude towards governance and transparency, and the future value to others. 

So what?

The "policy innovation" toolkit centers around two actions: transferring information between people and arranging information for people. Past this common core, it's often a question of forums and formats (increasingly, but not uniquely, about how we transfer information from non-governmental actors) (with exceptions, of course). So what?

One, I think it's worthwhile to examine what binds the idea of policy innovation together, to refine our working concept of the term.

Two, I think thinking in these terms highlights what we're actually trying to accomplish through these approaches, and might make it easier to choose between them.

Three, putting them in a historical context puts the perceived risk in context. I mean two things here: first, that policy innovation is very similar to our personal experience with telecommunications advances: more options allows more niche approaches, and eventually they become routine. Second, that if some of these approaches are at a fundamental level analogous to things government has been doing for ages, they seem less daunting. For instance, there are dozens of consultations ongoing at http://www1.canada.ca/consultingcanadians at any given time. It's just a different way of transferring information between people and policymakers.



Thank you to Blaise Hebert and Nick Charney for super interesting conversations on this topic.

Also, two recent posts from Melissa that are good general fodder here: What Innovation Feels Like, Part 1: Fear; and Part 2: Lack of Trust

Friday, January 24, 2014

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

by Nick Charney RSS / cpsrenewalFacebook / cpsrenewalLinkedIn / Nick Charneytwitter / nickcharneygovloop / nickcharneyGoogle+ / nickcharney

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:

Social Media + Big Data Analytics = Future of Public Policy

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

(Public Sentiment + Data Analytics) / (Design Thinking + Behavioural Economics) = Future of Evidence Based Policy

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 actually 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.

On Savvy Policy Makers

Savvy policy makers (and for that matter, elected officials) are likely the ones able (and willing) to chart their policy directions against this type of model; the one's who can say with confidence:
"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?

Wednesday, May 8, 2013

Moving Public Service Mountains, Part I

by Kent AitkenRSS / cpsrenewalFacebook / cpsrenewalLinkedIn / Kent Aitkentwitter / kentdaitkengovloop / KentAitken


This post will be part one of at least two. Next week I'll explain why I believe this is so incredibly important.


At The Museum of Nature in Ottawa, visitors can simulate an earthquake in the Vale Earth Gallery. You turn a crank to pull a spring-loaded hunk of simulated mountain over a surface, and at some point the force overcomes the friction and it slams back into place. The intended lesson is that it's impossible to predict exactly when the tipping point will be reached; each experiment plays out differently.

On To The Dogs or Whoever I referred to a possible “tectonic” shift approaching for public service. I can see the possibility of a very different model for how the bureaucracy functions, develops policy, interacts with Canadians, and creates a competitive advantage for Canada. And in the last few weeks, I've discovered that others have the same hunch. People arrived at this prediction from two very different roads, some on account of mounting evidence, and some from feeling the increasing weight of necessity.

But like the museum counterpart, it's hard to tell if that tectonic shift is actually about to happen. If this mountain worth of inertia is about to move. Or if it needs a shove.



Some of the evidence I would point to:
  • It was recently announced that Deputy Minister Robert Fonberg would join the Privy Council Office with a specific mandate to examine the broader policy development model.
“I believe that we need a clear and shared vision of what Canada’s Public Service should become in the decades ahead,” the Clerk wrote, adding that Deputy Ministers have been tasked with engaging “all public servants in this important dialogue about our shared future.”

Some may greet this litany of anecdotes with skepticism. One could point to Public Service Renewal, the push for a strengthened public service that launched in 2006 or 2007, and ask how far we've come. Is today any different?


Necessity is the Mother of Innovation

On the necessity side, I feel that we have a better grasp now of the mounting need for committed renewal:
  • Deloitte's William Eggers highlights, in his Public Sector, Disrupted report, that government is the one sector of economy where innovation has not pushed down costs.
  • Samara's research suggests that the number of Canadians satisfied in the way Canadian democracy works dropped from 75% to 55%, in only 10 years.
  • Research from Nanos also puts Canadian's level of trust in public servants at record lows. Only 14% surveyed responded that they had a distinctly positive view of the role of Public Servants in developing public policy.
All is not necessarily well. I would go so far as to suggest that the status quo is a risky position. So what's next?


Mountains to Move

So here stand we. Staring at a mountain that may, or may not, be ready to move.

We know that it needs to, and we have some forces pushing. It could be another Public Service Renewal, in which we never quite leaned in enough to overcome our inertia. But we have that lesson learned to build on, and the rules have changed. We have black swans proving the possible: there is a Deputy Minister conversing frankly and openly with public servants of all levels and backgrounds about policy development on GCConnex. Another deputy head has resoundingly proven the worth of employee engagement through honest, personal social media interaction. Pictures of cats and all. And the silo-defying, self-organizing GC community is stronger than ever, and has a science fair of success stories to showcase.

Often, we don't know what we don't know [see: The Importance of Being Earnest (and Open)]. And that (unnecessarily) incomplete picture of the world leads to pitfalls and obstacles; in this case, additional friction holding this mountain back. But today, that cold fact is increasingly recognized, and input is being widely solicited. I think we have a unique opportunity now to create discussion.

I don't want to look back, years from now, and wonder if that mountain was ready to go. If all it needed was one more good shove.



*I'd like to unpack that last one for a moment. When I first heard that figure, I found myself wondering how much was due to a safe and generous benefits system, and how much was due to mental health issues. Not that either exists in a vacuum. If a portion is due to the benefits system, it makes me wonder how many of our private sector peers are suffering through untreated mental illness because they are worried about losing jobs, or because they don't have needed benefits. And I'm certain that the system, alone, doesn't explain the discrepancy between public and private rates. Public servants are also more likely to binge drink, which is indicative of stress and mental health issues (although income and education levels impact here as well). There's a direct, and significant, correlation between engagement levels and absenteeism. And there are links between one's perception of control over their jobs and their health. I believe that mental health issues for public servants are a genuine issue and merit significant concern.