Numbers and nonsense in Oakland’s Search for Public Safety

Oakland is once again talking about data and facts concerning crime, causes and policing practices, except we’re not really. We’re talking about an incredibly thin slice of a big reality, a thin slice that’s not particularly helpful, revealing nor empowering. And this is how we always do it.

Chip Johnson is raising the flag on our lack of a broad discussion about the complexity of policing practices and the involvement of African-Americans in the majority of serious crimes in our city, and on that I say he’s dead right, these are hard conversations and we’ve not really had them openly. The problem is, the data we’re given as the public (and our decision makers have about the same) is not sufficient to plan with, make decisions from nor understand much at all.  Once again we’re given a limited set of summary tables that present just tiny nuances of reality and that do not allow for any actual analyses by the public nor by policy makers. And if you believe that internal staff get richer analysis and research to work with you’re largely wrong.

When we assume that a few tables of selectively chosen metrics suffice for public information and justification for decisions or statements, we’re all getting ripped off.  And the truth is our city departments (OPD esp.) do not have the capacity for thoughtful analytics and research into complex data problems like these.  And this is a real problem.  Our city desperately needs applied data capacity, not from outside firms on consultancy (disclosure: my current role does this sometimes for the city) but with built up internal capacity.  There is a strong argument for external, independent access to data for reliable analysis in many cases, but our city spends hundreds of millions per year and we don’t have a data SWAT team to work on these issues for internal planning.  Take a look at what New York City does for simple yet powerful data analytics that saves lives, saves money and makes the city safer.  This is what smart businesses do to drive better decision making. 

Data, in context, with local knowledge and experience, evidence based practices (those showing success elsewhere) and a good process will yield smarter decisions for our city.

Data tables do not tell us about any nuances in police stops, we don’t know how these data vary across different neighborhoods nor anything about the actual situations around each stop- the lack of real data that shows incident level activity makes any real understanding impossible.

For example, the data report shows that White stops yield a slightly higher proportion of seizures/recoveries, so logic says why don’t the OPD pull over more White folks if they lead to solid hits at least as often?

Back in 2012 the OPD gave Urban Strategies Council all their stop report data to analyze, but there was no context nor any clear path of analysis suggested making it near impossible to produce thoughtful results, nor was it part of our actual contract.  But the data exist and should be used by the city to really understand how our police operate, the context of their work and the patterns that lead to meaningful impacts rather than habits that are not reflected upon and never questioned or changed.

it is not our cities job to just do the work, process the paperwork and never objectively review meta level issues.  According to our Mayor “Moving forward, police will be issuing similar reports twice a year”. We need data geeks in city hall to support our police and all departments and in 2014 we need to be better than data reports that consist of a set of summary tables alone.  Pivot tables are not enough for public policy.

If you’re still reading- the same problem arises with relation to the Shot Spotter situation- the Chief doesn’t think it’s worth the money, but our Mayor and CMs want to keep it- we now have the data available for the public but we’ve not really had any objective evaluation of the systems utility for OPD use- and we’ve certainly not had a conversation in public about the potential benefits of public access to this data in more like real time! Just looking at the horrendous reality of shootings in East Oakland over the past five years makes one pause very somberly when considering how much the OPD must deal with and how much they need more analytical guidance to do their jobs better and more efficiently.

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For a crazy look at shootings by month for these five years take a look at this animation– with the caveat that not all the city had sensors installed the whole time and that on holidays a lot of incidents in the data are likely fireworks!  Makes me want to know why there is a small two block section of East Oakland with no gunshots in five years- the data have been fuzzed to be accurate to no more than 100 feet but this still looks like an oasis- who knows why?

Oakland Planning, data and engagement

There’s a frustrating but worthwhile read over at sf.streetsblog on the city’s decision to close down part of the Latham Sqaure pilot in downtown Oakland. The pilot was meant to last for six months and is being partly shelved after just six weeks. This is another sad example of bad use of data, closed decision making and poor engagement in our city.

Problem # 1:

Planning Director Rachel Flynn, when asked for data on Latham Square’s use, said, “We don’t know how to measure pedestrian and bicycle activity.”

This is 2013 and with the powers of Google at our fingertips (yes, despite the clunky computers in city hall they still can get on to the internets). There are two stupidly simple options should this have been something our city staff actually wanted to do- to understand the problem or the situation. We could have worked with local hackers to build simple, cheap sensors using Raspberry Pi devices and off the shelf sensors- read how here. Or we could have simply paid for a small pilot using the super clever MotionLoft system built in SF that is aimed at helping retail businesses understand pedestrian flow and patterns.

No data is not a situation that is acceptable in this century.  No data simply suggests we don’t care enough to gather it. It says that facts are not really what matter, it’s all about perception and personal opinion. No data cannot be adequately challenged or debated. Data are not everything, but no data are dangerous.

Problem #2:

When you hear an official say something like “we were kind of hearing the same thing over and over” you should be skeptical. Especially when you have people representing significantly sized local organizations stating that they have heard almost nothing but differing opinions to those proffered by city staff.  This problem breaks down into two sub-issues. Firstly, the type of engagement common in our planning dept and the city in general- a couple of town hall meetings which tend to attract squeaky wheels who are in opposition to most projects and are only scheduled to suit a small percentage of the community.  In person alone is not a sufficient form of engagement given how digital our community largely is.  Secondly, there is little opportunity to really test this statement- the meetings don’t have nicely recorded videos to replay the conversations and oppositions and the city is not maintaining an online discussion on the pros and cons of this project. We have no record of these complaints within easy reach.

So what?

It’s disappointing that in a city that desperately lacks any innovation or experimentation, we cancel one of the few creative place based projects so fast.  When the rationale to end the project is that it was "prompted by negative feedback… What we’ve heard from property owners and businesses is they need that access” for cars, it’s hard not to wonder if that is the best approach to civic decision making.

Almost no project or idea in Oakland goes without its critics- if we shut down every experiment to improve our city with no data to objectively measure the impact and if we continue to fail to leverage online communities for ideation and constructive feedback, we are doomed to remain a city under-invested in itself and its future.

If you love the current (well, former) plaza, you can sign the WOBO petition.

Don’t Silo Your Geeks

First posted on the Harvard Data Smart Cities here

I’ve just told another partner organization “Don’t silo your geeks!”  It’s about the tenth time this year that I’ve conveyed this message.

The way most organizations utilize research, mapping and data is the same whether the analysis comes from an internal group or a contracted partner. You ask the data folks to do some analysis, with a well formed plan to give them, then get the results and go do the thinking work to implement a new plan or improve an existing effort. So what’s wrong with this model? Everything. This model not only serves to perpetuate a gross misunderstanding, it also serves to devalue your own staff and to rob your organization of valuable insights.

When you take your broken car to a mechanic for repairs you tell them the symptoms and then leave them to do their thing. All good.  Unfortunately with data analysis you’re not just following a formula model like: issue+data+geek=result.  By handing over a specification or formed plan for analysts to follow, you’re missing the fact that the analysts know an enormous amount about what is possible, best practices for indicators, methods and communication styles, and about how to frame a research project to ensure your goals are met. Data geeks actually happen to know a lot about your work, your issues, and how to effectively think through a problem.  We’ve long treated data folks as simple number crunchers who know magic tricks that we leave alone to do their thing. That’s a serious misunderstanding.

Involve your data partners in your thinking, strategy, and planning and you ensure a higher chance of success for your project.

This approach sends a message to your data team or consultant that you really only consider them useful for doing the geekery, that they cannot possibly understand your problem or the end application of the data.  When organizations maintain the stigma of data analysts being simply geeks who like tech, you ensure those very talented individuals will never truly reach their potential in your organization.  Given the average analyst possesses traits including problem solving abilities, critical thinking skills and rare creativity, do you really think we’re using them best by siloing them away and perpetuating the geek stereotype?

More importantly, you ensure that your analysis is never as good as it should be by isolating the data folks from your initial thinking process, from your planning and brainstorming phase and your research formation efforts.

Would you take your car to the mechanic with a detailed procedure to follow? Not likely, you’d consult with them and develop a plan that includes their detailed knowledge and your broader mission (namely keeping your car reliable). Then they execute, you receive the results.  By engaging with your data folks in the early phases of a project you add valuable perceptions and insights, you allow for perspectives on what can be done, what would be problematic and how best to frame the plan.  You gain from having the folks who will execute your plan helping to form it, ensuring that your ask is reasonable and that your ideas can be executed upon.  A weak plan is nearly impossible for some research group to turn into a useful end product.  Involve your data partners in your thinking, strategy, and planning and you ensure a higher chance of success for your project.

Likewise, when you get your research report, data outputs, maps or other results, don’t consider the role of your data geeks to be over.  I’ve witnessed so many planning and implementation meetings where the folks in charge butcher the data analysis or misinterpret the maps, leading the effort down a bad path with less chance of the desired impacts.  Take the data geeks out of this stage and your chances of making similar mistakes are seriously amplified.  Keep your data partner engaged in this crucial last stage. Allow them to help form the end result, expect that you will raise up further data questions that will require more work to go back and answer.

A final benefit in keeping your data team involved at all stages is that you’re building the capacity and skills of your data folks, giving them insights to better guide their phase of the work, strengthening your team, and allowing for more diverse, experienced voices in your efforts. That’s rarely a bad thing.

State of the City from Living Cities

Living Cities has published a new report on the state of cities in the USA, it’s a worthwhile read if you’re already reading my blog. It’s not that long, really. It lays out a number of key struggles our cities are facing and suggests some innovative practices that show promise, but mostly paints a very daunting picture of our country’s future.  I just bought a home, for the first time, and that process of viewing, inspection and bidding highlighted the poor condition of so much of our housing stock built in the 1950-1954 boom.  We have an aging population and high unemployment and it seems to me that much of the housing stock in the east bay has some serious deferred maintenance. We don’t seem to be able to maintain our own homes to a high standard, just like we don’t seem to be able to maintain our cities, infrastructure and schools. 

the community development sector has failed to keep up with these enormous changes. Our systems for supporting national prosperity and individual economic opportunity were built for different times on outdated assumptions. Place-based efforts, while beneficial to some, are not sufficient to reaching the scale necessary to fix these broken systems. We cannot simply manage decline in cities – we must be on the cutting edge of these economic and social shifts and change how cities operate.

This paragraph stood out to me- the idea that we are managing decline in our cities rather than rebuilding our infrastructure for the future- take Oakland’s 84 year road paving cycle for example.

Isolated approaches to fixing our most intractable problems have not worked. There needs to be new, local, ‘civic infrastructure’ built around one table where cross-sector decision-makers come together to set ambitious goals, use data to transform systems and achieve better outcomes.

Having worked in a cross sector organization that does excellent work in forming and sustaining collaborations I see the focus on breaking down decision making silos as a key way to improve our government functioning and our community development efforts.  We’ve seen so many isolated efforts fail because the department only considered their own jurisdiction and mandate and failed to connect their work to those of connected agencies.  You don’t fix urban schools without improving safety and you don’t fund that without good businesses and housing as a base for your community- it all fits together and all must be tackled  together. Get better teachers and schools but don’t fix the juvenile justice system? Nice try. We need more cross sector and inter-agency collaboration and serious planning efforts that accept risks and support innovations that are not comfortable but work to improve our common good.

It is imperative that we build a new civic infrastructure that supports collaboration; that we develop a high performing public sector that provides leadership and resources more strategically

This is something I’m very focused on and feel constant frustration at the pace of this change- we need leaders in our cities who get these new issues, who understand the scale of change needed and who embrace better practice.  We need them to share lessons and failures while being more open to implementing good practices from other cities without feeling the need to reinvent the wheel on every issue in every city. We cannot afford to do things the old way- making unique programs and policies and systems that do the same thing in every city- we need to think more like the open source software community and copy and redeploy as much as we can- we can all build on what others have done and then give back into the pool of ideas, policies and tools to allow others to build on our work. Collaboratively as a country, working together to solve our big problems at a scale that we can fund.

View the full report on Living Cities website here.