I just finished a day and a half in the company of some of the most interesting people in government, chief data officers and their performance management peers. The occasion was the first Summit on Data-Smart Government, sponsored by the Civic Analytics Network. While there were many great and interesting discussions, here is a short description of the 6 key things I’m taking away from these past two days:
- 311 data is always biased. That doesn’t mean it isn’t useful. We have to be mindful of it’s limitations as a system that was meant to collect and manage service request information, not be a scientific instrument for rigorous and fine-grained measurements of our communities on all levels of the socio-economic scale and geographic distribution. Finding ways of comparing service request data with the actual experiences on the ground are essential to understanding and accounting for the biases inherent in the data.
- Be customer focused. Joy Bonaguro gave an amazing presentation showing the approach they use in San Francisco to develop potential projects. They have a clear, transparent process communicating not only milestones and progress but also the partner responsibilities, which includes involving senior leadership in collaboratively scoping the project as well as actually providing the data necessary for the project all smoothed over with the appropriate smiley face emojis. Without those things in place from the partner, the project doesn’t officially start.
- Be more than just data people. This goes along with #2, but we need to cultivate the skills necessary to engage various people in various ways. This means being more aware, sensitive, and empathic. We can’t rely on objective facts to carry arguments with subjective people or discount the value of things that can’t be measured. At the end of the day, we all need to come out of our “creepy little data cave” and talk to actual people about their actual problems.
- Scoping problems is hard. Okay, so this I already knew, which is why I’ve been developing training and protocols around how to structure these types of engagements. As data people, we need more practice facilitating those conversations with stakeholders, building buy-in among not only the converted, but the ones in government who are suspicious of what we do as chief data/analytics/performance officers. They also have valuable things to contribute and we should be reaching out to them whenever possible. I’m a particular fan of design thinking approaches to brainstorming and refining problems, inputs, processes, and potential outcomes.
- Training is important. Also not something that I was unaware of given the work I do training city employees, but the key thing for me was the growing consensus around the relative value of training in the analytics process. This isn’t just for members of the analytics or performance management team, but included the potential partners and other in government who benefit from greater data literacy, learning the art of the possible and becoming empowered to do their own analysis when the city-wide analytics team doesn’t have the resources to support the project. For me, this shows the maturity of the civic analytics field. We’re no longer pioneers blazing a trail but are instead starting to walk clearer paths of best practice we can share with others.
- Innovation isn’t just a big-city phenomenon. There is great work being done in the large metropolitan areas of this country where there is the concentration of people and resources that make this work particularly impactful. There are also some really innovative projects being done in places without the size, density, and complexity of places like New York, Chicago, or Boston. South Bend is bringing transparency to its police department. Louisville, KY is leading the way in how municipalities can make the most of Waze data. Pittsburgh and it’s surrounding municipalities are defining multi-agency data collaboration. Everyone has something to contribute to the civic analytics conversation and there are times the most experienced and well-resourced municipalities can be a student to the lessons smaller municipalities have to teach.
I leave the conference with two main intentions going forward:
- I need to better develop my training materials for municipalities wanting to launch their own training. There are some great resources out there (Data SF’s Academy and WPRDC’s Data 101), but the excited reactions I got when I mentioned the materials I had online have me convinced there’s value in what I’m producing.
- I want to develop and distribute the lessons and strategies I’ve identified in my work collaboratively developing data science projects. Look for some blogposts in the near future, but in the meantime, checkout some of the training materials we’ve been developing for our classes with managers in New York City.
Thanks to the Civic Analytics Network for all the hard work making this happen and opening up key lessons for everyone to learn.