Our government is the definition of a \u2018customer-centric\u2019 organization – replace customer with citizen. Therefore, finding ways to understand and engage citizens should be the foremost priority of the government. Therefore, crowdsourcing information from citizens, and more recently through sensors, provides a powerful opportunity for the government at large to provide better public services in response to its citizens\u2019 needs. Unfortunately, government is not known to have the \u2018best\u2019 technical or analytical talent. Therefore, governments have begun to \u2018open\u2019 their crowdsourced data to engage wider talent to analyze the massive amounts of data collected. Open data enables citizens to live their promise of participatory government, keep their government accountable, and design solutions that may improve their day-to-day.<\/p>\n
However, for open data initiatives to work, citizens need a significant amount of data to work with. One example of an organization that has this large amount data is a city\u2019s 311 \u2013 take, for example, NYC\u2019s 311 system that processes several thousands of transactions every day<\/a>.[1]<\/a><\/p>\n NYC311 provides the public access to various government services and information through a customer service model[2]<\/a> – it is a one-stop shop for managing non-emergency citizen calls. Citizen requests are routed to the appropriate government agency and documented in a citizen management system. NYC311 also includes in its mission statement: \u201chelp Agencies improve service delivery by allowing them to focus on their core missions and manage their workload efficiently\u201d in its mission statement[3]<\/a>. Opening up NYC311\u2019s data directly helps with that.<\/p>\n Opening up NYC311\u2019s data was the biggest innovation across local governments that we\u2019ve seen in the past decade. However, according to the former Chief Analytics Officers and Chief Technology Officers of NYC and Boston, respectively, long-standing impact by way of change in government agencies based on open data analysis are still in its early days. Three challenges stand out: (1) are there enough incentives for citizens to indeed analyze the data in a meaningful way?, (2) is the data that is \u2018opened\u2019 accessible in an easy and structured enough way for citizens to use the data?, (3) are government agencies connected enough to 311 to actively take into consideration the open data analysis?<\/p>\n The first challenge is mitigated in the short-term because of today\u2019s booming start-up and technology ecosystem. Software companies face active competition to showcase their value, young start-ups could use open data to gain publicity and credibility for their work. For example, Vizzuality<\/a> and Carto<\/a>, are both companies that have built decision-making dashboards for city government officials[4]<\/a> \u2013 a \u2018new\u2019 concept and a good marketing tool. Additionally, the rise of interest in data science and data analysis may provide new students the opportunity to test and develop their skills through open data. NYC Open Data hosted a citywide competition for compelling city projects built on open data sets to further incentivize citizen participation[5]<\/a>. In the short term, there seems to be enough talent that NYC can capitalize on, given the excitement around \u2018data science\u2019 and the lack of publicly available data sets for companies and people to experiment on. The second challenge is being improved upon more and more. As in-house technology teams see how data is being used, they are iterating on data formats, structures, and tools by which data is made accessible and updated. Finally, for Open 311 data to make long-standing impact, government agencies need to buy into the analysis and have the capacity to adopt changes based on it. Initial analysis and dashboards are good to help evidence the potential impact of data analysis. For NYC311 to be successful, they should continue to evangelize projects developed by open data and advocate for data literate leaders.<\/p>\n The long-term risk is that talent interested in analyzing open data may decrease as the tech \u2018hype\u2019 passes. It will be important for 311 to invest in in-house technology talent. Additionally, the types of analysis done on open data could become stale and frankly, unhelpful, unless NYC311 continues to improve upon the data that they collect \u2013 in terms of data diversity, depth, and accessibility.<\/p>\n Additionally, NYC311 needs to grapple with the hard questions, such as \u2013 is the data collected by 311 in any way biased by race, socioeconomic status, gender, ethnicity, or other subgroup? Propensity to complain or make a request often has historic ties to whether or not citizens believe in and trust their government. Any analysis upon this 311 data set \u2013 whether it\u2019s pure data stratification, insight generation, or machine learning, could perpetuate any biases[6]<\/a>.<\/p>\n NYC311 has made great strides in evidencing the power of data analysis and innovation within the government, through opening up its data. Now it needs to build capacity in-house and answer tough questions to solidify the long-term impacts of open innovation.<\/p>\n [1]<\/a> About NYC311, Our Data. https:\/\/www1.nyc.gov\/311\/our-data.page.\u00a0The Official Website of the City of New York.<\/span><\/p>\n [2]<\/a> About NYC311, Our Mission. https:\/\/www1.nyc.gov\/311\/our-mission.page.The Official Website of the City of New York.<\/span><\/p>\n [3]<\/a>\u00a0About NYC311, Our Mission. https:\/\/www1.nyc.gov\/311\/our-mission.page.The Official Website of the City of New York.<\/span><\/p>\n [4]<\/a>\u00a0Campbell-Dollaghan, Kelsey. NYC Gets a Dashboard. https:\/\/www.fastcompany.com\/3067091\/new-york-city-gets-a-dashboard. Fast Company (Jan 2017)<\/p>\n