Smart Governance is related to the future of public services by using technology to facilitate and support better planning and decision making systems. Therefore, access to meaningful data is a core demand and indispensable part of a smart governance to improve service delivery and citizens’ quality of live.
Four elements might be more critical than the others as an indicator of a smart government; i) participation in decision making mechanisms, ii) public & social services, iii) transparency in governance iv) political strategies & perspectives. All of those indicators can provide more considerable outputs if there is available of a superior data governance system.
Smart governance improves democratic processes and transforms the ways that public services are delivered, but increasing complexity and volume of data in cities as they are getting smarter create a necessity of comprehensive governance plans to understand the usefulness of data in a better way.
Data & data analytics are the most critical elements to be able to understand what is going on in your city or anywhere in the world, and they are the base of all smart governance activities. According to IBM, there are six main elements to build up a strong data governance system;Step 1: Set and communicate goals: Goals should be specific, measurable and directly tied to either success of the business or possible processes to help the business for achievement. Creating situational goals policy-specific based on measurable deficiency (e.g. achieving 80% data quality, but KPI is 90%) , and sustainable goals the program expects to achieve (e.g. reducing the number of customer complaints by 20%) is the first step.
Step 2: Define your metrics: Without careful metrics, it is too difficult to analyze whether your program is achieving its goals. Key Performance Indicators (KPIs) are key and synthesized from performance indicators built from indicators. Indicators are raw data collected from your information supply chain and they do not have an integrated meaning without putting them into a sentence. However, KPIs show the trends of change as well as the ups and downs of performance indicators as they fluctuate over time. Therefore, we use “Variance” often as one of the main KPIs in many sectors.
- Indicator 1: Key ; Indicator 2: Performance ; Indicator 3: Indicators
- Performance Indicator (Integrated meaning): Key + Performance + Indicators
- KPI: Trends of change over time (ups and downs)
Step 3: Define how decisions will be made: You need metrics about the decision making process that you can analyze to plan your next move. Who participates in the decision (a council consultation, citizen participation, delegated authority, etc.), how metrics were used to justify the decision and how information was analyzed are important key decision indicators (KDIs).
Let’s make it a little simpler up to now with an example;
In 2008, the German government started an innovative project in Cologne to allow citizen participation into the budget making process of 2008/2009 by submitting their own funding proposals. As a reminder, Cologne has one million residents, nine municipalities and c.€4bn budget in total. The first concentration of this e-participation process was on three topics including a participatory budget of €311m (c.7.8%) in total: i) Street paths, ii) open areas, and iii) green spaces & sports. So, the target group -citizens- was encouraged to provide their contributions through internet and all suggestions were published publicly.
Top 100 suggestions in each area were selected mainly through a user friendly interactive web site (85%) along with e-mails (2%), call-center (4%) and written forms (9%); commented by technical administration and a total of top 300 citizen opinions over 4,937 suggestions were shared with the city council to look into further.
In this way, the government informed the citizens comprehensively about the budget; made them aware of the participatory power of citizens; created more transparency in municipal executions by responding after a common decision making mechanism, and finally, enriched the budget conversations by the contributions and expectations of citizens.
Step 4: Communicate your policies: Regardless of the political models used to set city policies, city administrations should communicate their policies effectively. Even, great policies do not work if you do not communicate them in a good way. In cologne case, internet platform was the most effective instrument. The local authorities put their vision clearly to be able to get the citizens’ contributions. For the municipality council in cologne case, the results of a good communication were 4,937 suggestions, more than 9,000 comments on the suggestions, c.873k web page interaction, 40,891 positive votes, 11,855 negative votes, 498 pages of council report synthesized from all those feedbacks and €8.2m worth of measures as a result of all those communication efforts bringing about more contentment and a happier community via a new generation Public-People Joint Participation.
Step 5: Measure your outcomes: It is key to measure data quality, refine meaningful results, monitor failures and observe benchmarks in advance to improve the future of performance on the data delivery of today.
When we examine the historical citywide crime complaint data (2000-2015) of New York Police Department (NYPD), it is admirable to see that there is a significant decrease over time in all crime types from simple violation offenses to felony. According to some New York Times articles and similar other ones, crime levels have been falling even during the economic crisis, but what’s interesting about this is that crime generally rises during economic recessions, not goes down.
An audit report of crime practices indicated that precinct captains were rewarded due to lower crime rates. Furthermore, they invented new creative practices to indicate crime rates lower. For example, they persuaded victims not to complaint about their victimizations or they reported stolen goods based on looking up the values of used goods on Ebay web site.
The reasons are varied, but in interviews, dozens of police officers said out of being too busy to report that there is a departmental pressure to keep the statistics low.
Even the management of police forces did really not know what they achieved was somehow distorted as a result of new kind of data corruption. Therefore, data quality is very important to measure your outcomes. There should be some data quality monitoring processes and critical event observations. KPIs should be aligned with your outcomes, and variances should be analyzed carefully. We never forget that governance is a process, not an end or a state.
Step 6: Audit: Every part of the governance process should be audited, but it is better to perform it all the time instead of periodical checking. Over time, you will have a historical archive of errors and fix all of them in a more efficient way not to face with same problems again. Therefore, efficient and smart documentation might be useful to discover what went wrong in the past when you look back later.
- Smart Cities: Big Cities, Complex Governance?, “Manuel Pedro Rodríguez Bolívar, 2015”
- Factors and indicators Smart Governance, “smart-cities.eu”
- Definition of Smart Cities “collinsdictionary.com”
- Smart Governance, Politics in the Policy Process in Andhra Pradesh, India, “Jos Mooij”
- Smart Governance: A Roadmap for Research and Practice, “Hans J. Scholl and Margit C. Scholl, 2014”
- Smart governance and technology, “PwC India, 2013”
- Cologne, the participatory budget, “E-government and Online services, Cologne”
- Six easy steps for smart governance, “IBM, June 2010”
- Historical New York City Crime Data, “nyc.gov”
- Police Tactic: Keeping Crime Reports Off the Books, “NY Times”