Rebecca Litauer, Research Associate at Fraunhofer IAO, designed and implemented a workshop on the KPI of the project. The workshop was held on the 9th of July in Barcelona in the EIT headquarters. 

What was the workshop about?

The workshop consisted in the motivations for successful pilots, identification and discussion of pilot KPI as well as the planning of the next steps in order to gather the information and data needed to finalise the baseline descriptions. The workshop objectives were the following: 

  • Top goals and motivational aspects for a successful piloting 
  • Rank most important KPI for each city
  • Discuss data collection methods and alternative, rather unconventional ways of measuring Smart City KPI in the case of missing data

Workshop step-by-step

  • Task 1: to gather the top goals and motivational aspects of a successful pilot and sustainable continuation of the digital loading zones. 
  • Task 2: to discuss the current status and clustering of KPI by value creation for the city stakeholders. 
  • Task 3: to discuss questions of data collection methods and how the information can be retrieved in the case of no data being available within the project scope (in city-specific groups)

Workshop reasoning

Today, city KPI are widely used for monitoring and evaluating smart cities ecosystems. Creating value from data enables political and digital business outcomes, generating further insights. By developing a H-KPI framework in the context of this project, we aim to use a methodology that can assess technology and associated community benefits in smart cities in a more holistic manner. Smart cities are complex organisations, so this approach is more appropriate for them and is based on a set of baseline assumptions*: 

  • Each city has its own unique characteristics. The solution cannot be an “one size fits all” option that works across all different application fields and municipalities.
  • At a particular time, KPIs are determined to be “best fit.” As the community develops and technologies improve, the selected KPIs may need to be revised at a later time.
  • Every situation requires a different set of KPIs. When choosing KPIs, multiple pros and cons must be weighed against one another. 

*Serrano, M., Griffor, E., Wollman, D., Dunaway, M., Burns, M., Rhee, S., & Greer, C. (2022). Smart Cities and Communities: A Key Performance Indicators Framework. NIST Special Publication, 1900, 206.

Workshop results

The workshop results show that across all cities, operational goals tend to be of a high interest. In particular, decreasing illegal parking while increasing parking rotations and therefore reducing traffic congestion stand out as goals, motivated by the creation of controllable parking zones and an increase of inner-city environmental health respectively. Goals following up are regaining public space and using it more efficiently through better and more regulated policing, and an overall better overview of local parking space usage and city planning through the collection of better and more reliable data.

  • The results of Paris and Argenteuil show a higher focus on KPI across all types, with a reduction of pollutants emissions, a higher turnover and wider availability of parking spaces, and a high satisfaction rate from stakeholders sharing the same level of priority. The top KPI to focus on are: 
    • A reduction of illegal parking
    • Number of vehicle types over time
    • An increase of average parking rotation in the area over time
    • An increase of the availability of loading spaces over time
    • An improvement of perceived liveability in the area
  • The results of Ankara show a clear prioritization of operational KPI. The top KPI to focus on are: 
    • The availability of loading spaces 
    • The acceptance of their clients and stakeholders
  • The city of Vic tends to focus on all operational and social KPI. The top KPI to focus on are: 
    • Availability of parking spaces
    • Reduction of illegal parking
    • Higher turnover rate for parking spaces
    • An increase of vehicle types share the highest priority
    • A higher perceived liveability of the affected area

What’s next?

The next steps are the finalisation of the data collections methods: 

  1. Final city’s KPI definition 
  2. Data collection methods design
  3. Data collection
  4. Baseline set up 
  5. Data analysis