Smarter Cities: Citizen Inclusion Citizen Collaboration & Social Media Analytics & Maturity Model Findings for Ljubljana Michele Leonardi, COO IBM Slovenia Big Data is the Next Great Natural Resource
IBM Intelligent Operations Center for Smarter Cities provides integrated insight Smarter Operations across departments and agencies Leverage information with real-time visibility of key data to drive better decisions Anticipate performance to identify, manage and mitigate incidents that impact operations Coordinate resources and processes to respond to situations rapidly and effectively IBM is clearly progressing its vision of supporting smarter-city endeavors with less customized and more reusable solutions. The Intelligent Operations Center is an important step in building a more repeatable offering for smarter cities. Gartner Group start within within a particular a particular service service area area or or managing across manage many across services services 2
Leverage data in the Cities : Collecting and analyzing data, while automating a collaborative response Events Incidents Incidents Events Events Events Incidents Data Insight Events / Incidents Leverage Information Anticipate problems through analytics Coordinate resources and response using actionable intelligence 3
Intelligent Operations in Cities New Ways to understand our Environment Data sources Connecting across multiple data sources for a single picture across the city Video Social Media Analytics Sensors Correlation Citizen Collaboration Mobil Phone Tracking Prediction 4
Social Media in the City citizens opinions and their involvement 2. Analysis the sentiment Citizen Collaboration Feeds 1. Connect to the sources 5 3. Make the information part of the situational awareness features and functions inside the IOC
Enabling socially responsible citizens Citizen Collaboration How it works Function As the general public go about their daily lives and encounter issues in their environment, they can use IOC for Citizen Collaboration to report these issues for resolution. Example 1. New issues appear in a public areas that could required attention 2. Citizens can report via a mobile / web based IOC application. 3. This information can be used to supply the office of public works with an additional input to their maintenance schedule. Mobile Reports Paving Stone 1. The general public can become proactive and report issues in their environment via MOBILE devices Garbage Graffiti 2. A traceable report can be sent to the city s 311 solution application Value The monitoring of an environment can utilize human observation and include this in an existing process 3. The IOC can help to manage the response 4. The issue is resolved and communicated back to the citizen 6
Maturity Model Findings 7
Initial Results Initial Results Ljubljana Region Level 1 Silo Level 2 Centralized Level 3 Partially Integrated Level 4 Multimodal Integrated Level 5 Multimodal Optimized strategic planning information creation capability Planning Performance Measurement Customer Data Collection Data Integration Analytics - Payment Methods Project - based Planning (single Defined metrics by mode Customer accounts managed separately for each system/mode Near for major routes Networked Periodic, Systematic analysis Automatic Cash Machines Integrated agency wide planning (single Limited integration across organizational silos Multi - channel account interaction per mode Real - time for major routes using multiple inputs Common user interface High - level analysis in near Electronic Payments Integrated corridor - based multimodal planning Shared multimodal system - wide metrics - Unified customer account across multiple modes Long term strategy & Integrated regional planning multimodal is planning clear and well documented Continuous system - Performance management wide performance against measurement the strategy is not Integrated strong multimodal incentives Urbana to optimize card multimodal use Real - time coverage for Within System mode - wide real data - is collected major corridors, all time data collection significant modes adequately across all modes and integrated internally 2 - way system Integration Extended integration externally between integration modes / organisations is lacking Reporting & Analytics (KPI Detailed analysis in Multi - modal analysis in reporting, simulation, prediction) is poor and infrequent Multimodal, multi - Multimodal integrated Tourist card Urbana card (but media (fare cards, fare card not cell covering phones, rail) etc) intervention capability Network Ops. Response Incident Demand Traveler Information - Centralized, Single Mode Manual detection, coordinated response, manual recovery Individual measures, with long term variability Static trip planning with limited alerts Automated, Single Mode Automatic detection, coordinated response and manual recovery Coordinated measures, with short term variability Multi - channel trip planning and account - based alert subscription Automated, Multimodal Automated pre - planned multimodal recovery plans Dynamic pricing Location - based, on - journey multimodal information Multimodal Real - time Optimized Operations within modes are good Dynamic multimodal Incident recovery plans response based is mainly silo on real based - time data Demand is only managed Multimodal dynamic with fares which are set on a pricing long term basis within silos Information Location - based, is silo based and multimodal not always proactive easy to find re - routing Multimodal Network Maturity Model version 1.1 Copyright IBM Corporation 2007 8
Benchmark Strengths Compared with Average Average Ljubljana Region Level 1 Silo Level 2 Centralized Level 3 Partially Integrated Level 4 Multimodal Integrated Level 5 Multimodal Optimized strategic planning Planning Performance Measurement Customer Data Collection Functional Area Planning (single Minimal Minimal capability, no customer accounts Limited or Manual Input Project - based Planning (single Defined metrics by mode Customer accounts managed separately for each system/mode Near for major routes Integrated agency wide planning (single Limited integration across organizational silos Multi - channel account interaction per mode Real - time for major routes using multiple inputs Integrated corridor - based multimodal planning Shared multimodal system - wide metrics - Real - time coverage for major corridors, all significant modes Integrated regional multimodal planning Continuous system - wide performance measurement Central Planning Policy Unified customer Integrated multimodal account across multiple incentives to optimize modes multimodal use System - wide real - time data collection across all modes information creation capability Data Integration Limited Networked Analytics Ad - hoc analysis Periodic, Systematic analysis Common user interface High - level analysis in near 2 - way system integration Detailed analysis in Extended integration Urbana Multi - modal analysis in Payment Methods Manual Cash Collection Automatic Cash Machines Electronic Payments Multimodal integrated fare card Multimodal, multi - media (fare cards, cell phones, etc) Network Ops. Response Ad - Hoc, Single Mode Centralized, Single Mode Automated, Single Mode Automated, Multimodal Multimodal Real - time Optimized intervention capability Incident Demand Manual detection, response and recovery Individual static measures Manual detection, coordinated response, manual recovery Individual measures, with long term variability Automatic detection, coordinated response and manual recovery Coordinated measures, with short term variability Automated pre - planned multimodal recovery plans Dynamic pricing Dynamic multimodal recovery plans based on data Multimodal dynamic pricing Traveler Information Static Information Static trip planning with limited alerts Multi - channel trip planning and account - based alert subscription Location - based, on - journey multimodal information Location - based, multimodal proactive re - routing Multimodal Network Maturity Model version 1.1 Copyright IBM Corporation 2007 9
Benchmarking Improvement Themes (compared with London) London Ljubljana Region Level 1 Silo Level 2 Centralized Level 3 Partially Integrated Level 4 Multimodal Integrated Level 5 Multimodal Optimized strategic planning Planning Performance Measurement Customer Data Collection Functional Area Planning (single Minimal Minimal capability, no customer accounts Limited or Manual Input Project - based Planning (single Defined metrics by mode Customer accounts managed separately for each system/mode Near for major routes Integrated agency wide planning (single Limited integration across organizational silos Multi - channel account interaction per mode Real - time for major routes using multiple inputs Integrated corridor - based multimodal planning Shared multimodal system - wide metrics - Unified customer account across multiple modes Real - time coverage for major corridors, all significant modes Integrated regional multimodal planning Tighter KPI & Contract by TfL Continuous system - wide performance measurement Integrated multimodal incentives to optimize multimodal use System - wide real - time data collection across all modes information creation capability Data Integration Limited Networked Analytics Ad - hoc analysis Periodic, Systematic analysis Common user interface High - level analysis in near 2 - way system integration Detailed analysis in Extended integration Oyster Multi - modal analysis in Payment Methods Manual Cash Collection Automatic Cash Machines Electronic Payments Multimodal integrated fare card Multimodal, multi - media (fare cards, cell phones, etc) Network Ops. Response Ad - Hoc, Single Mode Centralized, Single Mode Automated, Single Mode Automated, Multimodal Multimodal Real - time Optimized intervention capability Incident Demand Traveler Information Manual detection, response and recovery Individual static measures Static Information Manual detection, coordinated response, manual recovery Individual measures, with long term variability Static trip planning with limited alerts Automatic detection, coordinated response and manual recovery Coordinated measures, with short term variability Multi - channel trip planning and account - based alert subscription Automated pre - planned multimodal recovery plans Dynamic pricing Location - based, on - journey multimodal information Dynamic multimodal recovery plans based on data Integrated view of transport data and operational control by TfL Multimodal dynamic pricing Location - based, multimodal proactive re - routing Multimodal Network Maturity Model version 1.1 Copyright IBM Corporation 2007 10
Benchmarking Global Improvement Themes Best of Best Practices Ljubljana Region Level 1 Silo Level 2 Centralized Level 3 Partially Integrated Level 4 Multimodal Integrated Level 5 Multimodal Optimized strategic planning information creation capability Planning Performance Measurement Customer Data Collection Functional Area Planning (single Limited or Manual Input Project - based Planning (single Near for major routes Data Integration Limited Networked Analytics Minimal Ad - hoc analysis Cross mode reporting and KPI management Minimal capability, no customer accounts Cross mode data sharing and analytics Defined metrics by mode Customer accounts managed separately for each system/mode Periodic, Systematic analysis Integrated agency wide planning (single Limited integration across organizational silos Multi - channel account interaction per mode Real - time for major routes using multiple inputs Common user interface High - level analysis in near Integrated corridor - based multimodal planning Shared multimodal system - wide metrics - Unified customer account across multiple modes Real - time coverage for major corridors, all significant modes 2 - way system integration Detailed analysis in Integrated regional multimodal planning Continuous system - wide performance measurement Integrated multimodal incentives to optimize multimodal use System - wide real - time data collection across all modes Extended integration Multi - modal analysis in intervention capability Payment Methods Network Ops. Response Incident Demand Manual Cash Collection Ad - Hoc, Single Mode Manual detection, response and recovery Individual static measures Automatic Cash Machines Closer cross mode operations Centralized, Single Mode Manual detection, coordinated response, manual recovery Individual measures, with long term variability Electronic Payments Automated, Single Mode Automatic detection, coordinated response and manual recovery Coordinated measures, with short term variability Multimodal integrated fare card Automated, Multimodal Automated pre - planned multimodal recovery plans Dynamic pricing Multimodal, multi - media (fare cards, cell phones, etc) Multimodal Real - time Optimized Dynamic multimodal recovery plans based on data Multimodal dynamic pricing Traveler Information Static Information Static trip planning with limited alerts Multi - channel trip planning and account - based alert subscription Location - based, on - journey multimodal information Location - based, multimodal proactive re - routing Multimodal Network Maturity Model version 1.1 Copyright IBM Corporation 2007 11
Recommended Focus Areas For Ljubljana Region as-is National Fare Card Focus Areas Level 1 Silo Level 2 Centralized Level 3 Partially Integrated Level 4 Multimodal Integrated Level 5 Multimodal Optimized strategic planning information creation capability intervention capability Planning Performance Measurement Customer Data Collection Functional Area Planning (single Limited or Manual Input Project - based Planning (single Near for major routes Data Integration Limited Networked Analytics Payment Methods Network Ops. Response Incident Demand Traveler Information Minimal Minimal capability, no customer accounts Ad - hoc analysis Manual Cash Collection Ad - Hoc, Single Mode Manual detection, response and recovery Individual static measures Static Information Defined metrics by mode Customer accounts managed separately for each system/mode Periodic, Systematic analysis Automatic Cash Machines Centralized, Single Mode Manual detection, coordinated response, manual recovery Individual measures, with long term variability Static trip planning with limited alerts Integrated agency wide planning (single Limited integration across organizational silos Multi - channel account interaction per mode Real - time for major routes using multiple inputs Common user interface High - level analysis in near Electronic Payments Automated, Single Mode Automatic detection, coordinated response and manual recovery Coordinated measures, with short term variability Multi - channel trip planning and account - based alert subscription Integrated corridor - based multimodal planning Shared multimodal system - wide metrics - Unified customer account across multiple modes Real - time coverage for major corridors, all Focus on: significant modes 2 - way system integration Detailed analysis in Multimodal integrated fare card Automated, Multimodal Automated pre - planned multimodal recovery plans Dynamic pricing Location - based, on - journey multimodal information Integrated regional multimodal planning Focus on: More frequent cross mode KPI based reporting Continuous system - wide performance measurement Integrated multimodal incentives to optimize multimodal use System - wide real - time data collection across all modes Centralised cross mode data collection, analytics, and sharing of significant events Extended integration Multi - modal analysis in Multimodal, multi - media (fare cards, cell phones, etc) Focus on: Improving operations with better data and improved cross mode incident management Multimodal Real - time Optimized Dynamic multimodal recovery plans based on data Multimodal dynamic pricing Focus on: Improving traveller experience with easier access to better information Location - based, multimodal proactive re - routing Multimodal Network Maturity Model version 1.1 Copyright IBM Corporation 2007 12
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Intelligent Operations - How It works Key Process Indicators are monitored and managed to trigger actions Example: Real time monitoring of a bus environment Example: A transport dept is working hard to ensure bus arrivals time don t fall below 5 mins delay. 3 routes A,B & C run at a 6 mins delayed and are deemed by the operational KPIs engine to be yellow. The comments via Social media analytics is that there is no perceived issue on route A & B but the C route delay is unacceptable from a passages experience point of view. This means that the operational KPIs and Social media analytics KPIs are mismatched around the same item been monitored.. Insight comes from combining many sources of data! 14
Enabling socially responsible citizens Giving citizens a way to have active involvement... Improve the communication between cities and their citizens in the domain of non-emergency city matters Enhance citizens involvement in the city matters, and promote transparency in the communication with the citizen Enhance citizen engagement and satisfaction Increase city operational efficiency Help build city image as being modern and up to date with the latest technologies 15
Intelligent Operations Center (IOC) and sentiment analysis Understanding Citizen Sentiment on City Issues Backdrop A city is evaluating a permit request for a commercially sponsored festival that will disrupt general city operations, traffic, schools, access, noise etc. 1. A city is considering a commercially sponsored festival 2. They publish their plans to the general public Example Social media analytics is made part of a full communication and strategy plan. The event and the disruption that could be caused is posted on city wide web sites, twitter, etc.. Comments on the city s blog site is encouraged. A social media analytics capability will monitor different sources, twitter, blogs, traditional online media and RSS feeds to understand the level of acceptance of this initiative. It will also look for any negative sentiment that may point to anti social protesting. The city managers may wish to re-think the size and location of the festival based on this feedback. 16 3. IOC analyze s sentiment 4. Reconsider decisions and ensure all issues are addressed 5. Setup the IOC to manage the event
Intelligent Operations Center (IOC) and citizen collaboration Enabling socially responsible citizens 1. The general public can become proactive and report issues in their environment via MOBILE devices Backdrop As the general public goes about their daily lives and encounter issues in the city, they can use Intelligent Operations Center to report these issues for resolution. Mobile Reports Paving Stone Garbage Graffiti Example New graffiti appearing in a public area, broken facilities that could cause harm, broken paving stones, garbage in children's play ground, signage missing, etc. Citizens report via mobile Intelligent Operations Center connected application. This information can be used to supply the office of public works an additional input to their maintenance schedule. Using Intelligent Operations Center, this information can be combined with other information to help schedule, spot trends and optimize the response. 17 3. The IOC can help to manage the response 4. The issue is resolved and communicated back to citizen 2. A traceable report can be sent to the city s non emergency solution application
Intelligent Operations for Citizen Collaboration Intelligent Operations Center for citizen collaboration can improve communication between cities and their citizens in the domain of non-emergency city matters Background and Challenge Citizens are increasingly using only mobile devices; non emergency traditionally lacks support for mobile communications channels Need to augment existing systems, leverage mobile communications channels and provide a compelling user experience Provide cost effective, scalable solutions to improve citizen experience and city services Benefits: Improve the communication between cities and their citizens in the domain of nonemergency city matters Enhance citizens involvement in the city matters, and promote transparency in the communication with the citizen Enhance citizen engagement and satisfaction Increase city operational efficiency Help build city image as being modern and up to date with the latest technologies Use Case Scenario: Provide citizens tools to report a city problem via both Web and smart phone application Utilize tools to view on map service requests and city improvements Create personalized views of the city and subscribe for updates Support social features comments and votes Provide city workers tools to manage service requests including aggregation of identical service requests Provide city workers tools to publish city improvements Define communication preferences SMS, e-mail, Smart-phone push notifications Utilize GeoReport open standard for reporting and viewing service requests Integrate with IBM's Intelligent Operations Center (IOC) 18
Social Media Analytics supplies new sources of data to the Operational Center allowing deeper insight for more effective management of an environment Background and Challenge Operational information only tells an organization how well it is delivering its services from its own point of view. The power of the individual s / crowd s input can contribute to successfully managing an environment, but how do we do it? Benefits: Gives the operational users insight to how the stakeholders in the environmental perceived how well the solution is being delivered. Can spot social media trends that can define how the management of the environment is being perceived Can point to activities that may take place in the managed environment that the operational data sources are unaware off.. Use Case Scenario: A city is holding a large sporting event which will disrupt general city operations. The city wants to ensure that it understands the sentiment of the population towards this decision before it finalize it. The Social Media Analytics feature can start to show positive / negative sentiment towards the idea by analyzing social media forms. The event organizers can also analyze any protests that may be planned against this decision by analyzing social media forms. i.e planning anti social behavior. Once a better understanding on how the general public feels about the event, planning can be modified to take this into consideration. The social media forms will be continue to be analyzed to ensure the setup of the solution is inline with the general public wishes. 19
Generating insights to how well a solution or action is been received.. Social media analytical data can allow the IOC user to understand how well the end users is responding to the management of an environment. Can identify trends in end user s behavior before they become an issue for the operators of the environment being managed. Social media analytics aims to determine the attitude of a speaker or a writer with respect to some topic. This can be used to validate the effectiveness of the operational KPIs inside the IOC. Example: A transport dept is working hard to ensure bus arrivals time don t fall below 5 mins delay. 3 routes A,B & C run at a 6 mins delayed and are deemed by the operational KPIs engine to be yellow. The comments via Social media analytics is that there is no perceived issue on route A & B but the C route delay is unacceptable from a passages experience point of view. This means that the operational KPIs and Social media analytics KPIs are mismatched around the same item been monitored.. Insight comes from combining many sources of data! This is not our solution but look how seriously Gatorade takes Social media analytics http://www.youtube.com/watch?v=inrovee2v38 20
Enhance prosperity and attractiveness to business and citizens Urban Vitality Coordinate cross agency operations with business and citizen participation to drive economic prosperity and enhance citizen involvement City Services Resources & Operations Manage resources more effectively by understanding the complete situation. Coordinate across city departments and private sector to optimize efforts. Economic Integration Interact with local businesses to improve business opportunity and citizen services availability and convenience. Use offers to drive local commerce Transportation & Water Traffic and Transit Operations Predictive Insights and Responsive Operations to City, Business and Citizen operations, activities and environment Executive Dashboard Managing the pulse of the city Citizen Involvement Participation in community programs and awareness of opportunities Create interactive experiences and deliver information where its needed 21