Page | 1     Design Thinking PS-2017 

 Reflection – Visualization 

 Challenge : 

 Urbanization is becoming a major challenge ; the United Nations recently projected that 1.1 billion people   will be added to cities between 2017 to 2030 . Cities in Asia , in particular , are experiencing enormous   social , economic and environmental change ; forming the largest and fastest growing consumers of   materials and energy , producers of waste and emitters of greenhouse gasses ( GHG ) . 

 In 2007 , mega - cities were already experiencing a multitude of challenges including congestion ,   environmental destruction and a significant rise in emissions . The scale of future development required   urgent prioritization of build programs that integrated efficiency goals . 

 At the time , I was working with a large infrastructure planning consultancy based out of the United   Kingdom and an opportunity was created to support emerging secondary cities in India on low - carbon   development . We were tasked to conceptualize an alternative growth plan ; to develop a toolkit of   solutions to aid urban local bodies in better planning their long - term future . 

 Selection : 

 Every locations challenge are unique and low - carbon design needs to be tailored to local requirements .   During a brain storming exercise with stakeholders , we identified that one of the major barriers to future   planning is that city departments worked in silos and followed independent objectives .   We were keen to   introduce the concept that city departments needed to be collaborative and integrative in meeting the   long - term objectives of emission reduction . As a focus on better design , it was important to understand   that city level choice made today on land planning , building and neighborhood design , waste   management , water , and energy would have long term implications . 

 Angel Sanders mentioned in her talk that the beauty of using a visualization tool is that we can tap into a   single picture .   The more likely you are to achieve a sense of agreement and consensus with people ,   the more you are likely to draw out conversation . 

 Over half of GHG emission reduction can be achieved through better design in land - use planning ,   efficient buildings , transportation , and energy use . The cross - disciplinary nature of emissions reduction   required active participation across the city - departments , and visualization was seen as a powerful tool to   communicate this message . 

 The chosen approach was to resurrect a shelved carbon master - planning tool ; conceptualized for use in   the United Kingdom to map GHG emission in future development . The tool had two key capabilities : firstly   the ability to create a 3D visualization of design models for a city , and secondly , it estimated the GHG   emissions for each plan . The aim was to present three scenarios of urban masterplans to a diverse   audience and to unlock a subsequent debate on delivering the best design : 

 I. Base scenario : A masterplan of the existing city and estimated GHG emissions    II . 2030 plan scenario : A future city masterplan with existing policy and regulations    III . 2030 low - carbon plan scenario : A masterplan with revised low - carbon design , policy and 

 regulations 

 By presenting two future scenarios , the objective was to introduce the potential reduction in GHG   emissions through better design through cross - cutting solutions ; such as the closer relationship between   transportation , housing , and energy . 

 Application : 

 The city we were working with had a population of around 1million residents and was in the process of   launching a new city master - plan to cater to rapid growth over the next 20 years .   We began a dialogue   with the City authorities as a two stage process : 

    Stage 1 : Involved a data gathering exercise in - order to adapt the master - planning tool to the needs   of the city . The data was gathered through preliminary discussions with individual city stakeholders   to customize the tool to the city . In line with Whatis stage of Design thinking 

    Stage 2 : Using the master - planning tool to develop 3D visualization models of the three scenarios   and estimating the GHG emissions for each . In line Whatif stage of Design thinking 

 At Stage 1 , there was a major challenge in collecting data for the tool as a large proportion of the   information had never been monitored and measured before . We were forced to use assumptions that   required creative estimation ; it echoed Roberto Fink “ Poppycock ” descriptor on the barriers of traditional 

 Page | 2     Design Thinking PS-2017 

 thinking : Data from a known passed to apply into connecting an unknown future ( Ref : Week 4 : Learning   launch tool ) . However , in this case , we were not preparing a business plan but using logical references to   adapt the model to estimate GHG emissions in India . Fortunately , the focus was not on accuracy , but   rather to communicate a realistic impact of what different design choices could have on emissions and   present it in a relatable 3D visualization similar to google maps . 

 Insight : 

 City governance in India had typically had a hierarchical reporting structure with individual departments   not - necessarily communicating with each other . Many department heads had never met or discussed   joint opportunities . By applying the 3D models of the City as a visualization tool , the stakeholders were   able to quickly grasp a common understanding of good - design and the potential impact on GHG   emissions . Each city stakeholder was able to draw on the key link of where their department contributed   to the overall city GHG emissions and opened the need to work collaboratively to find common solutions . 

 The workshop was revolutionary to a traditionally hierarchical governance , as it brought a round - table   participation where every stakeholder had a say . Stakeholders wanted to immediately apply their new- found understanding of low - carbon design on a live project and began exploring the challenges and   barriers of delivering a model low - carbon neighborhood . Every member had a say as no longer was the   design driven by the “ highest paid ” or senior member . As they strived to “ prototype ” the ideal   neighborhood , many innovative solutions began to arise across departments . One such example was the   operations team collaborating with road designers to refine plans to better capture ground water ; thereby   hydrating green pathways through a cost - effective and energy efficient outcome . 

 Although unconventional , this reflection was one of the best career examples in capturing some of the   early capabilities of “ design thinking ” . Beyond just the visualization , the stakeholders consisted of a mix of   engineers , planners , and administrators , which brought together a diverse perspective to low - carbon   development . 

 There was mutual learning as there was not a single solution applicable to all departments but iterative   changes needed in each practice to ensure an overall improvement for the city . We all walked away   learning something new , as consultants , we had a more realistic understanding of the challenges of   delivering efficient design in India . 

 Approach : 

 Jeanne introduced early in the course that “ innovation often involved borrowing something from   somewhere else . Another industry , your own past , or else recombining things that already exist ” .   This reflection encompassed the repurposing of an existing visualization tool to break down creative   barriers within an organization ( city government ) and unlock innovative low - carbon solutions . The   Design thinking course has aligned a better understanding of the overall horizon of unpacking innovation .   The complexity of cities and human - centric nature makes it the ideal for future design thinking . 

 The Carbon master - planning tool was appropriate as a visualization but was ineffective in creating a final   live solution for the City as it was “ static ” in nature and lacked feedback from consumers . In the future   “ Smart City ” strategies are leading to a revolution in digital transformation ; to better understand the   complex relationship between communities and their citizens ( and customers ) . For low - carbon and   efficiency solutions this would lead to a faster approach to realizing the WhatWOW ’s ; through learning   launches of efficiency solutions and high - quality feedback . 

 Terms : 

    Greenhouse Gases : Greenhouse gasses are responsible for the greenhouse effect , which ultimately leads to global warming   and climate change . Carbon dioxide forms almost 2/3rd ’s of the total global greenhouse gas emissions . 

    Low - carbon Development : Development focused on low carbon sources that minimize the output of greenhouse gas ( GHG )   emissions into the biosphere .   The main sources of carbon emissions within cities are transportation , commercial / residential ,   industry and land - use change . 

    Master - plan / Master - Planning : A master plan is a blueprint for the future . It is a comprehensive document , long - range in its   view , that is intended to guide development in the city / township for the next 10 to 20 years . 

    City - Administration / Urban - Governance / Departments / Stakeholders : A broad description of the administration and technical   teams tasked with planning , development , and operations of a city . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: Page | 1     Design Thinking PS-2017 

 Reflection – Visualization 

 Challenge : 

 Urbanization is becoming a major challenge ; the United Nations recently projected that 1.1 billion people   will be added to cities between 2017 to 2030 . Cities in Asia , in particular , are experiencing enormous   social , economic and environmental change ; forming the largest and fastest growing consumers of   materials and energy , producers of waste and emitters of greenhouse gasses ( GHG ) . 

 In 2007 , mega - cities were already experiencing a multitude of challenges including congestion ,   environmental destruction and a significant rise in emissions . The scale of future development required   urgent prioritization of build programs that integrated efficiency goals . 

 At the time , I was working with a large infrastructure planning consultancy based out of the United   Kingdom and an opportunity was created to support emerging secondary cities in India on low - carbon   development . We were tasked to conceptualize an alternative growth plan ; to develop a toolkit of   solutions to aid urban local bodies in better planning their long - term future . 

 Selection : 

 Every locations challenge are unique and low - carbon design needs to be tailored to local requirements .   During a brain storming exercise with stakeholders , we identified that one of the major barriers to future   planning is that city departments worked in silos and followed independent objectives .   We were keen to   introduce the concept that city departments needed to be collaborative and integrative in meeting the   long - term objectives of emission reduction . As a focus on better design , it was important to understand   that city level choice made today on land planning , building and neighborhood design , waste   management , water , and energy would have long term implications . 

 Angel Sanders mentioned in her talk that the beauty of using a visualization tool is that we can tap into a   single picture .   The more likely you are to achieve a sense of agreement and consensus with people ,   the more you are likely to draw out conversation . 

 Over half of GHG emission reduction can be achieved through better design in land - use planning ,   efficient buildings , transportation , and energy use . The cross - disciplinary nature of emissions reduction   required active participation across the city - departments , and visualization was seen as a powerful tool to   communicate this message . 

 The chosen approach was to resurrect a shelved carbon master - planning tool ; conceptualized for use in   the United Kingdom to map GHG emission in future development . The tool had two key capabilities : firstly   the ability to create a 3D visualization of design models for a city , and secondly , it estimated the GHG   emissions for each plan . The aim was to present three scenarios of urban masterplans to a diverse   audience and to unlock a subsequent debate on delivering the best design : 

 I. Base scenario : A masterplan of the existing city and estimated GHG emissions    II . 2030 plan scenario : A future city masterplan with existing policy and regulations    III . 2030 low - carbon plan scenario : A masterplan with revised low - carbon design , policy and 

 regulations 

 By presenting two future scenarios , the objective was to introduce the potential reduction in GHG   emissions through better design through cross - cutting solutions ; such as the closer relationship between   transportation , housing , and energy . 

 Application : 

 The city we were working with had a population of around 1million residents and was in the process of   launching a new city master - plan to cater to rapid growth over the next 20 years .   We began a dialogue   with the City authorities as a two stage process : 

    Stage 1 : Involved a data gathering exercise in - order to adapt the master - planning tool to the needs   of the city . The data was gathered through preliminary discussions with individual city stakeholders   to customize the tool to the city . In line with Whatis stage of Design thinking 

    Stage 2 : Using the master - planning tool to develop 3D visualization models of the three scenarios   and estimating the GHG emissions for each . In line Whatif stage of Design thinking 

 At Stage 1 , there was a major challenge in collecting data for the tool as a large proportion of the   information had never been monitored and measured before . We were forced to use assumptions that   required creative estimation ; it echoed Roberto Fink “ Poppycock ” descriptor on the barriers of traditional 

 Page | 2     Design Thinking PS-2017 

 thinking : Data from a known passed to apply into connecting an unknown future ( Ref : Week 4 : Learning   launch tool ) . However , in this case , we were not preparing a business plan but using logical references to   adapt the model to estimate GHG emissions in India . Fortunately , the focus was not on accuracy , but   rather to communicate a realistic impact of what different design choices could have on emissions and   present it in a relatable 3D visualization similar to google maps . 

 Insight : 

 City governance in India had typically had a hierarchical reporting structure with individual departments   not - necessarily communicating with each other . Many department heads had never met or discussed   joint opportunities . By applying the 3D models of the City as a visualization tool , the stakeholders were   able to quickly grasp a common understanding of good - design and the potential impact on GHG   emissions . Each city stakeholder was able to draw on the key link of where their department contributed   to the overall city GHG emissions and opened the need to work collaboratively to find common solutions . 

 The workshop was revolutionary to a traditionally hierarchical governance , as it brought a round - table   participation where every stakeholder had a say . Stakeholders wanted to immediately apply their new- found understanding of low - carbon design on a live project and began exploring the challenges and   barriers of delivering a model low - carbon neighborhood . Every member had a say as no longer was the   design driven by the “ highest paid ” or senior member . As they strived to “ prototype ” the ideal   neighborhood , many innovative solutions began to arise across departments . One such example was the   operations team collaborating with road designers to refine plans to better capture ground water ; thereby   hydrating green pathways through a cost - effective and energy efficient outcome . 

 Although unconventional , this reflection was one of the best career examples in capturing some of the   early capabilities of “ design thinking ” . Beyond just the visualization , the stakeholders consisted of a mix of   engineers , planners , and administrators , which brought together a diverse perspective to low - carbon   development . 

 There was mutual learning as there was not a single solution applicable to all departments but iterative   changes needed in each practice to ensure an overall improvement for the city . We all walked away   learning something new , as consultants , we had a more realistic understanding of the challenges of   delivering efficient design in India . 

 Approach : 

 Jeanne introduced early in the course that “ innovation often involved borrowing something from   somewhere else . Another industry , your own past , or else recombining things that already exist ” .   This reflection encompassed the repurposing of an existing visualization tool to break down creative   barriers within an organization ( city government ) and unlock innovative low - carbon solutions . The   Design thinking course has aligned a better understanding of the overall horizon of unpacking innovation .   The complexity of cities and human - centric nature makes it the ideal for future design thinking . 

 The Carbon master - planning tool was appropriate as a visualization but was ineffective in creating a final   live solution for the City as it was “ static ” in nature and lacked feedback from consumers . In the future   “ Smart City ” strategies are leading to a revolution in digital transformation ; to better understand the   complex relationship between communities and their citizens ( and customers ) . For low - carbon and   efficiency solutions this would lead to a faster approach to realizing the WhatWOW ’s ; through learning   launches of efficiency solutions and high - quality feedback . 

 Terms : 

    Greenhouse Gases : Greenhouse gasses are responsible for the greenhouse effect , which ultimately leads to global warming   and climate change . Carbon dioxide forms almost 2/3rd ’s of the total global greenhouse gas emissions . 

    Low - carbon Development : Development focused on low carbon sources that minimize the output of greenhouse gas ( GHG )   emissions into the biosphere .   The main sources of carbon emissions within cities are transportation , commercial / residential ,   industry and land - use change . 

    Master - plan / Master - Planning : A master plan is a blueprint for the future . It is a comprehensive document , long - range in its   view , that is intended to guide development in the city / township for the next 10 to 20 years . 

    City - Administration / Urban - Governance / Departments / Stakeholders : A broad description of the administration and technical   teams tasked with planning , development , and operations of a city .
### Output: 