Mind Mapping for more effective Innovation - a Reflection     Challenge     I work for a technology services company and am responsible for rolling out innovative new   Digital services and offerings , to be delivered by internal teams as well as external partners .   Over the last 18 + months , in the AI & Data Science space , we have been struggling with   getting enough engagement and feedback from our market facing teams , i.e. Sales , Account   Management and Solutioning teams , to make our offerings both innovative and relevant to   the market . We ’ve been trying to follow the Learning Launch process , but found ourselves   unable to get to grips with clients ’ unstated needs , which is critical in an emerging   technology space – when we did ideation sessions with our market facing teams , we found   ourselves falling prey to one of the following : 

 -   ‘ Google’itis – where the ideas generated were based on basic web research and   hence neither deep nor innovative . 

 -   Subject to HiPO bias – the Highest Paid Opinion would win over others , and in   addition this would often insist on killing other ideas ‘ because these will not scale ’ 

 -   Repeating what we had done for a client elsewhere , so that cookie - cutter ideas   predominated , regardless of whether these were relevant for other industries and   clients 

 It was clear that if we had to succeed , we needed to change the way we did ideation and   came up with Use Cases around which we build our solutions .      Selection     Mind Mapping would be at the heart of the new approach , as I felt that our usual   structured approach to creating business cases has been failing to capture the potential and   possibilities of an emerging technology area – we needed to find a way to allow for   exploration , but in a manner that led to concrete outputs based on data , rather than pie - in- the - sky ideas .      Application     In the last few weeks , we have rolled out a revised methodology with the following key   features : 

 -   Ideation sessions to always be in - person , for maximum engagement , in workshop   mode 

 -   The kickoff sessions would always present data from primary and secondary   research , with actual clients and prospects . ( Refinement … ) As well as substantial   amounts of content from experts in the relevant technologies/ tools to ensure that   the potential of these was fully understood 

 -   Most important , we adopted Mind Mapping techniques to flesh out the personas/   wants/ key success criteria of key stakeholders and buyers in our target industries   and enterprises – building these out on the basis of the research data , best practices   and stories from our partners and technology experts and conversations with key 

 clients and prospects . These have helped us uncover and refine * real * business   problems and opportunities , eliminate guesswork and kill lazy rehashing of what   someone read on the web or what was done elsewhere . 

 -   In addition , we also implemented other ideation techniques like silent ideation ( for a   fixed amount of time ) , after which each person came up and presented their ideas   with one per sticky note , with others discarding any duplicates . Each person also had   to attach their sticky notes to the relevant Mind Map on the board , with a brief   verbal explanation of how it was relevant , why it met a clear need/ opportunity and   who would be the target beneficiary/ buyer for this service/ offering . 

 Insight     This has helped us achieve the following : 

 -   Use Cases are now based on data , real feedback and insights from clients and   prospects 

 -   Our services and offerings are now targeted at specific personas , addressing deep   needs and opportunities , with differentiated solutions that have already started to   change the tone of our conversation with clients 

 -   A much higher level of engagement from our market facing teams , as they have a   deeper understanding of the potential solutions and are energized by their market   potential 

 We are now rolling this methodology out for all our innovation workshops , where Mind   Mapping is central , but is also always based on rigorous research and data gathering   prior to the workshop session . It has also thrown up lacunae in this process of research –   in the past we have had major successes in innovation projects with field observation   using ethnographic methods , but this has not been rolled out as a consistent set of   practices , with the result that the quality of research and data on user behaviour and   needs varies from project to project . We are now addressing this as a critical area , so   that the Mind Mapping process and subsequent ideation is based on a more solid data   foundation .   And some of the market leading companies in the Data Science space ,   having participated in some of our workshop sessions , are now rolling out this   methodology to all their other partners ! 


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: Mind Mapping for more effective Innovation - a Reflection     Challenge     I work for a technology services company and am responsible for rolling out innovative new   Digital services and offerings , to be delivered by internal teams as well as external partners .   Over the last 18 + months , in the AI & Data Science space , we have been struggling with   getting enough engagement and feedback from our market facing teams , i.e. Sales , Account   Management and Solutioning teams , to make our offerings both innovative and relevant to   the market . We ’ve been trying to follow the Learning Launch process , but found ourselves   unable to get to grips with clients ’ unstated needs , which is critical in an emerging   technology space – when we did ideation sessions with our market facing teams , we found   ourselves falling prey to one of the following : 

 -   ‘ Google’itis – where the ideas generated were based on basic web research and   hence neither deep nor innovative . 

 -   Subject to HiPO bias – the Highest Paid Opinion would win over others , and in   addition this would often insist on killing other ideas ‘ because these will not scale ’ 

 -   Repeating what we had done for a client elsewhere , so that cookie - cutter ideas   predominated , regardless of whether these were relevant for other industries and   clients 

 It was clear that if we had to succeed , we needed to change the way we did ideation and   came up with Use Cases around which we build our solutions .      Selection     Mind Mapping would be at the heart of the new approach , as I felt that our usual   structured approach to creating business cases has been failing to capture the potential and   possibilities of an emerging technology area – we needed to find a way to allow for   exploration , but in a manner that led to concrete outputs based on data , rather than pie - in- the - sky ideas .      Application     In the last few weeks , we have rolled out a revised methodology with the following key   features : 

 -   Ideation sessions to always be in - person , for maximum engagement , in workshop   mode 

 -   The kickoff sessions would always present data from primary and secondary   research , with actual clients and prospects . ( Refinement … ) As well as substantial   amounts of content from experts in the relevant technologies/ tools to ensure that   the potential of these was fully understood 

 -   Most important , we adopted Mind Mapping techniques to flesh out the personas/   wants/ key success criteria of key stakeholders and buyers in our target industries   and enterprises – building these out on the basis of the research data , best practices   and stories from our partners and technology experts and conversations with key 

 clients and prospects . These have helped us uncover and refine * real * business   problems and opportunities , eliminate guesswork and kill lazy rehashing of what   someone read on the web or what was done elsewhere . 

 -   In addition , we also implemented other ideation techniques like silent ideation ( for a   fixed amount of time ) , after which each person came up and presented their ideas   with one per sticky note , with others discarding any duplicates . Each person also had   to attach their sticky notes to the relevant Mind Map on the board , with a brief   verbal explanation of how it was relevant , why it met a clear need/ opportunity and   who would be the target beneficiary/ buyer for this service/ offering . 

 Insight     This has helped us achieve the following : 

 -   Use Cases are now based on data , real feedback and insights from clients and   prospects 

 -   Our services and offerings are now targeted at specific personas , addressing deep   needs and opportunities , with differentiated solutions that have already started to   change the tone of our conversation with clients 

 -   A much higher level of engagement from our market facing teams , as they have a   deeper understanding of the potential solutions and are energized by their market   potential 

 We are now rolling this methodology out for all our innovation workshops , where Mind   Mapping is central , but is also always based on rigorous research and data gathering   prior to the workshop session . It has also thrown up lacunae in this process of research –   in the past we have had major successes in innovation projects with field observation   using ethnographic methods , but this has not been rolled out as a consistent set of   practices , with the result that the quality of research and data on user behaviour and   needs varies from project to project . We are now addressing this as a critical area , so   that the Mind Mapping process and subsequent ideation is based on a more solid data   foundation .   And some of the market leading companies in the Data Science space ,   having participated in some of our workshop sessions , are now rolling out this   methodology to all their other partners !
### Output: 