Reflection - Learning Launch 

 Olivier Saidi 

 Challenge 

 I was leading a project to build and implement “ Technology Competency Framework ” for my   organization ’s large software programmers ’ pool of 0 to 4 years of experience in the company . We have   identified 6 different Lines of Technologies ( LOTs ) which are prevailing for the business to categorize the   target population within . I wanted each LOT to have definite curriculum and associated evaluation at 3   different levels ( L1 , L2 , L3 ) with increasing expertise and complexity to enable employees gain higher skills   and competencies as they progress year - on - year . We also wanted to map this framework to employees ’   career progression within the organization , so it was far more important to have an accurate technology   competency framework in place . Especially “ Evaluation ” mechanism at every L1 , L2 , L3 levels for all LOTs . 

 Employee evaluation framework was decided to be thru ’ online assessments in every LOT , based on the   curriculum set for every level ( L1 , L2 , L3 ) . Online assessment was to be using variety of Multiple Choice   Questions ( MCQs ) of low , medium , high complexities in each level ’s assessment . Sizable question bank   was generated and uploaded in the assessment engine . Parameters like Questions ’ complexity ,   randomization , points for correct answers , passing percentage have been configured in the assessment   engine . 

 Selection 

 Overall Evaluation model was conceptualized as stated above and validated to proceed with . Now the   most crucial part of the evaluation framework was ahead of us to establish its authentic workability . For   which “ Calibrating the Assessments ” was essential , i.e. to ensure that these assessments at each level   would produce the results which are in line with employees ’ actual skill levels . For example , when   employee is certified at Level 2 post the assessment , in reality , he / she is indeed at the skill / competency   Level 2 and not at 1 or 3 . For this , I ’ve decided to apply “ Learning Launch ” of design thinking . 

 Application 

 Selected a group of participants from the target audience and after imparting the necessary training to   them from their respective LOTs asked them to take the online assessments . Then their assessment results   were compared against their professional academic scores when they joined the organization , the scores   they have got in various relevant trainings they underwent after joining the organization and also against   the ratings they used to get on their technical skills and expertise by their supervisors during half yearly   and yearly appraisal process . Control graphs were plotted and cases falling outside of control limits were   analyzed . Initially we found higher numbers out of control limits . Then we adjusted the parameters in the   assessment engine and also modified the question bank repository . 

 This cycle was repeated 2 - 3 times with different set of employees to finetune the assessment mechanism   and calibrate the assessments till the cases falling out of control limits were minimal and our solution   became authentic and workable for the organization wide implementation . 

 Insight 

 “ Learning Launch ” tool turned out to be highly effective in this piece of our project . It was crucial and   most challenging work piece of the overall project and if we would have directly implemented the   framework across the organization , without having tested its accurate workability on smaller groups ,   2 - 3   times , the entire initiative would have been a flop show . Learning Launch tool helped us to 

 -   ensure solution workability in a shorter time ,    -   making us take fast corrective actions to calibrate the assessments ,    -   minimal but direct involvement of the end users of varied samples covering the larger spectrum of   technologies and levels    -   and most of all , with very minimal efforts , it enhanced our ( project team ) , sponsor ’s and key   stakeholders ’ confidence as to whatever solution / framework we are providing is the top notched   realistic solution for the benefit of the entire organization and target population . 

 Approach 

 I think , every tool has its own pros & cons . Not every tool will help or provide same benefits in different   challenges . According to me , “ Learning Launch ” is the better one to ensure the workability of the solution , 

 -   when there are multiple unknown factors involved in the new initiative ,    -   when there is no previous data available to cross verify the practicality of the solution ,   -   the volume of impacted population is high or very high   -   implementation cost is high or very high 

 If your challenge does n’t involve any of the aforesaid factors , then the risk of direct big - bang   implementation is comparatively less and that risk you can mitigate by analyzing the past data and trends   from the similar challenges and decide the course of action on your challenge . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: Olivier Saidi
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: Reflection - Learning Launch 

 Olivier Saidi 

 Challenge 

 I was leading a project to build and implement “ Technology Competency Framework ” for my   organization ’s large software programmers ’ pool of 0 to 4 years of experience in the company . We have   identified 6 different Lines of Technologies ( LOTs ) which are prevailing for the business to categorize the   target population within . I wanted each LOT to have definite curriculum and associated evaluation at 3   different levels ( L1 , L2 , L3 ) with increasing expertise and complexity to enable employees gain higher skills   and competencies as they progress year - on - year . We also wanted to map this framework to employees ’   career progression within the organization , so it was far more important to have an accurate technology   competency framework in place . Especially “ Evaluation ” mechanism at every L1 , L2 , L3 levels for all LOTs . 

 Employee evaluation framework was decided to be thru ’ online assessments in every LOT , based on the   curriculum set for every level ( L1 , L2 , L3 ) . Online assessment was to be using variety of Multiple Choice   Questions ( MCQs ) of low , medium , high complexities in each level ’s assessment . Sizable question bank   was generated and uploaded in the assessment engine . Parameters like Questions ’ complexity ,   randomization , points for correct answers , passing percentage have been configured in the assessment   engine . 

 Selection 

 Overall Evaluation model was conceptualized as stated above and validated to proceed with . Now the   most crucial part of the evaluation framework was ahead of us to establish its authentic workability . For   which “ Calibrating the Assessments ” was essential , i.e. to ensure that these assessments at each level   would produce the results which are in line with employees ’ actual skill levels . For example , when   employee is certified at Level 2 post the assessment , in reality , he / she is indeed at the skill / competency   Level 2 and not at 1 or 3 . For this , I ’ve decided to apply “ Learning Launch ” of design thinking . 

 Application 

 Selected a group of participants from the target audience and after imparting the necessary training to   them from their respective LOTs asked them to take the online assessments . Then their assessment results   were compared against their professional academic scores when they joined the organization , the scores   they have got in various relevant trainings they underwent after joining the organization and also against   the ratings they used to get on their technical skills and expertise by their supervisors during half yearly   and yearly appraisal process . Control graphs were plotted and cases falling outside of control limits were   analyzed . Initially we found higher numbers out of control limits . Then we adjusted the parameters in the   assessment engine and also modified the question bank repository . 

 This cycle was repeated 2 - 3 times with different set of employees to finetune the assessment mechanism   and calibrate the assessments till the cases falling out of control limits were minimal and our solution   became authentic and workable for the organization wide implementation . 

 Insight 

 “ Learning Launch ” tool turned out to be highly effective in this piece of our project . It was crucial and   most challenging work piece of the overall project and if we would have directly implemented the   framework across the organization , without having tested its accurate workability on smaller groups ,   2 - 3   times , the entire initiative would have been a flop show . Learning Launch tool helped us to 

 -   ensure solution workability in a shorter time ,    -   making us take fast corrective actions to calibrate the assessments ,    -   minimal but direct involvement of the end users of varied samples covering the larger spectrum of   technologies and levels    -   and most of all , with very minimal efforts , it enhanced our ( project team ) , sponsor ’s and key   stakeholders ’ confidence as to whatever solution / framework we are providing is the top notched   realistic solution for the benefit of the entire organization and target population . 

 Approach 

 I think , every tool has its own pros & cons . Not every tool will help or provide same benefits in different   challenges . According to me , “ Learning Launch ” is the better one to ensure the workability of the solution , 

 -   when there are multiple unknown factors involved in the new initiative ,    -   when there is no previous data available to cross verify the practicality of the solution ,   -   the volume of impacted population is high or very high   -   implementation cost is high or very high 

 If your challenge does n’t involve any of the aforesaid factors , then the risk of direct big - bang   implementation is comparatively less and that risk you can mitigate by analyzing the past data and trends   from the similar challenges and decide the course of action on your challenge .
### Output: 