Background
Govt is the biggest employer in India, employing almost 47 lakh people. Due to the extreme reach of GOI, job security attached with a govt job & the pensions post employment makes govt job a prestigious pursuit in our Indian society. Now recruitment of most of these jobs is done via govt exams. Thus, these exams are viewed as a gateway to change the financial & social status by many Indian families.
Problem Space
❓ Problems -
Unfair risk to reward ratio - With the perception of breaking the social mobility barrier many Indians take massive amount of risk to achieve the rewards in hand. But many times these rewards do not do the justice to the risks taken High failure rate - With almost 7.22 lakhs selected out of 22 crore candidates the failure rate is way too high. In case of failure, the sunk cost in terms of time & opportunity lost is way too high. There is no way to recuperate this cost any means as the marks achieved become useless for any new avenue explored by the candidate Candidate search - For private employers it becomes hard to get a good talent fast as they’ve to setup their own filterization metric & reach out to relevant candidates to fulfill their positions. It becomes quite a task to navigate through such a clustered market
🔍 Importance of problem vs Satisfaction of existing solution
Solution space
💡Problem theme vs solution hypothesis
🏅 Prioritization
Here we’ll look into the impact vs effort framework to decide whether the given solution would really help us solve the problem with minimal effort thus, answering should we really pick the feature up (NOTE - real life would have lots of other factors to be considered like context or client demands but for sake of simplicity we’re only measuring these 2)
Let me just define the metrics to be used for both impact & effort
🎯 Success metrics
Like any job portal website the north star metric for such a product would be - total # of applicants placed. To better understand the complete flow let us understand each set of metric with regards to pivotal positions in user journey -
Product distribution - # of failed applicant registered / exam Mapping algorithm efficiency - # of applicable jobs / registered user Applicant <> job interest fit - (# of applied jobs / # of applicable jobs) / registered user Employee <> employer fit - (# of shortlist / # of applied jobs) / registered user Final job interview success rate - (# of job calls / # of shortlist) / registered user