"No one is harder on a talented person than the person themselves" - Linda Wilkinson ; "Trust your guts and don't follow the herd" ; "Validate direction not destination" ;
Showing posts with label Analytics Thoughts. Show all posts
Showing posts with label Analytics Thoughts. Show all posts

August 22, 2021

The Dark side of Analytics

Interesting read - When algorithms dictate your work: Life as a food delivery ‘partner’

This applies to all aggregators - OLA, UBER, etc..

Key Perspectives

The Trap

  • The illusion of guaranteed income while the variable incentives seem attractive initially
  • Incentives riddled with a bunch of terms and conditions

Chasing Dreams

  • Competition to be top performers
  • Physical and mental costs of driving to complete those targets
  • Average of 10 hours of being on the road
  • A job that demands a large amount of time

Eating outside has costed my health very badly. In a way, this is not a sustainable business model. Until 35 your body will not show any problems. The effects will come up after 35. 

This business model is a toll on workers and they are not prepared for any better next job. Doing a good job vs Live your day vs Work for a better tomorrow.

Sustainable business models vs Profitable business models vs Inclusive social growth is always a question.

I am scared if the algorithm starts measuring my time

  • How long have you looked at PC
  • How many lines of code written
  • How many functionality worked

Life is too short to see everything through the same lens. 

Keep Thinking!!!

August 06, 2021

Thoughts - Ideas - Application Log Analytics

  • The average number of users per day
  • The average number of User login by day 
  • Top Peak hours of App usage by weekday/weekend
  • User - Preferences - Areas spent in App
  • Weekend Usage
  • Duration of Average successful transaction
  • The age group of users vs Duration of users
  • Multiple logins per day
  • Average session for multiple users
  • Average transactions are done per month by age group
  • Segmentation of customers based on areas of usage - Age_group, App_Area, Number_of_Transactions_per_day, Number_of_Login_by_day
  • Segmentation of customers based on Transaction types, Transaction value, Transaction category
  • Types of App Errors
  • Types of Timeouts
  • Peak App Usage during Holiday
  • Peak App Usage during Markets Signals (High)
  • Signals at Month End, Quarter End, Fiscal Year-End
  • Trend usage patterns during quarters / Months / Holiday 2 Week periods
  • Usage Life year over year
  • Hourly Patterns 

Keep Thinking!!!