Data Driven Trick or Treat – Maximize the “Candy Collection” next time

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Another Halloween just got over. I am sure all of you had a great time putting the lights and carving the pumpkin – at least your kids had really a fun time.  I too enjoyed standing at the door and giving out candies. My 11-year-old boy just came after a 2 hour Trick-or-Treat journey in my neighborhood. Not only that he was tired, but he was very upset. I asked him on his concerns and he listed a few:

 

  • We went as a group of over 10 kids together to each house but it looks like whoever went as an individual or in small groups got more candies
  • We started on the first street but many of them were not home by then
  • But when we reached the last street, we were too late
  • When we were in the middle street, all the groups were there at the same time and people in the houses were tired (continuously opening the door) and they just wanted us to get away as soon as possible – neither them nor us really enjoyed there
  • At the end, we walked too much but the candies we collected were too less

I promised that I will provide him a path for next Halloween to “Maximize the candy collection with the least (or optimized) distance walked!”

I have one year at hand from today to keep my promise to my son and I have a lot to do. Many of those are really un-knowns. Let me list a few that comes to the top of my head now:

  • Which neighbors consistently celebrate Halloween and passionately – It could be based on various parameters including ethnicity, country of origin etc.
  • How are they doing year over year (trend) – based on demographic data?
  • Who will be at home and when – data related to their work schedule/exercise schedule etc.?
  • Are there kids coming from the next neighborhood?
  • ………………….
  • ………………….
  • OK, now I have all the data, but do I know how to solve this problem (statistically)?
  • Do I have the skill/tools to get to the solution?

I am sure by now you have guessed where I am headed. Is this the same problem all of the organizations have – “They want to increase their topline but with optimized resources”. If that is the case, are they doing these basics?

  • Once you have the problem defined, are you able to create a fishbone diagram (a cause-effect matrix)
  • Do you have a one-line statement of the problem you are trying to solve – just like “Maximize the candy collection with the least (or optimized) distance walked!”
  • Have you figured out what data you need to analyze the “causes”
  • Do you know where to get the data from?
  • ………………….
  • ………………….
  • You have all what you need but do you know how to solve your problem?
  • OK, all set but your window is too short and you should do it fast!

Is this what you all are supposed to do? Is this what we talk about as the strategy – a data strategy? Followed by a roadmap? Data? Execution Plan? Skills? Agility? Speed…?

Are you all ready to “Maximize your Candy Profit” for the next Halloween?

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1 Comment
  1. Really good presentation. Worth to read it.

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