Honest Data Science Talks

The Social Science

#HDST

This article is Talk 03 of Honest Data Science Talks series. Each talk of around 500 words length, is personal thoughts and deliberations on the domain.

No wonder not only us, but even the society (social) around us is encouraging complexity. Technology always brings updates. These updates, to me, seem like a universal balance. It updates something somewhere and downdates (hope I can coin and call that) something somewhere else. The decision making and process workflow is not the same as what it was once and we cannot ignore it, just because we don’t see it.

Here is a scenario to make it more transparent. I have a grocery shop in my neighborhood where I mostly buy my daily needs from. If the shop has less or no customers, I prefer to converse to understand the process. One of the evenings when I had been to buy a bread packet, he said that was the first pack that got sold that day. I was a little curious and wanted to know more. When I tried to understand what he meant, I had this ‘okay-that’s-new’ realization.  

It’s the same old question – who will bell the cat?

Once, not very long ago, the bread delivery van used to arrive once in 3-4 days and deliver all the required supplies. Bread usually has an expiry time of a week. It was the shopkeeper’s decision on how many to purchase. Often, and many times either there used to be a shortage of supplies or a few packs expired. Sometimes the expenses were shared. But now the model has changed. The van comes every day. Every day the packages can be purchased based on the need. But, it’s still dilemma management. Some days, the packs are over by 11.00 am and some days it takes 6.00 pm for the first pack to go out. Inventory management needs to have a new chapter (or maybe there already is).

I tried to visualize the whole scenario in a data scientist perspective. I also asked if bread packs sold out more and fast on Sunday’s or any other specific days. I learned that there was no pattern at all — not even an approximate pattern. Collecting a month data or year data or decade data was not going to help. The model of management had changed and I don’t know how many times. We cannot collect the data generated using different process models and apply the same data science model for all of the data. We cannot plot a graph for this and predict the next day requirement. We cannot predict the accuracy of such a system. The system should also take care of the data generation model and not just the data.

Each and every home in the locality needs to be understood and first, their bread pack model needs to be predicted. Then, based on that data, the shopkeeper data can be predicted. Maybe there is more that I have missed out too.

I sit amazed and questioned about the societal effects on data science. And to say, this is one such example.  The social affects the data and it cannot be ignored. All those existing models look a lot immature, at least to me. Someone needs to pull the socks up and really get on to understanding such social-science models and then logically realize a meaningful, holistic picture for data science.

Dear Data Science,
Please understand Social Science
, if you may want to have science.

Go to Talk 02: The Data Villains

You are in Talk 03

Go to Talk 04: The Human Logic

15 thoughts on “The Social Science

  1. The blog post dropped a new idea, about how simple things around us can be made better by using methodologies that already exist. Now on I will try to think of where computer science can fit in given any scenario.

    Liked by 1 person

  2. In the times where all data science is to analyse the data that the users generate this a fresh perspective that we must also analyse the users who generate the data

    Liked by 2 people

    1. The uncertainty needs mathematical modelling, one which goes beyond the patterns. (This might be just me thinking out loud, but) Mathematics of randomness is also patterned. So as you said,
      “Dear Data Science,
      Please understand Social Science, if you may want to have science.”

      Liked by 1 person

  3. Human Beings are creatures of habit. The problem arises when there is an inexplicable reason to the pattern of customer’s buying habits. I have had a similar experience when I went out to buy milk. The dairy product gets spoilt in a day and I always got perplexed over their management system. Number of packets brought today might not be the same tommorow, similar to the bread problem. So how do they manage/predict that? Personally, demands from my house changed, with festivals, birthdays or my parents not being home, and as an effect changed my buying pattern. (When I asked them about my conundrum, they replied that they got advance orders or brought specific number of packets a day, otherwise they faced the same problem as I had asked.)

    Club the patterns of all these and the data in front of you is chaos, pure CHAOS!

    Though this is the case, let’s not lose hope, let’s take a step back. We are too near to the data. Maybe the data just looks chaotic from this close… Because I think there is always a pattern, there always is. (Because we are after all creature of habits and circumstances as a society, Together!)

    P.S. – The question remains: How much of your privacy are you ready to give up in order to increase the overall efficiency?

    Liked by 1 person

    1. Exactly. The anti-patterns do turn patterns. I like the way you bring in the CHAOS. If time permits, do read about the chaos theory. Though not very closely related, it does add sense.

      Commenting on privacy, that’s no more a questions. Every data is out there, like it or not.

      Thank you. We have been working on models to capture the questions you raised.

      Liked by 1 person

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