How machine learning is taking over human jobs?

Everything was saying Please let us know more details about your latest arose rice car They did not really what he about these Alfa camera batteries they want toe Similarly you were If you are saying optimizing separate chain by demand forecasting off amazing separating only devil thing is your project is more on the demand forecasting So you can even say the man forecasting for supply chain operations Even that would do as a title Yeah I think this example is available We take this No but don’t have to take this because I say you have a think and think about it because I was not interested.


I was not quite convinced about your title of the project Yeah just think about it The group is coming here Even the very start is remarkable So far the problem for me How am I going to really differentiate Of course I’ll be very fair and just Yeah very body as put in the best efforts And every group is trying to do at the excellent job it looks like in search of excellence Your everything is excellent How can you such in such of excellence Everything is excellent on and everybody has the viewpoint.


I think the shows that mark cover for 10 shillings you are potential is infinite which perhaps was not fully discovered by all of us is a remarkable potential you have And what do you say this started Six is hard at This is hard I think everything is a cakewalk for you know they won’t we Except that I put some questions sometimes that’s my job You see just to set the context Um So again going back to the supplication thing we all belong to supply each end of the reason why I wanted to probably him physician separation though we’re doing demand sensing primarily Um so we kind of as ah um saying that we wanted no get a good data and then problem statement so related to the industry that we are working on We are basically from rated industry So stumbled upon this data on the problem statement which belongs to the bakery industry So I know we wanted a deep dive in what the baby industries on the board and record Very good inside.


We didn’t know this prayer doing this Not getting to the project break industry in itself Globalists about 4 $60 billion industry which is buying aboard 2.5 million people And some of the leaders in the industry are a suspension there Masaki Grupo Bimbo and Model is international Group of M Boy itself is ah $14 billion company Basically Mexican Mexican company model is international Is American company again About $15 billion company thing A Masaki is again $10 billion companies The Japanese company This one of the big players But we are considering um small players like because statistics I don’t show up anywhere How the bacon industry is segmented There are no surprises There is clearly led by the bread rolls which is kind of our daily consumable product followed by cookies and crackers Andi then cakes and Tortola Us Yes sure.


What It was great This just employs about 2.5 million people and it’s much for 61 billion on We are working on the problem group open with the second-largest my infection into but right I mean what the next night Yeah a saying $14 billion company having its presence in 22 different countries predominantly in American countries and a little bit of Europe as well as Asia currently employing about 1.3 million people globally Um obviously slept Donald is making Mexico Mexican company headquartered in Mexico Just while we’re here I want to get your attention to some of the brands because these play I mean our model was more about feature extraction you know get getting insights from all the brands and all the products And how do they go together So just want to get your attention to this Although not all of these are quite familiar Be more at least Laura de Rosa.


I’m not familiar Until I wasn’t really until I saw this Ah bits of an investigation into what their operations are So we are going to look at the Mexican market in specifically on the information we had obtained from Kagle So there was x 70 million our data on they put a problem statement which is what this is so surprisingly That’s how it started Given the huge volumes group of members have no inventory Calculations have been done by a computer or intercourse Um so it’s all been done by the direct delivery sales employees So hasn’t been the going deliver They take the input for Hey what you want tomorrow on your talking about not just the stores of different form it. We start talking about Wal Mart which is one of the key suppliers of Wender for a group of U and also talking about the small convenience stores where talking about the ski down our shops and everything.


You get when stores in all size and form it are the windows And also it informs It’s a group of you are servicing And that’s what even makes it more surprising You don’t have forecasting first a mechanism so yeah this is corporate covered actually On Another key thing is the shelf life of these products are gonna be one week We’re talking about bread rolls cakes and all those that are bakery items which are going to go stale within a week or so And it’s quite important to get those numbers right from that Yet did you want to get away from these direct employees on then The local knowledge also comes in a large So we want to make sure that how can we move that into the garden left It is possible to right Ah well this is just a snooper from Gardner I don’t want to really dwell on this lot more just to kill the importance of forecasting a greasy from a supply chain planning perspective.


This you ate wonder We’re talking with operations and planning Want to enter into the demand forecasting world It’s all a part of the supply chain planning You call plating planning where the forecasting everything comes in You have execution where you have the rare housing transpiration everything it comes in and then you have the feet the last mile delivery So in supplies in planning the focus security this is a score after they have spoken to a lot of the leading retailers and people who are employed in the retail industry So that’s that stands out That’s why it’s even more important to address This problem from a group of it’s so the scope of this project is to focus demand for ah week nine and 2010 11.


We what group will be moved on They have given nine weeks of sales data sales on Britain’s later So off which ah ah we can use seven weeks of data to build a model on predicting eight and nine weeks data so that that’s what the objective of this project is all about Yeah it’s seventies data So all they got is one million customers on 800 products on its a time series data where the products are delivered in multiple trips to each customer or a week so it in order in 73 million transactions On Detest noted that is you are right in terms of the number of records Is 70 million what you’re saying But in terms of the time series data only seven weeks Yeah so that’s one of the problems we have So we can’t do We can’t find demand started trained or seasonality because it’s very short duration Do you have any exogenous Any other variables which are related to the growth of that will come to that.

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