 Let us further update the model, again we have been talking about the retailer, we have been making one fundamental assumption in this, what is it? We assume leak time is 0, so as soon as I order end of the day I check the my sales, I check my desired inventory, ok any 200 kgs, ok today sales has been 20 units extra, so I immediately order and the next day morning it is there with us. So, that is the assumption that we have made. It is instantaneously supplied by the factory or the distributor or whatever the source warehouse or whatever you call it. Now, let us introduce and see what will happen to dynamics when we explicitly account for this supply delay, right. Suppose there is a supply delay of say 2 days fixed delay, let us say there is 2 days delay fixed, from the time of ordering to the time of receiving the order, now let us update our model to represent this, how will we do that? What do we need to introduce, variable, flow, stocks, what do you want to introduce? So, now the simplest is whenever there is such a physical flow of information it is it is good to start explicitly capturing it. So, let us introduce a quantity called as quantity in transit, so whenever I make an order let it be in transit and after 2 days let it be delivered, ok. So, we will be introducing a new stock, as soon as we use the word there is a stock that means there has to be a flow that has to change it and once a transit once the quantity in transit is delivered that means the quantity in transit has to fall down to because it is already delivered, right. So, that there has to be an inflow as well as an outflow to this stock. We will save it as pilots, why don't you model this. The red color once has one you have to do, it will require you to delete some of your old model and then recreate this model, so whatever you have done you will leave it, the red part you incorporate. So, all this model does is introduce a new stock, so as soon as decide order that became order rate it stays in transit for a supply delay of 2 days and then it gets delivered to the inventory, that is the only thing that we have added. So, go ahead and delete your earlier order rate and redraw the diagram, only red ones is a new one others you should already have it, order rate continues to remain equal to desired order rate. It is a fixed delay, how do you model it, fixed delay of 2 days how do you model it. So, we are using delay fixed equation, go into your model use delay fixed and give the input as order rate, duration as supply delay, initial value as initially what should be delivery rate, it is 0 initially sales rate is 0, so we will assume delivery rate is also 0, then initial quantity in transit will also be 0. So, first 5 days nothing happens, so there is no reason why we should keep delivering it is all 0, yeah this is a delivery delay, this is a delivery rate, delay fixed order rate comma supply delay comma 0, got it, when the model fraction adjusted our smoothing constant say this model I am using it should be 0.2, now let us look at order rate, now you will I start to see a pronounced oscillations within your dynamics of your order rate earlier when there is only information delay you overshot and then you gradually reached your goal, but when there is a supply delay is also in the supply line is also explicitly captured to represent the physical reality of the scenario, we find that there is oscillations. This is called as damped oscillations, the oscillations occur, but it just dams out and it reaches steady state of 20, if order rate is going to oscillate quantity in transit or 0 then it starts to oscillate, inventory will oscillate, initially it falls down and it slowly oscillates around the mean or that is around the desired value it oscillates and then reaches steady state, sales rate will also oscillate, no it will not it is exogenous variable, why should it oscillate that should not oscillate, it is an exogenous variable that is what drove the rest of the system to oscillate, so the important idea to understand here is your sales rate is remaining constant from 0 to 20 to 20 that is it nothing else and let us look at expected sales rate that also did not oscillate, expected sales rate had a nice exponential goal seeking behavior that also did not oscillate, but because of your ordering decisions that is your entire decision that is captured here, so the model can be divided into two, the top part of the stocks and flows can represent the physical stock flow model of physical flow versus the decision making structure that is employed by the retailer decision maker is represented using the variable like desired order rate and inventory gap and expected sales that is represent decision making structure, that decision making structure of how we are adjusting for only the inventory gap as well as the expected sales rate is allowing us to is causing the oscillation within the system, is causing the oscillations in inventory order rate, expected sales rate does not oscillate, causing oscillation oscillation in your order rate. So, this is a very simple example of the origins of oscillations in business cycles where why do you think it oscillated, the answer is here we added this in the model it started to oscillate right, we had explicitly model quantity in transit it started to oscillate correct, it oscillated because we failed to account for the supply line in our decision making though physically the supply line was modeled, we never use the information in our future decisions, we ordered something today I know it is going to come after two days, but the next day immediately look only at the inventory and look at decide inventory, oh the gap is large ok let me again order and then let me again order. So, result happened is that initial orders overshot more than what you actually need because initially the gap will keep widening because it takes two days for it to come, you saw the shortfall of 20 immediately order 20, then next day the shortfall became 40 because whatever you order is 20 took two we will take two days to come it has not had reached. So, in gap became 40 you ordered 40 units said overshot what you more than the desired steady state order values and then when the quantity started getting delivered you suddenly realize that oh 20 got delivered ok let me order less, but then the next week 40 got delivered three weeks hence right. So, the inventory overshot what it should have been. So, immediately start to cut down the orders lower than the steady state order. So, that result in the order quantity going below the steady state values which is represented in this graph right. So, initially over compensated that is every time you only looked at the inventory value in making decisions you did not account for the supply line within the system in making your decisions. Why do we ignore the supply line? Well it is difficult account for it frankly speaking when talked about logically it seems yeah we should account for it yes it is so obvious if I already made an order I would not make an order again right we do not make an order again because I order no retailer is going to order forget whatever you ordered yesterday because he is going to get it later there is a rational explanation, but there are several real life scenarios where we may tend to ignore the supply line. For example, multiple clicks on web page if it is in load you keep refreshing many times if you refresh it once it will come, but you still refresh many times that is all goes to supply line and suddenly you will find the website refreshing two three times it is all getting piled up. Balancing hot and cold water in the shower especially if it is a new place it takes some time to get used to it maybe in your home or in your hostels or somewhere you know exactly where to change the dial, but if the new place you do not know where to check it you set it in there will be cold water in the pipe it has to come down come out right, but then you make it really warm then suddenly you get lot of warm water then again you close it. So, that is because you did not account for a supply line because the information is not available to you to make the decision why do we ignore supply line because recognizing and accounting for time delays is not at all innate we are used to taking short term and very quick feedbacks we do not account for a very long term effect that can occur we look at what is happening now that is the inventory kind of thing. Now this is what is happening ok let me take a decision right now we do not care about what is in the stock what comes later and things like that. We need to be patient recognize and account for time delays. So, you may say like you know in our hostels and the homes we are used to you know where to set the hot water cold water dial or our current retailers will know exactly where to set for his how much to order how much when to order, but whenever new settings new products come in people have failed to account for it especially when there is a disruption in the supply they just cannot account for it. We will learn only if the feedback is swift in most business cause and effects is obscure and supplies need not only be caused by you right there will be so many other retailers ordering so many other manufacturers supplying so all those things are also going to affect it. So, which obscures your cause and effect scenario when dynamics are so and time to learn is more than the tenure sometimes he is a regional manager only for 2-3 years right if some feedback is going to come kick in after 3 years you do not really care because your term is over, but this 3 months is you had a objective the marketing manager objective so he has to fulfill that in this 3 months in this quarter. So, any feedback may occur in the next quarter you will say I will worry about it next quarter, but that means what he is doing is he is ignoring the supply line. Sometimes it is rational to be aggressive ignore the delayed consequences like we just told about incentives to incentive to only look at this month's sales target and accordingly take a call this month's inventory level and take a call on what you should do rather than what is in the pipeline what might happen in future. So, general structure of the physical structure of the flow can be simply modeled as an order rate and then there is something in the supply line and an acquisition rate which affects the stock and then there is a loss rate. Most often we are used to seeing the stock to make the decision based on the loss rate. What is difficult to capture the supply line is very difficult to capture. We are looking at the stock and the loss rate and taking a look at the order rate without accounting for supply line acquisition rate. This can be mapped into variety of scenarios the structure that we are going to discuss or we have been discussing like inventory management what we are doing the stock is called as inventory the supply is goods in order. Loss rate is shipments to customers acquisition rate is delivery from supplier order rate is goods on order the behavior is called as business cycles that is what we have been seeing. The similar model can be applied for even human resources where your stock is nothing but employees supply line is your vacancies and trainees that are there in the system. Your loss rate is nothing but your layoffs and quits so based on that I need to hire people but then as soon as you hire they are not immediately available we need to train them we need to give a job offer people have to join and then they will go through some induction program and then you have to select and become part of the team. So, there is a huge supply line gap. So, this is also part of a business cycles. Even in marketing this applicable where we look at customer basis as your stock potential customer is supply line and we customers can defect to the competitors then you have to recruit new customers and as new customers come in that is the whom you are going to work with. So, that is called as boom burst in customer cycles. Agriculture commodities also similar structures applicable where inventory is inventory of the grains or food. Supply line is nothing but a crops in field and your consumption is your loss rate acquisition is a harvest rate and order is a planting rate. So, this fundamental structure can be used to somewhat explain the agriculture commodities cycle where some commodities you get a huge over stock and prices just crash and government has to you know rescue them because people looked at there is a lot of demand now. So, let me plant more and then they forget that they have planted more and suddenly you have a huge amount of stock coming in and then price. So, there are other dynamics like price, but the fundamental idea remains the same. In real estate building stock we have buildings under development is the supply line and when buildings depreciate that is a loss rate completion rate adds new buildings to the stock development rate has to supply line. So, this results in real estate boom and burst where multiple players are building a lot of buildings, but based on the current demand new when new developers come into play result is total building stock increases then price goes down then they again hold because they are not really worried about the supply line they just keep building.