From theCUBE studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. Cisco's $28 billion acquisition of Splunk represents a good outcome for Splunk and a strategic growth opportunity for Cisco. Splunk's painful transition to a cloud and subscription pricing model was largely through the knot hole as seen by its margins and recent P&L performance, but questions remained with respect to its growth prospects and competitiveness in the hot observability space. For Cisco's part, the acquisition brings more software and additional $4 billion in ARR and a chance to grow Splunk's business, particularly internationally. Our initial research shows joint customers are generally positive on the deal, in particular with respect to Cisco's expanded portfolio in security and observability. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this special Breaking Analysis, Eric Bradley of ETR and I will share the results of ETR's flash survey assessing joint customer perceptions and likely spending actions as a result of the Cisco acquisition of Splunk. Eric, good to see you, my friend. Thanks for coming on. Always great to be here, thank you for having me. Yeah, you bet. Okay, before we get into the survey, let's set the table with the recent rocky journey of Splunk. So what we're showing here is a five year chart of Splunk in the blue and the Nasdaq in yellow. Let's go back to 2019. That's the year Splunk acquired SignalFX in an effort to accelerate its pivot to the cloud observability in a subscription model. As you can see, prior to December 20th or December 2020, the street was buying into the story. Note Splunk's performance through November 2020 in the lower right, outpacing the Nasdaq by almost 30 percentage points. But then it had a really bad miss on ARR when it announced earnings in December of 2020, December 3rd, and it suspended long-term guidance. And while this was common practice at the time during COVID, Splunk had been holding firm on its pre-COVID ARR guidance, and that was a tactical error. At that point, it became clear that the first disappointment as the saying goes, would not be the last and the bears gained control as investors retreated from a company that was in transition. The stock got a bump when it was reported in February 22 that Cisco was offering $20 billion to buy Splunk and around that time, the board removed Doug Merritt as CEO and brought in Gary Steele, a CEO with experience selling companies. The pain continued, but in 2023, we started to see light at the end of the tunnel as the transition started to show up on the income statement and you can see the pop-up in price at the end of this chart as Gary Steele's handoff from Doug Merritt took hold and Splunk got $8 billion more than Cisco's rumored prior offer. And that brings us to where we are today. Now, while some voices are vocal and this is a bad thing for Splunk, as Eric and I reported in our predictions post in 2021, the spending picture for Splunk was clearly deteriorating. This chart shows the breakdown of ETR's proprietary net score methodology, which is a measure of spending momentum shown in the blue line. The green bars are spending more, the red bars are spending less, and the bright red is churn. And Eric, as we called out two years ago, competition and transition were not friends of Splunk. The point is Cisco in many ways represents a lifeline and avoids Splunk's board having to do a heavy lift. Eric, your thoughts on all of this. Yeah, there's a lot there. First, I want to state we also called this Cisco large acquisition and security in one of our predictions posts. So it's very hard to get one of those right. So a little kudos to you and I, Dave. But also about the stock price, amazing that they were able to get $8 billion more. One of the things that concerns me is that a 4 billion in annual ARR, it's going to take Cisco a very, very long time to recoup that money. However, as we're going to dig into soon, there's a lot of potential synergies here and overall the sentiments skewed positive among their client base. Another thing that I think we should just talk about a little bit is the Splunk data completely spot on. We've been catching a downward trend, deceleration and spending intentions for quite some time, particularly in what we call the analytics big data sector. It's really starting to drop. This sim is holding up a little bit better, but the amount of competition in that space is just overall grueling and it's going to get worse. I think the real key here is a combined entity is not only integration, but then innovation on top of it. These two combined entities really need to take all this data telemetry they're now going to have and turn it into a great XDR if they're going to be able to compete with the other competitors in their space. Alex, bring back this slide because while it shows a worrisome spending deceleration in the blue on Splunk's combined platforms, the yellow line, which represents pervasiveness in the data set, it's held up pretty well although it's beginning to wane. So the Cisco acquisition comes at the right time. Okay, so let's get into the customer analysis. First, let's look at the overlap of Splunk accounts and Cisco accounts over time. And Eric, I wonder if you would take us through this time series chart and what we're looking at here. Yes, certainly. So what we're looking at in this first slide is what we call our proprietary shared accounts analysis. And what we do is we overlap citations. So on the left hand side, you would see that this was 665 different Cisco customers only within analytics, big data and security. So we kind of took out the Meraki networking, all of those type of situations. So among those 665 customers that cited a spending intention on Cisco, we also see that almost 50%, a little over 49% also were customers of Splunk. So the overlap here is fantastic. This is where we're starting to see some of the great synergies. Also from your point of the timing, this has been rising for years and in April of this year was the first time we saw a small down ticket went from 53 to 49. So the timing of this might be really good to kind of stop that acceleration from happening any further. Okay, thank you for that. And so Eric and I spoke right after the acquisition was announced and he said, hey, we could do a flash survey. So we fired up a shared doc and we came up with a number of questions that the ETR analysts and our market analysts put together. And Eric, before we get into the results explain the survey composition, the nuances and of course the caveats of the small end. Yes, so we want it to be fast, right? This is the type of thing that you can do when you're a more agile type of survey company. And I think it's one of the, you know the great prowess of ETR. So for that reason, we weren't looking for an end of 3,400 but what we can do and which I think is really cool about this survey is the 66 people we cited and we did it in less than a day are customers of both Cisco and Splunk. And we were able to do that very quickly and we were also able to do it across only large enterprises which we categorize as 1,200 or more employees. So overall, the caveat to the survey is it's not the largest citation in the world. You know, our quarterly surveys capture, you know 16, 1700. So it wasn't meant to be the broadest but it was meant to be targeted. So these are large enterprise customers of both Cisco and Splunk. I don't know who else we could have gotten a better early reaction and sentiment gauge from. Yeah, it's predominantly North America. There are I think 10 international citations. Okay, let's get into the results here. These joint customers were asked how do you view this acquisition in terms of Cisco's product suite, Splunk's product roadmap and your company's likely utilization of either company's products as a result of the acquisition. And this shows the positive plus the very positive responses. So pretty good positive momentum here for both companies or sentiment for both companies, especially Cisco and Cisco's positive sentiment increases as you filter on the global 2000. I think roughly half of the respondents for global 2000 had jumped up to almost 70%. As well, the sentiment from overseas customers again, the warning is a small end of 10, but still it's 10. But it was overwhelmingly positive. It was nearly a hundred percent. So Eric, anything you'd add to this, do you agree with that takeaway? Yeah, I do. I mean, it's certainly skews positive. There's really no denying it. It's a little bit more positive on the Cisco side to the Splunk side, but still overall it skews positive. The one interesting thing here is that actually of all the customers, the lowest sentiment was about their utilization of the company's combined. So it's good for Cisco. Little bit less so for Splunk, but still good, but the customers aren't so sure it's good for themselves. So that's something that's going to be interesting to watch. Yeah, so let's double click on that a little bit. Now, despite the positive sentiment, we wanted to understand the risk of defection. You saw in that earlier slide, the red, there was a very small churn, maybe 5%. The spending less was going up, but this data represents responses to the question, how likely are you to find an alternative to Splunk? Obviously as a result of this acquisition. And it's mostly a wait-and-see or 39% unlikely, but there is a worrisome 17% that said likely and a very small sort of matching that churn, 5% said very likely. Eric, that 5% again is about what we saw in the previous net score granularity. I didn't go through the granularity, but it's a more sophisticated than I laid out, but me, so maybe not so worrisome, but how do you interpret this data? Well, the difference here between that and when we capture just a general replacement of a vendor in our syndicated quarterly surveys, is that this was asked about specifically based on the acquisition. So that 5% is troublesome, but they're very likely to leave. So there'll be a small amount of churn, but the real takeaway here is that 39% were neutral. So the acquisitions can have no impact. And then the other 39% said they were completely unlikely to leave. So I mean, the majority of this is that, still a pretty good reaction from the customers. But yes, I think, from a headline perspective, the company needs to be aware of that 22% that said this deal is more likely to make them look for alternatives. And let's be honest, there's a lot of alternatives out there. Again, I'm gonna go back to what I really think the key to this entire deal is Cisco in the past has made acquisitions but hasn't integrated it well. They need to put that behind them. They need to make sure this integrates and then they need to innovate on top of it. I would love to see a real industry leading XDR come out of this because Lord knows they're going to have a lot of data telemetry. Great points. And that's something that Cisco can manage. They have that, I believe is in their control. Let's now look at the likely spending patterns of customers, what they expect based on this deal in terms of new products, modules or features from Cisco and Splunk and Eric, nearly half of the customers in nearly 40% said they're likely to turn on or spend more on Cisco and Splunk new products, modules or features. And I find this pretty positive with a very small percentage saying unlikely. What are your thoughts here? I agree. I mean, I think it's fantastic. I mean, basically what this is showing is that even though they're two incredibly pervasive companies, there isn't much product redundancy here. That's why it was a really smart acquisition. They're a better company together than they were standalone. And this is a very positive aspect, particularly for Cisco, because you can see the data again, skews a little bit more positively for the Cisco side than the Splunk side. But still on both sides, they're more likely to turn on new features and modules. That is all you can ask for when you make an acquisition this big. And I'll come back to the other point at four billion ARR an annual for Splunk. That's going to take seven years to recoup this cost. So they better increase that ARR. So it's a little bit less time. Okay. As we've said, security and observability, big areas where Cisco will accelerate once the deal is closed, which is going to take at least until the spring. Here's a look at what the customers see as the positive impacts of the deal. Security is the big winner, followed by investment, leverage, and then expanded observability offerings. We'll talk about that some more. And while many have positioned this as an AI deal, joint customers don't see enhanced AI capabilities as advantageous, although there is a data angle there, Eric, what would you add to this? I think you pretty much gave a good analysis of this one. I think something that's really interesting here though is the very small amount of citations on that advanced AI capabilities. This kind of speaks to the trouble that both companies were having on a standalone basis. So to a certain extent, the game is sort of passing them by. And I don't know what they're going to do about that, but with only 22% saying that was a positive of this deal, the problem still exists, right? So the great part here is that everyone views this as an expanded security and enhanced security offering for them, which is fantastic, but they still are going to have this sort of, advanced analytics problem on their hand. Yeah, and it still gets vogue to say AI, AI, AI, as much as you can. So I get that. And I do think there's some legitimacy to the fact that Splunk has been in the data business and been doing AI for a long time, as have many, if not most software companies, but this is not specifically an AI deal. Okay, let's now look at the negatives and what concerns customers. No big shock. Customers are worried about higher prices, loss of focus, possible brain drain out of Splunk, and a smaller percentage are worried about lock in, even though they're probably pretty locked in, and dilution of innovation, and supporting Cisco's assertion of that, this data supports Cisco's assertion, that there's not a huge product overlap. That doesn't seem to be a major concern here, Eric. Yeah, the second time we've seen that, that there's no product redundancy, which I think is just fantastic of your executives of Cisco right now. So you're very likely to cause churn or lose customers based on that. But the number one concern is high prices. But the truth is that was existing for Splunk anyway. I've been capturing that in my panels and ITDM interviews for years. So I don't know if anything changes here. Anything involving Splunk has always been concerned about lock in and prices. But despite that concern about pricing, they're still incredibly sticky. And I think the question you would have to have, if you were a Cisco executive at the moment, is how much room do you have to raise pricing at this point? I think that's a question they're gonna have to test and figure out. There is a concern. And even if they do raise prices, it does seem like most customers realize that they're locked in and they're kind of okay with it, to be honest. So until something really, really intriguing comes along with a lower price and the same efficacy, I think they're gonna be okay for a while. So let's look at that. As Eric says, pricing has always been a top concern in Splunk's customer base. So we wanted to understand, drill down on that, what are customers thoughts on pricing? Nearly half of the respondents said, we don't like the pricing, but we feel locked in. Now, I mean, Splunk has a very large install base. It's got a loyal install base. Customers really, really like the product. They have processes and procedures built up around it. So hey, it's kind of like Oracle in that, in a way, this is a positive for investors, meaning the business case to stay is better than the switching costs and the risks of migration as well. The second bar here is software pricing, no matter what, it's never perfect. No matter what pricing model a company chooses, it's never gonna please everybody. And then not surprisingly, less than 10% of joint customers love the pricing model. Why would you ever answer a survey that says, oh yeah, we love the pricing? I mean, right, Eric, it's rare to say that they like the pricing. Any other comments on this data? Well, first of all, it's completely anonymous. So they did, it's not gonna come back to haunt them in any negotiations. I just wanna reiterate that to all of our ITDMs and thousands out there that contribute and thank you for what you do. Yeah, we've been hearing about this forever. This is sort of like old news type of thing. Splunk is extremely expensive and people have been looking and seeking different type of pricing models from them. I've heard people say that the problem with Splunk is they have to decide what to leave on the cutting room floor. And when you're talking about security, that's dangerous. You want to ingest everything. You want to store everything. And that's going to change. These new competitors out there have cheaper pricing, have better storage, longer record keeping.  But again, I think this move is going to make them better equipped for that than worse. Okay, the last data point we want to show relates to the Cisco and Splunk responses to a question from an Oppenheimer analyst. This was on the call. This individual asked, why did you buy a legacy company instead of an emerging company with a more modern architecture? An obvious target there would have been, for instance, Datadog in that scenario, by the way, Cisco would have had, they would have gotten 40% of Splunk's revenue and more than double Splunk's revenue growth rate, but it would have had to pay well no worth of $30 billion. Elastic is another one maybe, much, much smaller company and wouldn't have had the near-term potential of Splunk. At any rate, the response Cisco CEO Chuck Robbins and Splunk CEO Gary Steele gave basically said, look, the world is hybrid, multi-cloud and our strategy aligns with that. More than two thirds of respondents agree with these statements. Interestingly, the number one response speaks to the complexity of the hybrid approach, but it's got good value. Complexity is something that Cisco is aggressively trying to address. We've covered this in previous breaking analysis. So that's an opportunity there. 14% say it's hard and of poor value. So some work to be done there, as Eric, as you point out and then 13% say Splunk dismissed the boat on cloud. Eric, to me, this sentiment is very manageable. Like you say, they've got some work to do, but if Cisco focuses on it and they've got a competent management team for sure, and it speaks, by the way, to the challenges that Splunk would have had remaining independent. Cisco can hide a lot of those warts because of its massive portfolio. It's got great service, global coverage and it can invest in addressing some of those shortcomings with much greater resources than Splunk had available to it. Your thoughts? Yeah, I do think this is still going to be a problem as we move more towards serverless containers and those type of things. But for right now, the world is hybrid. Splunk has a great foothold in any regulated type of industry as well. So that's always gonna stay a little bit on-prem and hybrid. So I do think that the core base here is, and then look, even though some of them said that there's a little bit of complexity, we're talking about 48% of them, basically said they were satisfied and a lot of them were kind of neutral and not sure. So again, this skews positive and I think that in all large enterprises, this is a good takeaway from them. Certainly a manageable problem, but one that's going to persist, it's not going away anytime soon. So I still think there's a big road ahead of them to stay relevant, but in the meantime, they're certainly collecting a lot of cash and they are certainly a very sticky business. So I think that cash and that stickiness will help them give them some time to solve this problem. All right, let's close, summarize and look at some of the things that we're going to watch in this deal. First point is Cisco really needs a catalyst to its $4 billion low-growth security business and rather than buy a bunch of little tuck-ins, which is my friend, Zia's Caravala says, Cisco is the king of, Cisco decided to go big and this could be a nice boost to G2 Patel's security business. Remember G2 brought in Tom Gillis from VMware to help get that business going and that was a major executive hire and so this is a big, big move. Observability, which includes assets like AppD and Thousand Eyes also gets a boost. So both security and observability are data heavy businesses and with Splunk's data and analytics prowess, both of these groups can benefit from more predictive capabilities, what Eric and I were talking about before in AI. Look, while Splunk is not necessarily synonymous with AI, it's been using machine learning and AI for years and let's face it, AI starts with data. The big question is, as Eric said earlier, integration into Cisco's current business model and how it will be organized. One of the criticisms of Cisco has been its slow pace of deep integration with its acquisitions, creating more complexity. Meraki, for example, it took many, many years, like eight years before it's, even its catalyst gear could be seen on the Meraki dashboard. The deal is going to take eight to nine months to close. It's going to be another year before Cisco figures out the integration. So that's something that we'll be watching closely. We talked about the impact on the Cisco P&L and cashflow, $4 billion in new AR, cashflow are creative in year one, but Cisco promised to continue the buybacks and the dividends. They also promised to continue operating leverage. So on paper, it's a real plus for investors and Cisco has plenty of room on its balance sheet to take on a bit more debt, notwithstanding the higher interest rates. And this is a cash plus, take it on some debt deals, a cash deal, but to take it on some debt to pay for it. The other point is for Splunk to accelerate growth, it would have had to invest heavily in global expansion, which is extremely expensive and time consuming. Cisco's international footprint is massive. And with only about 15% of Splunk's business being overseas, there's a real upside there in our view. And as it relates to pricing and lock-in, those types of issues, Cisco's going to have to make the business case for staying better than migrating. And I think they'll successfully do that. One thing Eric, we didn't mention is cultural fit.  And that turned out in hindsight to be worth an $8 billion premium for Cisco relative to what they had offered reportedly in February, 2022. And much of that work has been done. So Eric, give us your final thoughts on this deal and the things that you're looking for. I think it's a fantastic deal from Cisco's perspective, albeit expensive. Again, I think they're going to make sure they turn on new features. They have to leverage the customer base on both sides and either increase pricing or increased features and modules because this is a very expensive deal. And without increasing the ARR on the Splunk side, it's going to take a very long time. But like you said, cash flow positive, you know, so I think it's a wonderful deal for them. I'm going to reiterate that integration is the key here. There's been too many times where they've been able to acquire something, but then just sort of leave it on the vine and not, you know, bring it into the fold. It's this time they really need to bring it into the umbrella and pun attended on that one. And also you mentioned networking, I think it's really important to point out in our data that Cisco and the networking in Maraki particular is one of their better spending product lines. It's really holding up well. So the data telemetry that these two combined companies are going to have is massive. And I really think they have to find a way to leverage that and increase their security going forward. And if they can do that, this is incredibly synergistic. And I think it's going to end up being a fantastic deal for not only shareholders, but the companies and hopefully the customers themselves. Because at the end of the day, we all know those are the ones who are going to dictate whether this works or not.  I love to look at revenue multiple, which is only one of tiny way in which you should value companies. But I will say this, Cisco trades and I want to say four to five times revenue. And so while at four billion in ARR, it's going to take a long time to pay back, I really said seven years, pay back 28 billion from a valuation standpoint. They, if they can boost it a little bit and get, you know, five X that ARR, you know, it's not going to take as long potentially. If they can get that to let's say six or seven billion in ARR at a five X valuation, they'll make it back in valuation terms for investors. What do you think about that? I agree. I'm trying to very quickly look up what their revenue growth was, because, you know, it doesn't matter four or five times, it depends on, you know, that's all going to be determined by the pace of growth that they have. And it looks like right now on revenue growth, it was their estimated to grow only at 1% to 2024. So that four or five times for 1% growth that doesn't seem that high. And now don't quote me on that. That was a very quick look while we're doing it, but they're going to need to boost that revenue growth to maintain, you know, multiples or see a valuation lift in that multiple. But the way you're thinking about it is absolutely, you know, correct, sure. If they can use the boost revenues and there's no doubt they're going to be rewarded for it. Was that 1%? Was that Cisco's growth rate or Splunk's? That's at Cisco. Yeah, okay. I think there was an anomaly in those figures. I think Cisco is committed to, I want to say 6% or even higher. It's like mid to high. It has met 2% for 25 on the out year. But again, this is real quick. I should have had these numbers prepped, but just off the top of my head, maybe there was an anomaly or an accounting issue there. And this certainly is not factoring in the new acquisition. So those numbers are certainly going to go up and they will be rewarded for it. Now the thing is, you know, the street usually moves very quickly and the stock reaction to this was muted at best. So I think they're going to, you know, kind of approve it type of mode, at least when it comes to the equity analysts out there, because you know, we saw a huge bump 20% to Splunk's side, based on the great job they did on getting the most money possible. But on the Cisco side, as the acquirer usually is, it's a little bit muted or down. So we'll see what happens. But right now I think the street is taking a wait and see approach and making sure that the synergies are there. The integration happens and they actually do start seeing some cashflow positive and some revenue growth out of this. Yeah, Cisco lost, I want to say, $6 to $8 billion of value on the day of the announcement. So that's obviously the street viewed as somewhat negative. Although listening to the analysts' comments, they were generally positive. I mean, you know how the analysts, they want you to not spend any money and continue to grow, continue to throw off cash, don't make strategic investments, keep paying back dividends and stuff. Right, I mean, it's CEO, that's why CEO job is so lonely. All right, Eric, hey, awesome to have you. Thank you so much to the team at ETR for doing this flash survey and record time and the great, great work that you guys do. I can't say enough about the partnership now. Thank you so much for having us and anytime you need some data, just let us know. You know where to call. You bet. Okay, thanks to Alex Meyerson who's on production and manages the podcast and Ken Schiffman as well. Kristen Martin and Cheryl Knight, they help get the word out on social media and on our newsletters and Rob Hough is our editor-in-chief at SiliconANGLE.com. Thank you all. Remember, these episodes are all available as podcasts. Wherever you listen, just search Breaking Analysis Podcast. Please subscribe. I publish each week on wikibon.com and siliconangle.com. You can email me at david.volante at siliconangle.com or DM me at dvolante or comment on my LinkedIn posts and please do check out ETR.ai. They're accelerating their investments. They do so many surveys like this, like this flash survey and also an emerging tech survey that they've accelerated the pace of that in addition to the technology spending intention survey which we quote and referenced so much here on Breaking Analysis, best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching everybody and we'll see you next time on Breaking Analysis.


So, in today's session, we will continue our discussion on the theory of cost, where towards the end of theory of cost, which talks about the and the economic of scale and the economic of scale. If you remember, in the last class also we discussed the basis for that, why there is a use of long run average cost curve. So, in the previous class, we discussed about different cost analysis like short run and long run cost analysis. Then we discussed that, why long run average cost curve is use of what is the evidence of economic of scale and the economic of scale and in the different kind of average cost. Then we talked about the contribution analysis specifically the PV ratio and then we talk about the learning curve, if you look at that is the other way to analyze the long run average cost curve. So, in one case we say that, when there is a economic of scale, long run average cost curve is use of, because there is a economic of scale and this economic of scale, whereas in case of learning curve, the long run average cost goes on decreasing and there is no point where it increases again. So, in today's class, we will focus more on the or mostly on the economic of scale, different type of economic of scale, how the large firms or how the large production amount brings some cost advantages and that is how the firm produce at a lower cost production, that is how we are going to discuss today. So, the focus or the session coverage is application of the cost analysis, we will take some of the cost function, the empirical determination of it and then we will talk about the economic of scale. So, application of cost analysis, if you look at this is the in the first case in case of optimum output level, we generally use the cost analysis to identify what is the optimum output level. So, optimum output has the reference to that level of that level of size of output, which minimizes the average cost of production and therefore, which the average cost is equal to the marginal cost. We have discussed several times this optimal production or optimal output, optimal output is one which can be produced at a lowest minimum cost, that is the basic understanding of the optimal output. And here if you look at optimal output is that level of output which minimizes the average cost of production, because here we are trying to fit the optimal output taking the constant as the average cost of output. So, optimal level of output is one which produce that level of output which minimizes the average cost of production or may be the another condition for is that where the average cost is equal to the marginal cost. So, we will just take an example that how to find out empirically taking a typical cost function, how to find out the optimal output level which minimize the average cost at that point of time. So, if we will take a cost function like that is total cost is equal to 128 plus 6 Q plus 2 Q square. If this is the cost function then in order to find average cost as we know this is total cost divided by Q. So, this is 128. So, generally when we find this average cost we generally divided by the unit of output. So, this is 128 by Q plus 6 Q Q plus 2 Q square Q. So, that comes to 128 Q plus 6 plus 2 Q. So, this is the average cost, this is the average cost for the cost function. Now, to find out at which point average cost is minimum we need to take the first order derivation that is first order derivative of average cost with respect to Q. And if you equalize that equal to 0 then this comes as 128 Q square plus 2 which is equal to 0. And if you summarize or simplify it again we get Q is equal to 8. Now, how do I interpret this Q is equal to 8. So, when we know that average cost is minimum, average cost is minimum mathematically we can find out that by taking the first order derivative of average cost with respect to Q. If you take this with respect to 120 Q plus 6 plus 2 Q in this case we get a Q value of Q which is equal to 8 and value of Q if it is equal to 8 then this is the level of output where the average cost is minimum. Now, let us understand the same cost function taking in term of the marginal cost or when we find out the marginal cost and equalizing the marginal cost and average cost again whether we get the same level of output where the cost of production or the where the average cost is minimum. So, taking the same cost function again suppose this is total cost is equal to 128 plus 6 Q plus 2 Q square here we will find out the marginal cost and how to find out the marginal cost generally we will take the first order derivation of total cost with respect to DQ. So, in this case how do you find out this? So, this term becomes 0 D 128 plus 6 Q plus 2 Q square as compared to with respect to DQ. So, if you do this then this term is equal to 0 calculus. So, this is equal to 6 and this is equal to 4 Q. So, 6 plus 4 Q is our marginal cost. We have average cost we have average we have marginal cost. Now, if you equalize this average cost is equal to the marginal cost then in this case what is the value we are going to get? As we know the average cost is 128 Q plus 6 plus 2 Q because this is nothing but T C divided by Q which is equal to 6 plus 4 Q. So, if you make a equalization of average cost and marginal cost and simplify this then again we get a value of Q which is equal to 8. So, Q is Q 8 is what? Q 8 is the optimum level of output Q 8 is the optimum level of output where average cost is minimum and we can say that this is a short run cost because we have some amount of 128 over here. So, what is this 128? 128 is the total fixed cost and if you remember we get the amount of fixed cost only in case of short run. So, since it is a case of total fixed cost we can say this is a short run analysis. In case of short run cost analysis Q 8 is the level of output or 8 is the level of output where the average cost is minimum. So, the point here we want to focus is that what is the role of this average cost, marginal cost or total cost or how it helps in taking the economic decision, business decision or how it helps to generally using it for the different kind of economic analysis. So, for to summarize this we can say that optimum output level is 1 where the average cost where the cost to be minimum and that we can check from a cost function by taking out the average cost, marginal cost and solving the value for the Q. So, next we will say this optimum cost analysis in case of the optimum inventory level. So, when this concept of inventory comes generally, inventory comes if all the production are not immediately sold and if you look at whatever is produced and whatever is sold there is a gap in between and the gap whatever the amount that generally goes to the warehouse that is generally go to the stock and in economics term we called it as inventory because that is the stock kept in the warehouse which is not coming to the open market for getting sold. Now, how to define the optimum inventory level? Optimum inventory level is defined as the size of stock for which the average cost of inventory is minimum. So, if you look at it is just generalized into the same concept of optimum output level is generalized into the optimum inventory level and what is an optimum inventory level? The size of the stock or the size of the inventory where the average inventory cost is generally minimum. So, the way we analyze the optimum output level that is that is the level of output where average cost is minimum. Similarly, here it is the level of stock where the average inventory average cost of inventory is generally minimum. So, let us look at how to find out the optimum inventory level. So, there are two types of cost involved over here one that is carrying cost generally it includes the storage cost, interest cost on borrowed capital to finance stock etcetera and second type of cost is reorder cost which includes the book keeping cost, telephone charges and some variable cost. So, there are two kind of costs are involved in case of a when we are finding out the optimum inventory level one is the carrying cost and second one is the reorder cost. Both has to be the part of the cost function when we are finding out the optimum inventory level. So, how to find out the average cost of inventory? The average cost of industry is K multiplied by D by 2 plus F plus V plus D S divided by T. So, the first part of this equation is carrying cost and the second part of this equation is the reorder cost. Now, we will see what is the terminology stands for? S is the expected cell D and why we are taking the expected cell? Because that will tell us that which has which is the what are the amount is that is going to be sold and what are the amount that is going to be stock or that is going to be in the inventory. So, S is the expected cell, D is the order quantity to be delivered and D is the number of orders delivered, F is the average fixed cost of delivery, V is the coefficient of ABC of reorder and K is the average carrying cost. So, if we look at this average cost consists of both carrying cost and reorder cost and different types of cost either coming under carrying cost or reorder cost that is added in the equation. And what is D by 2 that is the average inventory held between initial and terminal period and it is assumed to that the demand is spread generally evenly. Because this is since we need to find out what is the average inventory cost we also need to find out the average inventory level and that is the reason we bring this D by 2 variable into our average cost function and D by 2 is the nothing but the average inventory held between the initial and terminal period and it is assumed that the demand is spread evenly. Now, to find out the optimal inventory level held at any point of time generally we do the first order derivative that is for average cost has to be equal to 0. So, DAC with respect to D. So, if you take a first order derivative of average cost with respect to capital D then it comes to K by 2 minus F S D square which has to be equal to 0. If you simplify this for the capital D that is root 2 F S by K and this gives us the optimum size of stock or the economic order quantity. So, popularly this is known as the economic order quantity and this is the optimum size of stock. So, D how do you find it generally we take the average cost that is the first order derivative the we take the first order derivative of the average cost with respect to the capital D equal as it to 0 and then we solve it for D capital D and that gives us the optimum size of the stock or that gives us the economic order quantity. So, that D comes out to be root 2 F S by K. Now, we will look at the application of cost analysis in case of the optimum scale. In the first case we talk about the optimum output how this cost analysis is used in the optimum output. Then we check that how this cost analysis is used in case of optimum inventory level. Then we will say to identify the plant size to identify the scale of operation that is the what should be the optimum scale, what should be the optimum size, what should be the optimum level where the firm should operate and we will see how the use of cost analysis is being there. So, the optimum scale is given by the value of K that is plant size at which the total cost is list. So, if you look at there is a significant difference here from the application of cost analysis here in the last two cases that is optimum output and optimum inventory because in previous both these cases we identify that level of output or the level of stock where the average cost was minimum. But here we are saying the optimum scale is given by the value of K or the plant size at which the total cost is the list. Now, what is the necessary condition for this optimum scale? The necessary condition for this optimum scale is D C by D K has equal to 0 that is also known as the first order condition that is D C by D K has to be equal to 0. So, first order derivative essentially has to be equal to 0 and sufficient condition is D square C by D K square greater than 0 that is the second order condition where it has to be greater than 0. Now, we will take an example to understand that how to use this cost analysis in order to identify the optimum scale. So, let us take a cost function that is C minus C is equal to 0.04 Q Q minus 0.9 Q square plus 11 minus K Q plus 5 K square. Now, what is the first order condition? The first order condition is D C by D K has to be equal to 0. So, if you do that then D C by D K will come to the first term will be 0, the second term will be 0, the third term will be 0 and the fourth term will be 10 K. This has to be equal to 0. So, 10 K is equal to 10 K is equal to 0 and K is equal to, so if you look at K is equal to 0.1 Q. So, first order condition from that we find out that K is equal to 0 and what is our first order condition? First order condition is D C by D K is equal to 0. Now, we will look at the second order condition and the second order condition says that D square C by D K K square has to be greater than 0. So, in this case if you take this then the first order derivative, the second order derivative then we get it equal to 10 which is greater than 0. So, if K is equal to 0.1 Q that is from the first order condition, this is from the second order condition. So, we can say that both the conditions are getting fulfilled that is the first order that is D C by D K has to be equal to 0. The first order derivative has to be equal to 0 and the second order derivative has to be greater than 0. So, in this example whatever we are looking at now we are getting both this condition get fulfilled and we can say that the K is equal to 0.1 Q and how to interpret this? If the firm is to produce, if the firm wish to produce 10 units, optimum scale is 1 and if the firm wish to produce firms wish to produce 50 units, the optimum scale has to be 5 because K is equal to 0.1 Q and what is K? K is the scale of the plant or the size of the plant. So, this is the first question. This is how the application of the cost analysis in case of the optimum level of scale, identifying the optimum scale. So, if you look at the cost analysis whether it is average cost, whether it is marginal cost, whether it is total cost, in all these cases generally it is getting used when the business decision has to be made irrespective of whether this is related to output, whether this is related to inventory or whether this is related to the scale. Next, we will move to the topic that is economies of scale and I think we have just introduced the concept of economies of scale in our previous session. When we are curious enough to know that why the long run average cost curve initially decreases then reaches the minimum and beyond that if the still the scale of operation of the firm is going on or still the production is going on, then the firm generally the average cost generally increases. So, let us understand this economies of scale in details, what are the sources and what are the types of economies of scale and how generally the firm gets advantage out of it. So, how do you define the economies of scale? This is the advantage of the large scale production that results in lower unit cost or you can say that this is the advantage of large scale production that results in the lower average cost per unit and mathematically how do you find that the average cost is t c by q and economies of scale if you look at it spread total cost over a greater range of output because whatever the total cost that is initially decreasing then it is reaches minimum and increases. It means the total cost is not at any point of time generally it spreads over the greater range of output and that is why we experience decreasing cost, we experience cost and average cost and also we experience the increasing average cost. There are two type of economies of scale, one is pecuniary economies of scale and this type of economies generally realize from paying lower prices for the factor used in production and distribution of the product due to bulk buying by the firm as size increases. So, here it is about paying a lower input price whenever we pay lower input price we generally experience the pecuniary economies of scale or we get advantage in term of pecuniary economies of scale. So, when the price is being paid less for the input using the inputs we generally experience the pecuniary economies of scale that we discuss in a later point of time after we discuss about the real economies of scale. But for the time being the understanding for pecuniary economies of scale is it is not about using less quantity of input rather it is the less price what we pay for the input. Then the second time is second type of economies of scale is real economies. So, real economies associated with a reduction in the physical quantity of inputs, raw materials various types of labor and various type of capital. So, pecuniary economies if you remember what we discussed just now they are not using less input rather they are paying a lower price for the inputs when the scale of operations increases and that is how they are getting the advantages or that is how they are generating the economies of scale. However, in case of real economies it is the reduction in the physical quantity of inputs, raw materials various type of labor and various type of capital. So, there will be reduction in the quantity of input, there will be reduction in the raw materials, there will be reduction in the labor, there will be reduction in the capital and if this happens when the scale of operation increases then only we can say that the firm is enjoying the economies of scale. So, we will discuss this in detail this real economies and there are generally four type of for four category of the real type of real economy or the real economies is divided into four category. One is production economies, second one is the selling and marketing economies, third one is the managerial economic and fourth one is the transport and the storage economies. So, we will start our discussion with the production economies that is under real economies, how generally there is a production economies of scale and production economies generally it may arise from the factor that is either from labor or from the fixed capital or from the inventory requirement of firm. So, the advantage under production economies of scale either it comes from labor or it comes from fixed capital or it comes from the inventory requirement of the firm. Now, when you say that production economics comes specifically from the labor, let us identify the factor what happens with respect to the labor input that generally the firm gets advantage out of it. So, when you categorize again the production economies into the labor economy, these are the factors because of what generally the firm gets some cost advantage or firm generally may be use less of the labor in order to produce the same level of output when the scale of operations increases. So, the first factor here is specialization, second is time saving, third one is the automation of production process and fourth one is the cumulative volume economies. So, we will discuss the specialization first and if you look at the subcategory, this is part of real economy which is again comes under the subcategory of production economy, again comes in the subcategory of labor economic and then it comes to the specialization. So, large scale allow division of labor generally because the number of labors are more that allows the division of labor and that led to the specialization of labor force with the result of the improvement of the skill and hence the productivity of the various type of labor which results the saving in the time usually lost in going from one type of work to another. So, if you look at in case of large scale the pool of labor force is more. So, each the pool of labor force is divided into the different group and they have assigned a specific task and that is how the division of labor on the basis of their skill, on the basis of their expertise and in this case what is the advantage? The advantage is that if use the laborer skill is fit into the work they will do a better work or they will perform in a better way which result in the improvement of the skill, result in the productivity of the labor because they are doing a work which is more suitable to them according to their skill and that leads to more productivity and the decrease in the time required to do the work and that is the reason if you look at in case of large scale since the division of labor is there that leads to specialization of the work of the labor force and finally, that leads to the efficiency of the or the productivity of the labor and there is a less of time and that is bring the cost differential to the firm and the average cost generally comes down. So, the first factor what we have analyzed is the production economies in case of labor economics, specialization is the specialization of labor of the division of labor is one generally where we the firm or the producer in general they get some advantages. Then we will talk about the second factor under labor economy that is time saving. So, division labor apart from increasing the skill of the labor force results in saving of time usually lost in going from one time to one type of work to another type of work and that time again brings some productivity because there is no loss of time the same time is getting utilized for the productivity of the labor. So, if you look at division it is related the division of labor in time saving in case of small scale firm how it how they do not get an advantage of time saving because the same group of people either they have to work here or they have to work there because there is not a different group to specifically work on project one, project two or project three because it is a small operation. But in case of large operation it is possible to divide them according to their skill according to their expertise and in that case they get the advantage in term of productivity and in term of the time saving which brings the economies of scale to the firm. Then we will talk about the automation of production process how it generates the how it generates the advantage to the firm. So, division of labor promotes the invention of tools and machine which facilitate the supplement the worker. So, if it is they are working a working on a project which fits to their skill they are fit to their expertise generally that again promotes the invention of tools and machine which facilitate the supplement the worker. So, mechanization of the production method in large plant increases the labor productivity and leads to decreasing cost as the scale of output increases. So, whether it is a automation of production process whether it is a mechanization of the process itself that takes that reduces the time that that increases the labor productivity because they are not doing it manually then now the production process is become automated and what is the final outcome final outcome leads to the decreasing cost as the scale of output increases. And if there is a decreasing cost that is nothing but the economies of scale what the firm is enjoying. Then in case of production economies of scale in the sub category of labor economies scale we have one more one more point or may be one more focal points where which brings some advantage to the firm that is cumulative volume economy. So, with the increase in the scale there is a cumulative effect on the scale of the technical personnel in particular. So, there is a increase in the scale and which leads to a which brings a cumulative effect on the scale of technical personnel in particular. So, production engineer, foreman and other production employee tend to acquire considerable experience from the large scale operation. So, cumulative volume experience leads to higher productivity and hence to reduce cost at a larger level of output. Now, what is this cumulative volume economy? Suppose you are working on a specific assignment specific task in a smaller way. When the production operations increases, when the size increases you are contributing to a larger scale and that again increases the higher productivity at that again leads to the higher productivity of the labor. And that is the reason if you look at that again leads to again leads to decrease in the cost and improve the efficiency and productivity of the firm. And that is how we can conclude that the cumulative volume experience leads to higher productivity and hence to reduce cost at a larger level of output. So, then we will come to the second type of production economy that is the technical economy. So, if you remember when we discuss about the production economies of scale, it started with the fact that production economies of scale either come from labor or comes from the fixed capital or from the inventory. So, in the first case we discuss about the labor economies of scale, where we discuss about the specialization, where we discuss about the time saving, where we discuss about the automation of production process and where we discuss about the cumulative volume economy. Now, we will see that there is one more point that is the technical economics that is a subcategory of production economy, where the economies are associated with the fixed capital which includes all type of machinery and other equipment. So, specifically technical economies is one where the producer gets the advantage, the cost advantage from the fixed input that is all type of machinery and other equipment or we can call it also fixed capital. So, it arrives either from specialization and indivisibility of capital or from the setup cost or from the initial fixed cost or technical volume input relationship or reserve capacity requirement. So, these are the factors from which generally with the firm or the producer get the technical economies of scale. So, let us analyze all these factors one by one. So, what is the first factor comes here? The first factor comes here is the specialization and indivisibility of capital. So, technical economic result from the specialization of capital equipment which becomes the possible at the large scale of production and from the invisibility which are a character of the modern industrial technique of production. So, one if you look at the machine it is specific the assignment is specific by the machine. So, the it is like the specialization of the labor. Similarly, the specialization of the capital equipment or machine which becomes possible at the large scale of production not at the small scale of production and when it is possible at the large scale of production obviously, it leads to the productivity. It is from the the technical economies also comes from the indivisibility which are a character of the modern industrial technique of production. Because if you look at the machine as such a large that you cannot make them or you cannot divide them for in a small small way for the smaller level of output. Like typically the assembly line if you look at speed for a size you cannot make it a it is a part of it. Modern technology is as I said it is a higher degree of mechanization. Mainly it is a capital intensive production method because large scale of production we talk about the automation of production process. We talk about the high cap high and capital equipment. We talk about the mechanization we talk about the we talk about the high end technology that leads to the if you look at that is the part of the modern technology and if you look at these are all high overhead cost. But when it comes to the average cost it has the lowest average cost because there is in term of the productivity and in term of their performance. So, when it is a case of the low level of output higher average fixed cost is more than upset the lower level cost. So, initially when such a high end technology high end machinery high end may be the automation as a whole or high end about the capital equipment. This is the fixed cost is more specifically at a low level of output and the higher average fixed cost more than upset the lower level cost. But once the scale is reached once there is a large scale once the scale is reached and we can call it say appropriate scale the highly mechanized and specialized technique becomes profitable. Because why it is profitable because the in the large scale generally the fixed cost gets spread over the larger level of output and in general the unit cost comes down which leads to the economies of scale or the cost advantage for the firm. Then we will take out the second factor that is setup cost how it brings the technical economy. So, cost involved in the preparation of multipurpose machinery for performing the particular job or product that is generally the setup cost. So, cost involved in the preparation of the multipurpose machinery for performing a particular job or product and typically if you look at the example of a motor car industry or a firm producing the electrical household equipment in the use of general purpose machine is quite common because the setup cost is very high. So, if you look at if you again come down to a specific case like a metal stamping press which produces frames and the various component of the final product and the metal stamping press has to be reset anytime that a particular car has to be produced. So, setup cost is one which is generally required for the high end equipments and if you look at the typical example of a metal stamping press it has to be reset anytime that a particular part of car has to be produced. For example, different setups are required for producing the doors, the roof, the wings of a car and each setup involves a considerable time and cost. So, when it comes to setup cost if the if it is a case of only one car then again the average cost or the total cost is on a higher side, but if it is a case of the large scale output maybe it is a case of the number of cars the larger the scale of the output the more a multipurpose machine is left to one setup and hence resetting become less frequent which are the source of technical economies of scale. So, the understanding is that setup cost is required for the any high end cost or the high end capital equipment or high end machine, but even if it requires a setup for the different process different even intermediate product the cost is on a higher side, but once the scale of operation increases the larger the scale of the output the more a multipurpose machine is left to each to one setup and hence resetting become less frequent. So, one setup all door will get produced another setup wing will get produced or maybe another setup the frame will get produced. So, if it is large scale in one setup if the units are more the average the average setup cost goes down with each unit of output, but if it is a small plant or the small company where the unit of output is less in that case generally the setup cost cannot be spread over a larger amount of output and that is the reason the overhead cost for each unit of output generally on a higher side for a small scale, but larger scale they get a cost advantage because for one setup they produce a number of unit of output and which is a source of the technical economies of skill. Then we will talk about the next factor that is the initial fixed cost how initial fixed cost also we can we also get a cost advantage from the initial fixed cost of a large scale operation. So, it is usually involving starting a business or introducing a new product. So, if you look at what is the initial fixed cost fixed cost when either when you are starting a business you need you need a fixed cost you need a maybe the startup money or startup equipment or introducing a new product where the where the technicalities are different you need to get a maybe new type of capital equipment you need to get new set of manpower you need to use new technology. So, research and development expenditure the so typical example of fixed cost is research and development expenditure cost of market exploration design cost of the products are generally the comes under the initial fixed cost. So, these are all how it can be taken in case of a large scale operation larger the scale of output the lower the unit cost of such fixed expenses because it is spread over the different unit of output. So, larger the scale of the output lower the unit cost for such fixed expenses. Then we will take out one more factor under technical economic scale that is technical volume and input relationship. So, technical economy also arrives from some technical geometric relationship between the particular equipment and the inputs request to produce and install it. So, there are few important in the process industry like include special equipment such as storage tanks, reaction chambers and connecting pipes and in what context we are discussing this we are discussing this that what is the volume of output and what is the input relationship whether it is being cost advantage to the firm or not. So, if you look at there are few factor that is important in the process industry it includes special equipment such as storage tank reaction chambers or the connecting pipes. The material and labor cost for each this type of the inputs you can call it inputs the materials and the labor cost of constructing such plants are proportional to the surface area they occupy. So, it is proportionally the cost is proportional to the surface area and the volume capacity which determines the level of output of the plant increases more than proportionately as the area increases. So, material and labor cost their proportionality related to the surface area of the plant they occupy and the volume capacity which determines the level of output of the plant generally increases more than the proportionately as the area increases. Now, the technical cost of the unit capacity like whether you talk about the storage tank, whether you talk about any other reaction chamber the technical cost of unit capacity of installing such industrial plant falls as the output capacity increases. At least up to the point where equipment becomes so large as to require stronger material and special construction in order to make the large plant shape. So, the larger the scale maybe the equipment whatever comes they also requires a stronger material and special construction in order to make the larger plant shape and there they get the cost and advantage because the scale of operation increases. Then the we will come to the last factor under the technical economy and this is the reserve capacity requirement. So, firm always wants some reserve capacity in order to avoid the disruption of their production flow when breakdown of machinery occurs. Now, what is the need of this reserve capacity requirement? The reserve capacity generally cap because if in case of machine breakdown, in case of maybe labor force strike, in case of any eventuality at least the flow of the goods and services should go to the market and that is how the all the firms they keep some amount of the capacity as reserve and we will see that from the reserve capacity requirement how the economies of scale is generated. Firm always wants some reserve capacity in order to avoid disruption of their production flow when breakdown of machinery occurs. So, there may be a possibility of disruption of their production flow maybe because of failure of draw material, failure of technology, failure of machine where the breakdown of machinery generally occurs.  Because there is only one large machine which produces the entire requirement of the small firm. Now, for the reserve capacity requirement what they have to do? They have to keep another large machine as the backup. But in case of large scale how it works? In case of large scale anyway there are number of machines. So, if there is a breakdown in one the production flow never stops there generally it goes because the other machines are the maybe the other machines they are still producing the product. So, in this case the reserve capacity requirement is comes from all the machine not from a single machine. So, in order to keep the reserve capacity requirement a small firm has to invest more in order to keep one large machine again as the backup in case of the breakdown of the machinery. But in case of large firm since there are number of large machinery already in place if there is no need to keep the reserve capacity requirement or there is no requirement for the reserve capacity. Because if one machine breakdown the whatever the production comes from that machine can be taken from the other machine either by over producing or maybe increasing the quantity whatever they are producing. And in this case if you look at the cost of production decreases because it is not that you need to do again it is a initial fixed cost variable cost to run that machine or maybe you are not getting a loss because there is a decrease in the output rather that is getting cover in the other machine. And that is why there that is another source of technical economics that comes from the reserve capacity requirement to the real economies of scale. Then we will talk about the third source of production economics of scale. And what is the third source of production economics of scale? If you remember production economies of scale comes either from labor or from the capital or from the inventory or from the inventory. So, we can call that now we will check the third one that is the inventory economy. And this inventory economy also called as a stochastic economy. And why it is called as stochastic economy? Because the role of inventory is to meet the random changes in the input and the output side of the operation of firm. This is called as stochastic economy because what is the role of inventory? The role of inventory is to meet or the capture the random change in the input and the output side of the operations firm. It is not maybe the regular maybe it is a random kind of thing. So, stock of raw material do not increase with scale, but not proportionately. Stock of raw material increase with scale means if you are producing 100 units, you keep 10 units as the stock of the raw materials. If you produce 1000 units, obviously you need to keep some amount which is more than 10 units as the stock of raw materials if your production capacity or if the production level is 1000 units. So, the point here is the stock of raw material do increase with the plant size, but not proportionately. So, ideally what would have been situation? If 10 units as the stock for 100 units of output, then 100 units would be stock for 1000 units of output. But in reality that does not happen, it increases from more than 10, but it never reached 10 because it is not proportional increase in the with the scale of the with the scale of the output. So, random fluctuation in the supply of such input are generally smoothed out with the stocks which size need to change less than the size of the firm. And when it is possible, this is possible in case of a large scale operation. So, stock of raw material increases, but not proportionately, but if there is a random fluctuation in the supply of such input, supply of such raw material that smooth out with stock which size need change less than the size of the firm. And this is only possible in case of large scale and that is how we get a economic of scale or we get the advantage of economic scale in case of the inventory economy. Now, what happens on the demand side? Random changes in the demand of customer will tend to be smooth out as the plant increases. So, random changes in the supply can be taken from the stock of the raw materials. And on the demand side, random change in the demand of the customer will tend to be smooth out as the plant increases. The larger the number of customer, the more random fluctuation of the demand tends to upset the peaks and recession thus allowing the firm to hold a smaller percentage of its output to meet the random changes. So, if you look at when it comes to the demand side, it is not either at the peak or at the low. So, when you when you average out the peak and low random fluctuation from the demand side, ideally firm should not keep the stock on the basis of either peak or from the boom. And in this case, it generally average out the fluctuation on the higher side and fluctuation on the lower side. And that leads to or allowing the firms to hold a smaller percentage of its output to meet the random changes, because the random changes can go in the positive direction and also can go in the negative direction. Then we will talk about the second kind of economies of scale that is selling and marketing economy. So, the under real if you remember the types of economic one is real economy, second one is the pecuniary economy. And under real economies, we talked about the production economies, we talk about the we will talk about the selling and marketing economy. And in case of production economies, we talked about the technical labor economies of scale, technical economies of scale and inventory economies of sale, because production economies of scale generally come from the labor capital equipment or the inventory of the firm. So, in case of second case of the economies of scale under real economies of scale, this is selling and marketing economy. Selling and marketing economy generally associated with the distribution of the product of a firm. It comes from the advertising economies of scale, not only new firm also existing firm. So, when we talk about advertising, it is not about only for the new firm, but also for the existing firm. Why advertising is also for the existing firm? Because when the existing firm either they launch a new product or for their existing product to keep fresh in the memory of the consumer at least to certain point of the certain level of advertisement. So, this advertisement cost is also applicable to the existing firm who are launching a new product or for the existing product, if there is some updates or just to keep fresh in the memory of the consumer. So, advertising space and time increases less than proportionality with scale. So, advertising cost per unit of output falls with the scale and advertising budget is usually decided on the basis of available firm profit similar activities of competitor rather than on the basis of output. So, advertising space and time increase less than proportionately with scale. So, that leads to the per unit cost of average advertising cost generally falls with the scale and larger the output smaller the advertising cost per unit. Because whether it is for one product maybe the advertising cost is on a higher side, but when it is more more kind of product it comes from one company they just do a one company maybe campaigning kind of thing and that takes care of the product whatever is getting produced by the company or the other way if the advertising cost is for the lower unit of output even if it gets spread still the average cost is on a higher side, but when it gets spread over a longer spread over a longer or the larger level of output generally that average cost comes down because the advertising cost remains same irrespective of whether it is for 100 units or whether it is for the 1000 unit. But when it comes to benefit always the economies of scale comes from 1000 units of output not from the 100 units of output. Similarly, if we look at there are some other activity like other selling activity like salesman force the distribution of sample etcetera such small scale promotion expenditure increases by less than proportionately with output at least up to a certain scale in case of the large scale output. Then there is a third factor that is selling and marketing economics that is the economics from spatial arrangement with exclusive dealer. So, large firm can enter the exclusive agreement with distribution who undertake the obligation of maintaining a good service department for the product of manufacture. So, automobile industry where the dealer builds up the garages and the keep regular stock of the spare parts of various models the buyers of durable pays lot of attention to the availability of spares and good servicing shop for the brand they buy. So, if you look at in case of exclusive arrangement with dealer that leads to some reduction in the cost of production because the dealer is taking care of the some after sale service what has to be either has to be taken care of the by the firm itself. Then we talk about one more factor that is model change economy and if you look at there is a need to change the style of the product to meet the demand of customer which is ever increasing and the completion competition with the rival firms which involves considerable expense of R and D and new materials and equipment because you need to change the model you need to change the style. The spreading of such overhead is lower per unit if the scale of output is larger even if the initial fixed cost is high even if the capital equipment even if the raw material even if the labour require is high but the cost gets spread for a larger unit of output and that brings some economies of scale to the some economies of scale to the firm. If you look at there is a general agreement that large scale marketing in case of generally large scale market economy do exist but at least up to a certain size of plant. But there is some amount of disagreement exist as to whether the average selling cost curve turns at very large economies of output or whether the unit selling cost fall continuously with scale. So, given the technical cost of production falls with the scale the total average cost may eventually turn upward if selling this economy do exist after a certain plant size. So, we will stop here today and we will discuss in the next session about two more type of economies of scale that is managerial economies of scale and transport and storage economies of scale. Then we will spend some time on the pecuniary economies of scale and we will check that whether this economies exist at any point of time for a specific plant and if it it exist if this economies exist maybe what are the factors or what is the reason behind this. Then we can continue our discussion in the next session the whatever the part left in the economies of scale.


Nama Jesus Christ Maitama Jesus Christ Nama Jesus Christ She has snake spirit She keeps seeing this snake coming to her in the name of Jesus Christ So a snake keep coming to her That's what is giving her disappointment Come on Nama Jesus Christ Nama Jesus Christ She is free We thank you so much for being here and can you please tell us your name and where you from My name is Stacy and I live in Longview, Georgia And can you tell us, can you confirm that this prophecy is it true? It is true It is true that you had a spirit of snake operating in your life Can you tell us how do you know that that spirit was operating in your life? For the last couple of years I've been seeing the snake Every day in my dream You said that you've been seeing a snake in your dream for a couple of years And every time and then my husband's business and my business collapsed So for how long was your guys business collapsed Your husband and your business collapsed For how long? For a couple of years now Can you tell us after you got up after he prayed for you what did you feel, how do you feel right now after receiving prayer just last night? I feel really joyful and really happy It's just like love the Lord so much Can you tell us, did you feel happiness before did you feel an easiness did you feel heaviness before and what do you feel like now?  Yes Can you tell us do you believe through this prophecy that you have received deliverance and a breakthrough in your own personal life and in your husband's life? I believe Amen Give her a hand of applause


T. F. N. N. Headline news update. Good afternoon, folks. Steve Rhodes coming to you live from the shores of sunny Delray Beach, Florida. This is your 2 p.m. update and we've got a Fed decision that is imminent out here. So we should see quite a bit of market action here doing this two o'clock hour. So definitely stay tuned for David White's show. So what is it that we're looking at? What are you going to be observing today? I'm just simply going to switch over and take a look at, oh, I didn't realize I had my screen on. Take a look at the ES mini. We're going to look at the ES mini for signals. So the signal that you're looking for, the first one, with regard to busting itself to the upside, that's the market. If the ES mini, come on, open up.  Okay, there we go. So the level to be watching here, wow, we just got the bullish test that we had talked about during the last hour. So this is a 60 minute chart. I believe the 60 minute chart is the most relevant chart for what's going on inside the ES mini right now. So we talked about when the oscillator and change line changes color, as it did back here at about 11 o'clock this morning, that you typically see price in that line catch up to each other. Right now that's what's going on. Look, this is a 60 minute chart here. The bar that we're in just started a minute ago. But watch that, right now the signal is, that's a bullish signal. The real bullish signal is a close above 4, 3, 9, 3, 7, 5. In fact, two, two closes above that are then gonna suggest to move up to 44.33 or 44.66. If the market responds poorly to Powell's decision, then that would suggest that price will pull back to 43.28 and 42.93. A close below 42.93, it's curtains. Says that we continue to head lower. So those are the levels to be watching right now. If the market had closed here right now, what the daily timeframe chart is signaling is a bullish reversal candle. Let's see if we can expand this chart out to confirm it's A to B equal CD down to the downside. Actually what it confirms is a Gertley buy pattern out here. So you've got your three river morning star, the A to B equal CD pattern out here kind of looks something like this. I believe this is more than a one to one out here. That doesn't matter. You really need, in order to confirm a buy the D point or a Gertley pattern is a control seat policy. Just trying to do it. Doesn't look like I'm going to get this done in time. But there would be your A to B, the CD in essence. And this is your reversal signal. That would suggest that price will move up to the 44.45-ish area. Hey folks, do me a favor, stay tuned. David White's up next. Have a wonderful Wednesday. Tune in tomorrow at one o'clock for the Trader Zed show. And I'll be waiting for you then. Take care.


Agriculture has transformed the planet. We use more than a third of the Earth's surface to grow crops and raise livestock. About 70% of global water withdrawals are for agriculture, and our food systems are implicated in up to a third of anthropogenic greenhouse gas emissions. Each of these dimensions of global agriculture is now being influenced by globalization. Consider the meal pictured here. Depending on where in the world you live, the ingredients may have been sourced from very far away, including feed crops such as soy used to produce the meat. In many countries, the very ability to eat a food like avocado is a direct benefit of international trade. We are eating on an interconnected planet. Food trade now shapes land use worldwide and is reshaping the food supplies of many nations. With this agricultural globalization, food production and consumption are decoupled, making it more difficult to see cause and effect between our diets and the agricultural landscapes on which we depend. Growing global demand for certain commodities is now intertwined with local issues such as water scarcity, pollution and deforestation. In particular, commodity crops such as palm oil and soy have transformed land use in a few key countries where global production is now increasingly concentrated. What are the broader implications of this globalization in our food systems in terms of food security and resource sustainability? My lab at McGill University addresses this question by combining global data on trade and food supply statistics with different types of agricultural land use management data. An illustration of this food systems globalization is shown in this map here, which shows a network map depicting the global reach of the United Kingdom's calorie supply from imported agricultural commodities. The boxes on the bottom show a more detailed breakdown comparing each trade flow with domestic production of different commodities. Britain's particularly globalized diet links it with the diversity of farming systems and climates around the world. We're also studying these calorie import networks over time. These graphs compare the sources of Japan's calorie imports, which are concentrated and remain very stable over approximately two decades, to Saudi Arabia's, which are much more dispersed across many countries and change dramatically over this time period. The structure and composition of these food import networks moderates linkages between countries in terms of food and resources. By combining these global trade data with data on crop yields, fertilizer use, and water use, we can investigate how trade impacts the distribution of resource use across countries. What we are finding is that some countries are becoming increasingly reliant on foreign sources of land use underlying their food consumption outsourcing. With this, hundreds of millions of people are becoming reliant on potentially less certain sources of food and the resources needed to grow it. This trend is facilitated by other countries becoming more export-oriented in terms of their land use. Many of the countries pictured here in dark green use more of their domestic croplands for export production than for their own domestic food consumption. Other countries are even more highly globalized, essentially exchanging their export commodities for foreign imports grown on land use abroad. A shift towards specialization and concentration with globalization has fueled the emergence of disproportionately large and land-intensive trade relationships, such as pictured here for the global soy trade network. Just three countries produce and export about 80% of soy globally. Agricultural trade such as this can help to promote gains in average resource use efficiency in agriculture, reducing the amount of land, fertilizer, and water required to produce food calories on a global scale. However, the diversity of agricultural systems from which these imported foods are sourced means that these efficiency gains are not universal and may not occur for the same foods in the same countries. As food consumers, we're also increasingly urban. This compounds the challenges of globalization and separating us from food production landscapes. Our next step is to look at these global data through the lens of more local case studies to ask where globalization is beneficial and where instead we might strive for more of a middle ground model of regionalization. Part of navigating this is remembering that global food trade is not just about economics. In studying agricultural globalization, I've been learning that we can get a very different understanding of the structure and composition of global food trade networks using monetary, nutritional, or resource-based metrics. In the next few decades, it's projected that demand for food globally could increase by 60% or more, likely driving even greater separation of food production and consumption. In this time of change, we should envision what sustainable local and global food systems look like. How best can we all benefit from the diversity of agriculture on our planet in a fair, sustainable, and food secure way? Thank you.


Glenn Clark with Stevenson's all-time leading scorer, Sarah Tarbert, after a 63 victory over Stockton. Double-double tonight, 21 points. But as coach just told us, what she was most proud of, five assists for you. How pleased were you with the performance here tonight? Pretty pleased. I mean, I started off pretty slow. It was a rough start for me. But you have to give that to my teammates, though. They really hit the shots they needed. Johnny has been doing really good inside and out. So it makes teams respect her. And when I'm not hitting the shots, I'm just fortunate enough to be able to hit my teammates and rely on them to put those shots in. So you mentioned that slow start. You missed your first five shots. We don't see that from you very often. It seemed like from there there was a little bit of a determination to say, I'm not going to let that be the story of the night. Yeah, I mean, it's always frustrating when you do miss those first five shots. And they weren't like good misses. Some of them were pretty bad. But coach told me to keep shooting. My teammates told me to keep shooting. So I think they helped build my confidence back up. And I was pretty determined to try to at least get one in there. The 37-37 match in rebounding between these two teams, that's a really tough interior defensive team that you went up against. How much of that was that just a focus that you all had coming into the game? And how pleased are you that you were able to battle that way on the board? Yeah, I really think that we executed our game plan.  So I think all of us really bought into rebounding and making sure that they don't get those second shots. And 37-37, I mean, that's pretty good for us. And a lot of the second shots that they did get, I think we got just as many. So we were able to convert on those. Back-to-back wins, sort of a race of some of that taste of the four game funk, right? And headed back in the right direction? Absolutely, I mean, it was a tough four game losing streak. But I think that Messiah game really gave us a momentum that we wanted. And just fortunate we were allowed to convert on these two wins. Nice night for Sarah Tarbert. Sarah, congratulations on a big win. She's Sarah Tarbert. I'm Glenn Clark for gomustangsports.com.


Hey, Psych2Goers! Do you long for that perfect match? The person you know is the one for you. Perhaps you've leafed through pages of Cosmopolitan to find things that will assure you that the person you're with is your ideal partner. You talk to family and friends to make sure that your partner gets the okay. But despite the rigorous screening process, sometimes you break up with them. So how can you tell if you've found your ideal partner? To help you get the reassurance you need, here are 7 signs you have found the one. 1. The relationship is balanced. Balance is necessary for a long-term relationship. It needs flow. The most common example is a balance of personalities. One is extroverted, the other is introverted. But balance can also refer to chores and roles in the relationship. You'll notice if your relationship is balanced or not. If things go smoothly, you two naturally synchronize. 2. You both communicate effectively. To achieve balance in a relationship, you need to know how to communicate with each other. Communication extends beyond words. Communication is largely about subtext. What do we say when we aren't speaking? You need to clearly explain your thoughts in a way that the other person understands which can be harder than you think. Proper communication takes years of practice, but it's achievable and becomes easier when you know your audience, in this case, your partner. The other, perhaps more important, part of communication is listening, which is something we all need to learn how to do. Listening involves paying attention and being receptive to the feedback you're receiving. 3. You trust each other. No relationship, romantic or otherwise, works if you don't trust each other. There's no way around it. If you can't trust your partner or your partner can't trust you, the relationship won't work. Trust opens the door for vulnerability, respect, and intimacy. Eventually, these, along with other aspects, create love. These qualities of love manifest in different ways, from being supportive, respecting each other's alone time, and being affectionate. 4. You share the same values and try to achieve them as a couple. This also falls under having a balanced relationship, but sharing the same values also makes it easier to figure out where your relationship is going. An ideal partner will likely be heading the same direction as you are, and they'll want to be by your side on the journey. You and your partner should be on the same page about the big things, such as marriage, kids, and the future. 5. You also respect each other's differing views. It's alright if neither of you share similar opinions on ice cream flavors or holiday traditions. What matters is that both of you respect each other enough to agree to disagree. 6. You both value and keep your promises to each other. This ties in with whether you trust each other or not. This is vital in a relationship because it has the power to bind people, but also push them apart. Trust is fragile, so it's important to keep the promises you make to each other. Your ideal partner will strive to fulfill the promises they make to you. 7. You both are beyond aesthetics. The last sign that you found your ideal partner is that you're beyond aesthetics. Sure attraction is necessary to fall in love, and it does re-merge throughout the relationship. When you've found the ideal partner, you're not with them because of their looks, you're with them because you enjoy being with them. Because you've fallen in love with who they are, not what they look like. We all want to find the right person to spend the rest of our lives with, which explains the constant need for reassurance that we have made the right choice. But when you know, you know. Do any of these signs apply to your relationship? Do you agree with this list? Let us know in the comments below. And if you liked this video, share it with friends. As always, the references and studies are listed in the description below. Until next time friends, see you soon.