Let’s Netflix a bit


I have just returned from my summer holidays, and my mind wanders a bit. For me, going on holiday is a painful activity. Let’s face it: being on a holiday sucks. This is probably the reason why it is worth to go on a holiday. I know a woman, a really wise one, whom I once heard saying: ‘Real life starts when you get out of your comfort zone’. That’s deep. I can smell real wisdom here. I am the programmed kind: I like routines, I like scheduling and structuring my activity. Going on a holiday is bloody painful for someone like me. I need to reprogram, and I need to do it quickly, and it is stressful, and so it is good.

It is like six or seven years since I discovered that hoping for ‘rest’ and ‘relax’ on a holiday is just unreasonable. The whole point of taking some time off my ordinary routines is to do something different, the more different the better, and the more it sucks in terms of current adaptive effort, the more it benefits to my central nervous system.

I have been performing my current adaptive effort in Western Brittany, France, near the region’s capital Quimper. The first thing I needed adapting to was the astronomical, daily cycle. Longitudinally, the place is on the same meridian as Western England. It is almost like Ireland. Still, legally, the place is in the same time zone as my own country, Poland, i.e. in the Central European one. Result: the sun rises above the forest (I had one right in front of my window) around half past seven a.m., and it sets after nine p.m. My habitually programmed, neurological clock kicked into the ‘early morning’ mode when it was basically still night time outside, and it settled into the ‘night’ gear when there was still plenty of daylight.

The second type of daily cycle I found it hard to adapt to was of the gastronomical nature. Probably harder to catch on with than the astronomical. I am a big fan of intermittent fasting. Through laborious trial and error, over the last 11 months, I have found out that fasting like 16 hours out of 24 is just good for me, and the eight hours of eating would better to be in the morning and in the middle of the day. With that rhythm, I sleep well, I am in good shape, I stay sharp and alert, whilst keeping a lot of effortless self-control. Believe me, at the age of 50, it is all not as obvious as one could think.

Now, in France, breakfast at the hotel is served between 8.30 (sometimes 7.30) and 10.00 a.m. Lunch time in restaurants is from 12.00 until 2 p.m. Past 2 p.m. it is bloody hard to have a lunch served, save for McDonald’s, and for places with ‘Brasserie’ written over their doorstep. Dinner time starts at 7 p.m. You go hiking on those breath-taking cliffs of the Brittany’s seaside, you miss the ‘feeding window’ in restaurants, and you’re like out of the system. Just try to fast intermittently with that type of gastronomical culture. Good luck.

Anyway, I’m back. And I am joyfully sailing through the safely charted waters of my habits. I have been thinking a lot about my teaching, at the university. That holiday time in Brittany helped me to sort of drive it down to the bare essential. I can and should teach, most of all, what I am at least acceptably good at, and this is fundamental social patterning. I mean I can take the financial statements of a business and I quickly notice patterns in those numbers, and I deconstruct a business model out of them. Same with macroeconomic statistics. Very much the same with legal texts: I take a legal act, or a contract, and I start forming the pattern of alternative realities governed by various rules. During this holiday I have just reached the blissful end of, I noticed I tend to do it with people, as well. I am sitting in an airport, I have a glance here and a glance there and I start patterning people around me. I am having fun with trying to predict what the given person is going to do next, just on the grounds of my observation. Are they going to order coffee or orange juice, at the bar? This kind of thing.

What we call our mind works very largely like that. Unless you’re autistic, you instinctively group the instances of your sensory experience into categories, which you aggregate into even broader categories etc. This is called abstract thinking. It allows to see a forest where your basic wolf would just see a bunch of those-tall-not-to-bite-into-things-with-harsh-and-hard-on-them-and-spiky-around-them. In me, abstraction comes with a loop of introspection: I know I am abstracting and I am steering the process to some extent.

Thus, what I can teach, most of all, is that semi-intuitive patterning with introspection. As I am introspecting the process, I think I usually start proceeding with basic quantities. Whatever type of phenomena I deal with, I look for the biggest items in the first place, and then I go diminuendo (i.e. towards lower and lower sizes). If I wanted to represent the process analytically, like to put it into an algorithm, it is sorting associated sets. I have a set of values. I have it associated with a set of categories, matching one to one, i.e. one value with one category. I sort the values, from the biggest one downwards, and I infer about a hierarchy in the corresponding categories. Value A is greater than value B, and thus the associated category A’ is more important than the associated category B’.

In a consecutive step, I associated the ordered pair of associated categories (A’, B’) with more abstract a category, like ‘key assets’ or ‘value added’. I start identifying patterns of connection between those ordered categories. Should I add them up in order to have an aggregate, or maybe subtract them to nail down a residual? Wait, it could be like multiplying them so as to have a two-dimensional manifold. Still, dividing one by the other is tempting, too. I could have a proportion, then. Hmmm…

You see the general drift? Good, so let’s make it more specific, like into a structured teaching. I mentioned a few times that I teach fundamentals of management to the students of 1st year Undergraduate Film and Television Production. I guess I could base that teaching on the patterning of business models observable in the media and show business industry. Here comes a hurdle, however. I base my patterning of business models on the study of financial statements. This, in turn, requires elementary understanding of financials in themselves. Question: how can I teach that elementary understanding to people who, most probably, have never had any contact with those things, and probably don’t like maths at all.

Here comes the elementary wisdom of economic sciences: numbers have meaning regarding social phenomena, just as they have meaning in engineering or in art. When you shoot a photo of a waterfall, and you really mean art, you will look for different metrics (distance, breadth of the panorama, light filter etc.) that if you were shooting the photo of a dog playing with a ball. When you plan to make a video on You Tube, you will look for some metrics in, for example, the upload speed of your local Internet connection.

In business, numbers are frequently expressed in money, i.e. in the units of currency. Money is like a social hormone: it is being secreted, and it clusters in places and moments, where and when something important is happening. The amount of money present in a given place and time expresses the social value of things, i.e. the relative cost of doing something and the relative attractiveness.

Of course, you will say there are valuable things in life which are not measurable in money: love, peace, friendship, transcendence etc. Now, if you think so, just let’s make a short quiz. Where can you have more friends: in the middle of a thriving community or in a deserted warzone? Probably in the former. Where is there more money in circulation? Probably in the former. Next bus-stop: transcendence. Where do more people experience the feeling of transcendence: in the middle of a thriving community or in a deserted warzone? Probably in the former. Where is there more money in circulation? Probably in the former. Yes, money can’t buy love, but more love is likely to be found in thriving communities with monetary systems than in remote, lonely locations.

Thus, numbers describing the amount of money in a given time and place tell us a lot about the socially recognized, overall value of things that are going on in that time and place. This is socially ritualized information, and so it is generalized, distorted and it has holes in it, yet this is information.

Good. As we talk about Film and Television Production, let’s Netflix a bit. In order to understand how a business works, a good angle of approach is to identify the key resources they need, and the ways to collect capital for the accumulation of those resources. The type of financial statement that we use to grasp this aspect is called ‘balance sheet’. It is a T-account, i.e. it has two sides, and those two sides should be rigorously equal to each other. One side shows some inflow, or the source of a resource, and the other side shows the employment of that inflow. In a balance sheet, one side is called ‘assets’, and it shows how capital is being employed in a business. The other side is called ‘equity and liabilities’, and it shows the provenance of capital, respectively from direct ownership of the business (equity), and from borrowing (liabilities).

Here comes the balance sheet of Netflix, as presented in their Annual Report for the fiscal year 2017. In Table 1, a summary version of the balance sheet is presented. You can find the source table in the Excel spreadsheet attached to that annual report. This specific balance sheet seems to balance itself on one word: content. The resources (assets) of Netflix are mostly ‘content’, i.e. intellectual property rights to something you can broadcast or stream. On the passive side of the balance sheet, we have, in order, three categories: content liabilities, long-term debt, and stockholders’ equity. Content liabilities is the money you owe to people, whom you have sort of borrowed their content from, on the basis of a licence agreement.

Table 1 – The summary balance sheet of Netflix

As of December 31,
2017 2016 2015 2014 2013
(in thousands) (in thousands) (in thousands) (in thousands) (in thousands)
Cash, cash equivalents and short-term investments $2 822 795 $1 733 782 $2 310 715 $1 608 496 $1 200 405
Total content assets, net 14 681 989 11 000 808 7 218 815 4 939 460 3 838 364
Working capital 2 203 662 1 133 634 1 902 216 1 263 899 883 049
Total assets 19 012 742 13 586 610 10 202 871 7 042 500 5 404 025
Long-term debt 6 499 432 3 364 311 2 371 362 885 849 491 462
Non-current content liabilities 3 329 796 2 894 654 2 026 360 1 575 832 1 345 590
Total content liabilities 7 502 837 6 527 365 4 815 383 3 693 073 3 121 573
Total stockholder’s equity 3 581 956 2 679 800 2 223 426 1 857 708 1 333 561

Here comes the most fundamental business pattern in Netflix. You need content to be Netflix. You also need highly liquid financial assets (i.e. ‘Cash, cash equivalents and short-term investments’), as well as some working capital, but most of all you need rights to stream some content. It means that the most important activity at Netflix, like the most important business thing anyone can possibly do, consists in securing content.

Now, it is a good moment to ask a disconcertingly basic question: how is that value of content assets estimated? What is the financial value of one episode of ‘Walking Dead’, for example? In other words, what makes the recognized value of the most valuable resources in the Netflix business model? In the PDF version of the annual report 2017, I found a short note about the thing (page 48 of the PDF): ‘Streaming Content: The Company acquires, licenses and produces content, including original programming, in order to offer members unlimited viewing of TV shows and films. The content licenses are for a fixed fee and specific windows of availability. Payment terms for certain content licenses and the production of content require more upfront cash payments relative to the amortization expense. Payments for content, including additions to streaming assets and the changes in related liabilities, are classified within “Net cash used in operating activities” on the Consolidated Statements of Cash Flows.

For licenses, the Company capitalizes the fee per title and records a corresponding liability at the gross amount of the liability when the license period begins, the cost of the title is known and the title is accepted and available for streaming. The portion available for streaming within one year is recognized as “Current content assets, net” and the remaining portion as “Non-current content assets, net” on the Consolidated Balance Sheets.

For productions, the Company capitalizes costs associated with the production, including development costs, direct costs and production overhead. These amounts are included in “Non-current content assets, net” on the Consolidated Balance Sheets. Participations and residuals are expensed in line with the amortization of production costs.

Based on factors including historical and estimated viewing patterns, the Company amortizes the content assets (licensed and produced) in “Cost of revenues” on the Consolidated Statements of Operations over the shorter of each title’s contractual window of availability or estimated period of use or 10 years, beginning with the month of first availability. The amortization is on an accelerated basis, as the Company typically expects more upfront viewing, for instance due to additional merchandising and marketing efforts. The Company reviews factors impacting the amortization of the content assets on an ongoing basis. The Company’s estimates related to these factors require considerable management judgment.

The Company’s business model is subscription based as opposed to a model generating revenues at a specific title level. Therefore, content assets, both licensed and produced, are reviewed in aggregate at the operating segment level when an event or change in circumstances indicates a change in the expected usefulness of the content or that the net realizable value or fair value may be less than amortized cost. To date, the Company has not identified any such event or changes in circumstances. If such changes are identified in the future, these aggregated content assets will be stated at the lower of unamortized cost, net realizable value or fair value. In addition, unamortized costs for assets that have been, or are expected to be, abandoned are written off.

This passage tells us a lot, and I feel like cutting small bits out of that lot. You know, cutting with the Ockham’s razor. There is content that Netflix produces, the content it acquires. This is where content comes from. That content can be exploited in two ways: it can be sold directly to its final users, via streaming and Netflix, or it can be further licenced (or sub-licenced) to third parties, and streamed or broadcasted via their platforms. You can see it in the flow chart below. I like flow charts. Social scientists do.

Netflix business model content types 1

The balance sheet introduced in Table 1, plus the explanatory note supply some information as for the structure of the Netflix content business. We can see the word ‘content’ both in assets, i.e. in the resources of the company, and in the liabilities. Liabilities labelled ‘content’ are the estimated value of content acquired from external creators and streamed on the basis of a licence. Now, I divide the values disclosed in line labelled ‘Total content liabilities’ by the value of ‘Total content assets, net’. What I get is the relative share of royalties paid to external creators in the total value of content assets. Here are the results: 4          81.3% in 2013, 74.8% in 2014, 66.7% in 2015, 59.3% in 2016, and 51.1% in 2017.

In other words, the bigger Netflix becomes in terms of the total capital embodied in its assets, the greater becomes the share of its internally produced content, in relation to the externally acquired one. Here comes the next rule of that business model: the content you want is most of all your own. You can use the externally purchased one to make your platform more attractive, but the real money is in own creation. The provisional – and interesting – hypothesis is that there must be a lot of middlemen in that business, i.e. people who trade content, and add their margin at each transaction. The quite substantial amount of cash held in Netflix’s balance sheet corroborates this conjecture: if you want to buy content, or finance its production, at the best possible prices, you might need to advance cash quickly.

Good, let’s move away from ‘Walking Dead’ towards something more joyful and politically correct, i.e. towards the business of Walt Disney Co.  Below, in Table 2, you can find the consolidated balance sheets of Walt Disney Co. for 2017 and 2016.  I apply the same simplistic method of observation: I look for the greatest values on both sides of the balance sheet. In the case of this beast, big capital is counted in tens of billions of dollars. On the active side, surprise: the only two items in that range of magnitude are: ‘Attractions, buildings and equipment’ and ‘Goodwill’.

A bit of explanation is due as for that latter category. Goodwill might suggest someone had good intentions. Weeell, sort of. When you are a big company and you buy a smaller company, and you obviously overpay for the control over that company, over the market price of that stock, the surplus you have overpaid you call ‘Goodwill’. It means that this really expensive purchase is, in the same time, very promising, and there is likely to be plenty of future profits. When? In the future, stands to reason.

Anything that could be more or less directly associated to making movies and shows, like intangible assets (intellectual property etc.) or ‘Film and television costs’ is, quite surprisingly, much more modest in that balance sheet. On the passive side, the greatest value consists of ‘Retained earnings’. They make over 70% of the total capital accumulated by Walt Disney Co.

We have an interesting business model, here. You earn profits, and you retain them, and you use them to build attraction parks, as well as to buy smaller companies. If you want my opinion, whilst Netflix looked like a classical media business, Walt Disney Co. looks much more like an investment fund with two portfolios.

Table 2 Consolidated balance sheets of Walt Disney Co.

(in millions, except per share data)
September 30, 2017 October 1, 2016
Current assets
Cash and cash equivalents  $4 017  $4 610
Receivables 8 633 9 065
Inventories 1 373 1 390
Television costs and advances 1 278 1 208
Other current assets 588 693
Total current assets 15 889 16 966
Film and television costs 7 481 6 339
Investments 3 202 4 280
Parks, resorts and other property
Attractions, buildings and equipment 54 043 50 270
Accumulated depreciation (29 037   ) (26 849   )
Projects in progress 2 145 2 684
Land 1 255 1 244
Intangible assets, net 6 995 6 949
Goodwill 31 426 27 810
Other assets 2 390 2 340
Total assets  $95 789  $92 033
Current liabilities
Accounts payable and other accrued liabilities  $8 855  $9 130
Current portion of borrowings 6 172 3 687
Deferred revenue and other 4 568 4 025
Total current liabilities 19 595 16 842
Borrowings 19 119 16 483
Deferred income taxes 4 480 3 679
Other long-term liabilities 6 443 7 706
Commitments and contingencies (Note 14)
Redeemable noncontrolling interests 1 148  –
Preferred stock, $.01 par value
Authorized – 100 million shares, Issued – none  –  –
Common stock, $.01 par value, Authorized – 4.6 billion
Issued – 2.9 billion shares 36 248 35 859
Retained earnings 72 606 66 088
Accumulated other comprehensive loss (3 528   ) (3 979   )
Treasury stock, at cost, 1.4 billion shares at
September 30, 2017 and 1.3 billion shares at October 1,
2016 (64 011   ) (54 703   )
Total Disney Shareholders’ equity 41 315    43 265   
Noncontrolling interests 3 689 4 058
Total equity 45 004    47 323   
Total liabilities and equity  $95 789  $92 033

Still another jump, now, towards the respectable Discovery Communications Inc., the operator of Discovery channels. Table 3, below, introduces their balance sheet for 2017 and 2016. This particular case is interesting because of its dynamics more than its structure properly spoken. The company swelled like a balloon, over the fiscal year 2017. Its total capital, as registered in the balance sheet, has taken a shot of plus 44%, almost seven billions of dollars. Interestingly, practically all of that intake consisted of cash and cash equivalents. When businesses vacuum-clean the market of cash, as Discovery Communications has just done, it means they are up to something. Pardon, they are facing exciting challenges, which result in necessary strategic adjustments.

Here, with the case of Discovery Communications, we can see a media business whose activity seems to consist, very largely, of waiting for some opportunities to consume. On the passive side, this vigil is being financed by long-term debt. This is, in general, an interesting trait of those media businesses: they seem to be more debt-based than equity-based. In other words, their management seems to be more keen on dealing with lenders, than messing around with the stock market. It seems to be a recurrent characteristic of strongly project-oriented companies. I can see the same thing in a completely different fairy tale, that of aviation, with Boeing and Airbus.

Table 3 The balance sheet of Discovery Communications Inc.

December 31,
2017 2016
Current assets:
Cash and cash equivalents $7 309 $300
Receivables, net 1 838 1 495
Content rights, net 410 310
Prepaid expenses and other current assets 434 397
Total current assets 9 991 2 502
Noncurrent content rights, net 2 213 2 089
Property and equipment, net 597 482
Goodwill, net 7 073 8 040
Intangible assets, net 1 770 1 512
Equity method investments (See Note 4) 335 557
Other noncurrent assets 576 490
Total assets $22 555 $15 672
Current liabilities:
Accounts payable $277 $241
Accrued liabilities 1 309 1 075
Deferred revenues 255 163
Current portion of debt 30 82
Total current liabilities 1 871 1 561
Noncurrent portion of debt 14 755 7 841
Deferred income taxes 319 467
Other noncurrent liabilities 587 393
Total liabilities 17 532 10 262
Additional paid-in capital 7 295 7 046
Treasury stock, at cost (6 737) (6 356)
Retained earnings 4 632 5 232
Accumulated other comprehensive loss (585) (762)
Total equity 4 610 5 167
Total liabilities and equity $22 555 $15 672

I am consistently delivering good, almost new science to my readers, and love doing it, and I am working on crowdfunding this activity of mine. As we talk business plans, I remind you that you can download, from the library of my blog, the business plan I prepared for my semi-scientific project Befund  (and you can access the French version as well). You can also get a free e-copy of my book ‘Capitalism and Political Power’ You can support my research by donating directly, any amount you consider appropriate, to my PayPal account. You can also consider going to my Patreon page and become my patron. If you decide so, I will be grateful for suggesting me two things that Patreon suggests me to suggest you. Firstly, what kind of reward would you expect in exchange of supporting me? Secondly, what kind of phases would you like to see in the development of my research, and of the corresponding educational tools?

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Educational: microeconomics and management, the market and the business model

My editorial

This time, in the educational stream of my blog, I am addressing the students of 1st year undergraduate. This update is about microeconomic and management. Regarding your overall educational curriculum, these two courses are very much complementary. I am introducing you now into the theory of markets, and, in the same time, into the managerial concept of business model. We are going to consider a business of vital importance for our everyday life, although very much unnoticed: energy, and, more specifically, electricity. We are going to have a look at the energy business from two points of view: that of the consumer, and that of the supplier. If you have a look at your energy bill, you can basically see two lines: a fixed amount you pay to your supplier of energy, just for being connected to the grid, and a variable amount, which is, roughly speaking, the mathematical product: [Price of 1 kWh * Quantity of kWh consumed]. Of course, ‘kWh’ stands for kilowatt-hour. On the whole, your expenditure on electricity is computed as:

E = Fixed price for connection to grid + [Price of 1 kWh * Quantity of kWh consumed]

                             P1                                                                 P2                                 Q   

From the point of view of the supplier of energy, their market is made of N consumers of energy. We can represent this market as a set made of N elements, for example as N = {k1, k2, …, kn}, where each i-th consumer ki pays the same fixed price P1 for the connection to the grid, the same price P2 for each kWh consumed, and consumes an individually specific amount Q(ki) of energy measured in kWh. In that set of N = {k1, k2, …, kn} consumers, the total volume Q of the market is computed as:

Q = Q(k1) + Q(k2) + …+ Q(kn) [kWh]

…whilst the total value of the market is more complex a construct, and you compute it as:

Value of the market = N*P1 + Q*P2

  Most consumers have a more or less fixed budget to spend on electricity. If you take 1000 people and you check their housing expenses every month, you will see that their expenditures on electric power are pretty constant, unless some of them are building spaceships in their basements. So we introduce in our model of the market a budget on electricity, or Be, specific to each individual customer ki. Hence, that budget can be noted as Be(ki). Actually, that budget is the same as what we have introduced earlier as expenditure E, so:

Be(ki) = E = P1 + P2*Q(ki)

This mathematical construct allows reverse engineering of individual power consumption. Each consumer uses the amount Q(ki) of kilowatt-hours, which satisfies the condition:

Q(ki) = [Be(ki) – P1] / P2

In other words, each of us has a budget to spend on electricity bills, from this budget we subtract the fixed amount of money P1, to pay for being connected to the power grid, and we use the remaining sum so as to buy as many kilowatt-hours as possible, given the price P2. This condition is a first approach to what is called the demand function, on the part of the consumers. Although this function is still pretty sketchy, we can notice one pattern. The total amount of electricity Q(ki) that I consume depends on three parameters: my budget Be(ki), and the two prices P1 and P2. In economics, we call this an elasticity. We say that the quantity Q(ki) is elastic on: Be(ki), P1, P2. How elastic is it? We can calculate it, if we now the magnitudes of change in particular factors. If I know that my consumption of electricity has changed from like 40 000 kWh a year to 42 000 kWh, and I know that in the meantime the price P2 of one kilowatt-hour has moved from 0,1 euro to 0,12 euro, I can calculate something called deltas:

delta [Q(ki)] = ∆ Q(ki) = 42 000 40 000 = 2 000 kWh

delta (P2) = ∆P2 = €0,12 €0,1 = €0,02

The local (i.e. specific to this precise situation) elasticity of my consumption Q(ki) to the price P2 can be estimated, in a first approximation, as

e = ∆ Q(ki) / ∆P2 = 100 000 kWh per €1

The first thing to notice about this elasticity is that it is exactly contrary to what you see in my lectures, and what you can read in textbooks, about the demand function. The basic law of demand says something like: the greater the price, the lower the consumers’ willingness to buy. Here, we have something contrary to that law: greater consumption of energy is associated with a higher price, through a positive elasticity. I am behaving contrarily to the law of demand. In science, we call such a situation a paradox. Yet, notice that it is a local paradox: I cannot keep on increasing my personal consumption of electricity ad infinitum, even in the presence of a constant price. At some point, I have to start saving energy and increase my consumption just as much, as the prices possibly fall. So, generally, as opposed to locally, I am likely to behave in conformity with the law of demand. Still, keep in mind that in real life, paradoxes abound. It is not obvious at all to peg down a market equilibrium exactly as shown in textbooks. Most real-life markets are imperfect markets.

Now, if you look at this demand function, you can find it a bit distant from how you consume electricity. I mean, personally I don’t purposefully maximize the quantity of kilowatt-hours consumed. I just buy stuff powered by electricity, like a computer or a refrigerator, I plug it in, I turn it on, and I use it. Sometimes, I vaguely practice energy saving, like turning off the light in rooms where I am not currently staying. Anyway, my consumption of electricity Q(ki) is determined by the technology T I have at my disposal, which, in turn, consists of a set M = {g1, g2, …, gm} of goods powered by electricity: fridge, computer, TV set etc. We say that each j-th good gj, in the set M, is a complementary good to electricity. I can more or less accurately assume that an average refrigerator consumes x1(fridge) kWh, whilst an average set of house lighting burns x2(lighting) kWh. We can slice subsets out of the set N of consumers: N1 people with fridges, N2 people with air conditioners etc. With Q(gj) standing for the consumption of electricity in a given item powered with it, I can write:

 Q(ki) = N1*Q(g1) + N2*Q(g2) + …+ Nm*Q(gm) = [Be(ki) – P1] / P2

It means that, besides being elastic on my budget and the prices of electricity, my individual demand for a given amount of kilowatt-hours is elastic on the range of electricity-powered items I possess, and this, in turn, means that it is elastic on the budget I spend on those pieces of equipment, as well as on the prices of those goods (with a given budget to spend on houseware, I am more likely to buy a cheaper fridge rather than a more expensive one).

Now, business planning and management. Imagine that you are an entrepreneur, and you want to build a solar farm, and sell electricity to the people living around it. Your market works as shown above. You know that whatever you want to do, your organisation will have to satisfy the needs of those N customers, with their individual budgets and their individual elasticities in expenditures. The size of your organization, and its structure, will be significantly determined by the necessity to maintain profitable relations with N customers. Two questions emerge: what such organizational structure (i.e. the one serving to build and maintain those customer relations) would look like, and how could it be connected to other functional structures in the business, like building the solar farm, maintaining it in good technical state, purchasing components for construction and maintenance, hiring and firing people etc. You certainly know one thing: you have a given value of the market = N*P1 + Q*P2 and you have to adapt your costs (e.g. the sum total of salaries paid to your people) to this value of the market. Thus, you know that:

Average salary in my business = [(N*P1 + Q*P2) – The profit I want – Other costs] / the number of employees

In other words, the size of my business, e.g. in terms of the number of people employed, as well as my profit and the wages I can pay, will be determined by the value of my market. Now, let’s go along a path at the frontier of economics and management. I want to know how much capital I should invest in my business. I posit a condition: that capital should return to me, in the form of profits from business, in 7 years. Thus, I know that:

My initial investment = 7* My annual profit = 7*(N*P1 + Q*P2 – Current costs) = N*Be(ki) current costs = N*E current costs = N*[P1 + P2*Q(ki)] current costs

This is how the size of my business, both in terms of capital invested, and in terms of the number of people employed, is determined by, or is elastic on, the prices I can practice with my customers, the sheer number of those customers, as well as on their individual budgets.