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Lecture – 07
Business Models

(Refer Slide Time: 00:16)

Welcome back for the next session. We were discussing laws of manufacturing in the
previous one and the main concept which we concluded the session with was the
economies of scale. So, I will continue my discussion and I may emphasize now
economies of scope. This paper is one of the initial papers, we can say Economies of
Scope by Panzer and Willig.

The main idea here is if I have two products, then

TC (x1, x2) < TC (x1, 0) + TC (0, x2)

Where as,

TC (x1, x2): total cost of producing x 1, x 2
TC (x1, 0): total cost of producing x 1
TC (0, x2): total cost of producing x 2

we actually call this total cost function is subadditive. So, if you recall, when we
talked about the economies of scale, we were saying that the average cost is

In this case, the total cost of jointly producing x 1 and x 2 is actually lower than the
individual production. The total cost function is sub additive and if you just rearrange
this, it will look like this.

TC (x1, x2) - TC (x1, 0) < TC (0, x2) - TC (0, 0)

and the main idea here is that the firms grow on the back of one successful product
and this concept may be not very trivial to understand.

But one reason which can lead to economies of scope could be because customers
may have varied demand. They may so if you produce multiple products with
different variety, in that case the customer matching may be better. You may have a
higher demand. So, demand aggregation, this also leads to higher volumes, which
allows you to have higher utilization of your capacity.
(Refer Slide Time: 02:24)

Now can the technology of additive manufacturing can come to our rescue and can
actually improve the economies of scope. So, I think that is something which may be
relevant in the future, how additive manufacturing can enhance the economies of
(Refer Slide Time: 02:47)

The other concept which becomes relevant is what we call as economies of
complementarities. It may happen that so this paper again, is by Milgrom and Roberts
so published an economic American Economic Review. It is a slightly dated paper
published in 1990 and the main idea here is so when we talk about manufacturing, the
manufacturing cannot be seen in isolation.

We have marketing, we have design, we are manufacturing, engineering organization,
right. All these things work in sync with each other, in tandem with each other and
utility of flexible machinery increases with the use. So, this example, if you see this.
If I start taking the orders in the digital form, it is also important that my production
system should also be flexible.

If the customers can announce or declare that this is the product they want. My
production system should also match with that thing and that is where the economies
of complementarities come in. So, this becomes more and more relevant as we
become more platform dependent. We will discuss these things.
(Refer Slide Time: 04:10)

Now, so now we come to so we have seen different eras of production. We have
talked about mass production, mass customization and the things which become more
and more relevant in recent past is mass personalization. We need the right business
models for it. So, when I say business models, it is how you deliver the value to the
customers. We will formally define it in next one or two slides.

But for time being, just take it that it is about how you deliver the value to the
customer. Now there is a very interesting paper produced by written by Levitt titled
Marketing Myopia published in HBR and this paper I think, if you have taken any
marketing course, it may be part of that course. It says the companies were too
focused on products and not enough on the customer needs.

Companies focused too much on the products, they are not very specific about the
customer requirements and just to extend this argument, so this is taken from a recent
book by Peter Marsh, The New Industrial Revolution. While engineers tend to be
more interested in how products are made, what really counts is how they are used.
So, I think, I am just extending this argument by Levitt.

In fact, in one of the papers he mentioned that the companies do not buy drilling
machines, they buy holes and I have seen something very similar when I visited some
company in Bangalore. I think they mentioned to me that some of the aircraft
manufacturers are actually converting to that kind of a business model.

They actually outsource the whole drilling operation, so they are no longer interested
in buying the machines and the technology of IoT, maybe we will have a discussion
on that, the technology of maybe industrial IoT allows us to track how many holes or
drill has been done, what was the thrust, the rotation everything is captured.

You actually pay for how many things or how many holes had been properly drilled.
So, all these business models are actually coming up.
(Refer Slide Time: 06:59)

I think the next slide will give you some more insights on what I am saying. So, this is
a very interesting concept given by Warren, the founder of Acer the smiling curve in
1992 may not be true for all the products, but if you see this, this is a production chain
from the concept to the sales and after service and what it actually says the most value
addition comes from the sales and after service.

It means that that if you actually can monetize this part by some means that actually
can make a firm successful. So manufacturing, the value addition may not be much.
In fact, these days we are talking about concept called as servitization. In fact, some
companies are actually talking about can we make manufacturing as a service (MaaS).
So, because the value addition comes mainly from the sales and the after service.
(Refer Slide Time: 08:22)

This takes us to the definition of business models. A business model defines the way a
firm creates, delivers and captures the value. The classical example is always the
razor blade. Some companies you may be aware that they actually sell the razor at a
pretty low price, but the blades may be very expensive. What it actually means is the
most value addition actually come from after sales.

The more so this may not generate much value to the company, but this suddenly
would make it profitable.
(Refer Slide Time: 09:14)

The same extent, I am extending this argument again to three parts, one is designing
it, one is manufacturing and the other is selling it. I have taken it from a book on
manufacturing by Koren (2010). There is a firm and the firm has a design, make and

sell operations. All these three things are important. So, you design the right product,
you manufacture it with high quality, high speed, whatever.

That faster, cheaper part will still be applicable and then use the right business model
to actually capture the value. Even if you have any of these two things, third thing is
also important. So, even if you manufacture it well, you have the right product, but
you actually do not know how to capture the value, you may not be a successful firm.
(Refer Slide Time: 10:17)

I will extend the logic. If you see this when we talk about the business models, I think
one thing which becomes highly relevant is what is the nature of technology available.
So, when we talk about manufacturing, we still are talking about the faster, the better,
the cheaper, the diverse. I am adding sustainable from my side.

When I talk about sustainability, we are talking about sustainable manufacturing and
when I say sustainable manufacturing, in fact lot of groups across the globe, research
groups are already talking about it. There are groups which are titled like
environmentally benign manufacturing. So, the value you deliver is actually a
function of technology.

So, there would be societal needs, which could indicate sustainable part. There could
be market needs, which could mean that the product should be diverse and how you
deliver the value is also a function of technology. You can think of an example like, if

you have to take a taxi ride or if you have to go from A to B the technology may be
1950 may not allow you to use Ola or Uber kind of business models.

Now the technology is available, which can actually match the market needs to the
manufacturing or to supply. I am giving the eyeglasses as an example, because we
are going to see that as an example in our subsequent slides. So, this is the product
and in fact, we need this product in high variety, because each customer may have a
different requirement.

But finally, what we want is these eyeglasses should meet the customer requirement.
(Refer Slide Time: 12:35)

So the point here is will there be technology which will do that? Can we think of
additive manufacturing as a technology? Can we think of blockchain to make the
supply chain more and more transparent? Can we have machine intelligence available
on the or maybe a platform which allows us to forecast what is the market need? The
production system is highly flexible, which comes as part of additive manufacturing.

The supply chains are transparent, the things are well communicated to the suppliers.
All these things get integrated and you would actually foresee a newer way of
generating the value. I think as part of this course, we try to capture some of these
(Refer Slide Time: 13:35)

Yeah, so as I was mentioning about the example of the eyeglasses. One of the largest
manufacturers of eyeglasses is a company called Essilor and so they make about so I
am not sure whether this data is new, but I think the source which I have used, they
mention about 320 million lenses in a year say.

You can actually say that they actually capture the customer demand, maybe in the
digital firm using some computers, which is 20,000 and you can actually see that there
is pretty high variety. 320 million lenses or different types of lenses they need to
produce. Now what they normally do is they do not keep all these things in inventory,
their inventory certainly will not have 320 million lenses.

What they have is some kind of a blank and that type would be about 400,000 types of
blanks and they manufacture these in 14 different plants. Now when the customer
demand comes these blanks maybe at these 330 labs. These labs are closer to the
customer and these blanks will be converted to the required type of lenses at these

This whole idea, so what you are actually doing is you are delaying the
differentiation. 400,000 types of blanks are converted to different types of
personalized products based on what the customer wants. This is called as either the
delayed differentiation or postponement and what actually enables this thing? Maybe
the technology.

So, you can maybe even the information technology which connects the customer to
the product. Even the machining which allows you to convert those blanks into the
lenses. This is called as postponement and this is not something which is only
applicable in the case of lenses.
(Refer Slide Time: 16:24)

In fact, the former CEO of Essilor quotes that “the data are fundamental to organizing
hundred or more processes necessary to personalize blanks in a matter of hours”. In
fact, you can see the concept of variety, you can see the concept of speed. Cost will
always be there and you want with sustainability and you also want maybe high
quality. So, all those things come as part of this example.
(Refer Slide Time: 17:06)

But as I mentioned that this is not the only example. There are other examples also.
When we talk about say modular products, it means that you manufacture the
products in modular way so the customization becomes easier and what actually
encourages this, because this law of manufacturing that aggregation reduces
variability. You are looking for minimizing the internal variety without compromising
the external variety.

Three classical examples, so people who are aware of the Dell manufacturing. In fact,
Dell keeps, so these are called as Vanilla boxes. This could be a Vanilla computer
configuration. The customization happens when the demand comes. LG is doing
something similar. So, what they have done is, so the refrigerator would be in a
modular firm.

Based on your space requirement, they will customize it. So very interesting.
Customer can actually get a very highly personalized product. Maybe very similar
example is coming from the paint industry. I am putting Asian Paints, but I think it
may be true for other paint manufacturers also where you keep only the white as a
stock, and this converts to different colors based on the customer.

There may be, you can even go to a paint shop, and you can actually see that. What do
you keep is only the white color? So even I think the vanilla ice cream could be the
most common example. You keep only vanilla in stock and all the customization
happens and remember that the customer demand may be highly variable also. It is
important how you actually match the demand with the supply.

I think that technology plays a critical role and we are, that is why we are looking,
moving from an era of mass customization to mass personalization.
(Refer Slide Time: 19:27)

In fact, one of the metrics to capture this idea is what is the average revenue per
product variant. Some of these companies actually have this number very small,
because they actually customize the product based on the customer requirement. It
may happen that you actually have one product variant which is specific only to one

So maybe I think the point here is the companies which may be successful are those
companies which actually have low variation quotient. It means that average revenue
per product variant is actually very small.
(Refer Slide Time: 20:20)

Here, so this is maybe capturing the whole story what we have discussed till now. We
are talking about manufacturing paradigms coming from Koren and I think right from

the beginning of this course, we talked about craft production, we talked about mass
production, mass customization, mass personalization and you can actually see the
volume per variant and the variety.

When we were at craft, the volume per variant was small, but even the variety was
high. When we go to mass, the volume because of economies of scale. The mass
production the volume per variant was high, but the variety was low. When we go to
mass customer, so we are actually moving in this direction and now we are in the
area, in the era of mass personalization, where we want more and more personalized
(Refer Slide Time: 21:25)

Yeah, so now the point here is, can we do better? Can we do further? Can we go
further? Can we improve the manufacturing? Most of you may be aware of this
definition of industry 1.0, 2.0, 3.0, 4.0 and we can actually say that, there would be
some general-purpose technology which comes along with these different versions of

The next is or maybe ongoing is what we say about the digital convergence. This
could become the general-purpose technology and all the other technologies may
merge with it.
(Refer Slide Time: 22:16)

One thing which becomes more and more critical, I think it is critical not just with the
context of manufacturing, it may be for the much larger domain, even when we talk
about reconfiguring supply chains. It is not about automation; I think it is more about
the communication. Product communicates with the machine to tell it exactly what to
do. So, machine knows that this particular product is coming.

When we talk about IoT or IIoT that is something which we may be thinking off.
When we talk about blockchains I think we again maybe thinking of something
similar. In this case, the communication is not actually just between machine to
machine, it may be also between the product to machine. So, that is something which
comes as part of digital convergence and this could go beyond mass personalization.
(Refer Slide Time: 23:14)

I think this gives you some idea about, in fact this may not be the complete list. Some
of the countries actually have come up with their own national initiatives. You can see
example of US. They have the AMP 1 and 2. Make in India in India. Intelligent
manufacturing in China. E-factory in Japan. Industry, in fact the word Industry 4.0
came from Germany.

These are different national initiatives, which are trying to actually look beyond this
mass personalization and how the modern digital technology can be integrated with
(Refer Slide Time: 24:01)

I think this gives you some flavor of the different technologies. I think so in this
course, we may not be talking about all the technologies. But we may be talking about
parts of machine intelligence, blockchain, additive manufacturing. I think we will
have a substantial because Dr. Chandrasekhar from Wipro would be emphasizing only
on additive manufacturing.

We will have some discussion on IoT, digital supply chains, platforms, cloud
manufacturing. I think we will just take a small part of all these technologies and try
to just explain how they are actually influencing the manufacturing. So, this may be
the important part of this course.
(Refer Slide Time: 24:54)

I just give you one example of Siemens smart factory in Hamburg in Germany, where
they produce this PLCs, the programmable logical controllers and this may be the
larger ecosystem.
(Refer Slide Time: 25:16)

I give you some numbers to give you the insights. Let me skip this part.
This actually talks about efficiency, agility, risk capturing and innovation.
(Refer Slide Time: 25:31)

Let me not spend time on this. Let me directly come to what the Siemens is doing?
See you can actually see this in manufacturing and process people are running their
plants deterministically. The process is well understood. This is something very
stable, static and the it has advantage that it is very robust. But what it actually does is
it actually removes the flexibility.

You remove defects because of robustness, because of stability. But the flexibility is
not there. When we talk about digital factory, it also provides the tracking as well as
the flexibility.
(Refer Slide Time: 26:20)

I give you some numbers about so you can actually see 12 million units per year (one
unit per second). This is the number coming from the digital factory. So very high
defect free production. The output has gone up and you can see the statement about
the digital convergence what I made earlier that the products control their own
manufacturing processes.

McKinsey estimates that the operational efficiencies in factories has the potential of
adding about $3.7 trillion by 2025. This gives you the context. This gives you the
number, what numbers we are actually talking about. So, with this, I will stop my part
for time being. The next session we have an invited speaker, Mr. Murali, who would
actually talk about the manufacturing radar.

He will give you how these technologies are impacting the manufacturing. After the
manufacturing radar, he will continue his sessions on agility, on manufacturing
agility. After that, I will actually come back and talk about these technologies. So, for
next, maybe four sessions, you will be listening to Mr. Murali. Thank you.