The document discusses how increasing diversity and ubiquity of knowledge embedded in products and people leads to greater business complexity. It provides examples from games like Scrabble to illustrate how measuring the diversity of products a company makes and the ubiquity of those products across companies can serve as a proxy for estimating the knowledge within a company. Greater interaction and relationships between individuals and tasks increases the possible combinations and interactions, further adding to complexity.

1. Business Complexity
as
diversity and ubiquity of
knowledge embedded in product
When we think of products in knowledge terms,
markets take on a different meaning
Didi Sugandi, Nov 2011
dsugandi@gmail.com
Diversity = variety (n.) , multiplicity, assortment, differences
Ubiquity = existing everywhere at once, or seeming to be; Ubiquity is a
synonym for omnipresence, the property of being present everywhere

2. QUESTIONS - from a case studied
What are you Curious about?
How do you channel your Creativity?
What is your personal definition of Courage?
What are you Committed to?
How can we make our products & services more Intuitive?
How do we do what we do more Intelligently
What Inspires you and how do you inspire others?
What new possibilities are you CREATING
at Our Organization?

3. and then there are numbers of
persons, units, teams, groups, divisions (etc. , whatever)
Just an example:
ARCHITECTURAL & INTERIOR DESIGN
SPA CONSULTANCY
PR/MARKETING
DESIGN R&D
PRODUCTS
IT/SYSTEMS
H.R/BENEFITS/INCENTIVES
etcetera…..
etcetera…..

4. POSSIBILITY IS COMBINATION OF “ALL THE THINGS”
Curiosity - What are you Curious about?
Creativity - How do you channel your Creativity?
Courage - What is your personal definition of Courage?
Commitment - What are you Committed to?
Intuition - How can we make our products & services more Intuitive?
Intelligence - How do we do what we do more Intelligently
Inspiration - What Inspires you and how do you inspire others?
Possibility discovery is the discovery (or matrix) of :
Knowledge embedded in person(s)
AND (or versus)
Knowledge embedded in product(s)
That’s what we mean by “ALL THE THINGS”

5. Business or Economic Complexity:
(Diversity and Ubiquity) of Knowledge embedded in Product(s)
What are things made out of? One way of describing the
business or economic world is to say that things are made
with machines, raw materials and labor. Another way is to
emphasize that products are made with knowledge;
products consist of chunks of “productive knowledge”
When we think of products in knowledge terms, markets
take on a different meaning. Markets allow us to access
the vast amounts of knowledge that are scattered
among the people of the world.
Products are vehicles for knowledge, but embedding
knowledge in products requires people who possess a
working understanding of that knowledge.

6. a unit of knowledge type called “productive knowledge”
During the past two centuries, the amount of productive knowledge we hold
expanded dramatically. However, this was not an individual phenomenon. It
was a collective phenomenon. As individuals we are not much more capable
than our ancestors, but as societies we have developed the ability to make all
things that we have now – and much, much more.
Modern societies can amass large amounts of productive knowledge because they
distribute bits and pieces of it among its many members. But to make use of it, this
knowledge has to be put back together through organizations and markets. Thus,
individual specialization begets diversity at the national and global level. Our most
prosperous modern societies are wiser, not because their citizens are
individually brilliant, but because these societies hold a diversity (varieties) of
knowhow and because they are able to combine and recombine it to create a
larger variety of smarter and better products.
The amount of knowledge that is required to make a product can vary
enormously from one good to the next. Most modern products require more
knowledge than what a single person can hold.

7. For a society to operate at a high level of total productive knowledge, individuals must
know different things. Diversity of productive knowledge, however, is not enough. In
order to put knowledge into productive use, societies need to reassemble these
Productive knowledge_cont. 1
distributed bits through teams, organizations and markets.
The amount of knowledge embedded in a society, however, does not depend mainly on
how much knowledge each individual holds. It depends, instead, on the diversity of
knowledge across individuals and on their ability to combine this knowledge, and
make use of it, through complex webs of interaction.
Accumulating productive knowledge is difficult. For the most part, it is not
available in books or on the Internet. It is embedded in brains and human
networks. It is tacit and hard to transmit and acquire. It comes from years of
experience more than from years of schooling. Productive
knowledge, therefore, cannot be learned easily like a song or a poem. It requires
structural changes. Just like learning a language requires changes in the
structure of the brain, developing a new industry requires changes in the
patterns of interaction (and relation) inside an organization or society.
J.L. Lemke (a semiotician): human make meaning in two fundamentally complementary opposite ways:
• TYPOLOGICAL, by classifying things into mutually exclusive categories (Language operates this way)
• TOPOLOGICAL, by distinguishing variations of degree (rather than kind) along various continua of
difference.

8. Expanding the amount of productive knowledge available in a company involves
enlarging the set of activities that the company is able to do. This process, however, is
Productive knowledge_cont. 2
tricky. Industries cannot exist if the requisite productive knowledge is absent, yet
accumulating bits (“chunks”) of productive knowledge will make little sense in
places where the industries that require it are not present. This “chicken and egg”
problem slows down the accumulation of productive knowledge. It also creates important
path dependencies. It is easier for companies to move into industries that mostly
reuse what they already know, since these industries require adding modest amounts
of productive knowledge. By gradually adding new knowledge to what they already
know, companies economize on the chicken and egg problem. That is why we find
empirically that companies move from the products that they already create to others
that are “close by” in terms of the productive knowledge that they require.
We need a “map” (“a topology”: showing relative positions, continuity and
connectivity, variations of degree (instead of kind) along various continua of difference)
that captures the similarity of products in terms of their knowledge requirements.
This topology (map) provides “paths or continuations” through which productive
knowledge is more easily clustered (= agglomerated or accumulated). We call this
map, or network, the product space, a thought landscape and use it to locate each
person or company, illustrating their current productive capabilities (i.e. knowledge)
and the products that lie nearby (or overlapped).

9. How do we go (=find the links, find the continuations)
from what a company makes (=knowledge embedded in product)
to what a company knows (=knowledge embedded in people, persons)?
If making a product requires a particular type and mix of knowledge, then the
companies that make the product reveal having the requisite knowledge.
From this simple observation, it is possible to extract a few implications that can
be used to construct a measure of business complexity.
This measures (“states”) are neither states of natural-process nor states of
knowledge; they are objective probability measures. An objective probability
measure is the formal expression of an objective indefiniteness.
An objective indefiniteness entails that the values of certain observables are
extrinsic (possessed only because they are indicated) rather than intrinsic
(indicated only because they are possessed).
This dependence on value-indicating facts is not a dependence on anything
external to the free-standing reality that owes nothing to
observers, information, or our interventions into the course of natural-process.

10. amount of knowledge that a company has is expressed
in the diversity and ubiquity of the products that it makes
First, companies whose persons and organizations possess more knowledge
have what it takes to produce a more diverse set of products. In other words, the
amount of embedded knowledge that a company has is expressed in its
productive diversity, or the number of distinct products that it makes.
Second, products that demand large volumes of knowledge are feasible
only in the few places where all the requisite knowledge is available. We
define ubiquity as the number of companies that make a product. Using this
terminology, we can observe that complex products –those that contain many
personbytes of knowledge–are less ubiquitous.
The ubiquity of a product, therefore, reveals information about the volume of
knowledge that is required for its production. Hence, the amount of knowledge
that a company has is expressed in the diversity and ubiquity of the
products that it makes.

11. A game of scrabble is a useful analogy (1)
In scrabble, players use tiles containing single
letters to make words. For instance, a player can
use the tiles R, A and C to construct the word CAR
or ARC. In this analogy, each product is
represented by a word, and each capability,
(=module of embedded knowledge), is
represented by a letter.
We assume that each player has plenty of copies
of the letters they have.
Our measure of business complexity corresponds
to estimating what fraction of the alphabet a
player possesses (=sum of his/her
knowledge), knowing only how many words
he/she can make, and how many other players
can also make those same words (“product”).

12. A game of scrabble is a useful analogy (2)
Players who have more letters will be able
to make more words.
So we can expect the diversity of words
(products) that a player (company) can
make to be strongly related to the number
of letters (capabilities) that he (it) has.
Long words will tend to be rare, since they can only be put together by players
with many letters. Hence, the number of players that can make a word tells
us something about the variety of letters each word requires: longer words
tend to be less ubiquitous, while shorter words tend to be more common.
Similarly, ubiquitous products are more likely to require few capabilities, and less
ubiquitous products are more likely to require a large variety of capabilities.

13. From Scrabble back to Diversity and Ubiquity
Diversity and ubiquity are, respectively, crude approximations of the variety of
capabilities (i.e. knowledge) available in a person or a company or required by
a product. Both of these mappings are affected by the existence of rare letters
(scarcity), such as Q and X. For instance, players holding rare letters will be able to
put together words (=“product”) that few other players can make, not because they
have many letters (=“knowledge”), but because the letters that they have are rare.
This is just like rare natural resources, such as uranium or diamonds, etc.
Yet, we can see whether low ubiquity originates in scarcity or complexity
by looking at the number of other words (other “products”) that the makers
of rare words (“products”) are able to form.
If these players can only make a few other words, then it is likely that
rarity explains the low ubiquity. However, if the players that can make
these rare words (“products”) are, in general, also able to put
together many other words (“products”), then it is likely that the low
ubiquity of the word (“product”) reflects the fact that it requires a
large number of letters (“capabilities”) and not just a few rare ones.

14. Diversity can therefore be used to correct the information carried by
ubiquity, and
Ubiquity can be used to correct the information carried by diversity.
We can take this process a step further by correcting diversity using a measure
of ubiquity that has already been corrected by diversity and vice versa. In fact,
we can do this an infinite number of times using mathematics. This process
converges after a few iterations and represents our quantitative measures of
complexity.
DIVERSITY is related to the number of products that a player is connected to.
It is equal to the number of links that this player has in the network (map)
UBIQUITY is is related to the number of players that a product is connected to.
It is equal to the number of links that this product has in the network (map)
Note that those two are about “person(s)” and “product(s)” in a continua
Diversity and Ubiquity corrects each other

15. Possibilities are created by ways of relation & interaction
What new possibilities are you CREATING at OurCompany?
Intutition -
Inspiration -
Courage - How can we Intelligence -
Curiosity - Creativity - Commitment - What Inspires
What is your make our How do we
What are you How do you What are you you and how
personal products & do what we
Curious channel your Committed do you
definition of services do more
about? Creativity? to? inspire
Courage? more Intelligently
others?
Intuitive?
1
2
3
4
5
6
7
8
9
10
Interaction of individuals, possessing different knowledge and different
views, is what constitutes the life of thought. The growth of reason is a
social process based on the existence of such differences. It is of its
essence that its results cannot be predicted, that we cannot know which
views will assist this growth and which will not. — Friedrich A. Hayek

16. Topologize! - to make
tacit knowledge
more explicit
“Group priority
instant assessment”
matrix
a tool “to map” proximities
(closeness, similarity etc)
between and among
“player’s/actor’s knowledge”
and
“knowledge inside products”
distinguishing variations of
degree (rather than kind)
along various
continua of difference

17. continua of difference :
thinking topologically (not typologically)
"Hijau" adalah nilai/makna yang ada dalam kisaran di antara hal yang
sudah termasuk hijau, sampai dengan nilai/makna yang mau jadi
bukan hijau.. Sebuah harga dalam ekonomi juga demikian. Kebenaran
juga hal seperti itu. Sebuah konsep atau atribut bisa tidak dipandang
sebagai "titik" atau garis tak ber-entitas dalam ruang dan waktu, tetapi
dipandang sebagai suatu kisaran (range), suatu keberlanjutan (continua), -
dipandang sebagai variations of degree along continua of difference.
Entitas adalah relasi atribut-atribut, relasi konsep-konsep.. suatu
rangkaian relationships, suatu kisaran nilai, suatu continuum. Mulai dari
yang paling "rendah" sampai paling "tinggi". Sesuatu nilai yang terletak
diantara yang (mulai) masuk akal sampai di batas hampir ke luar, di luar
akal. Kisaran nilai/makna di antara yang "terendah" mulai bisa dicerap (or
perceived) sampai “tertinggi” bisa dicerap.

18. Pairwise Comparison (pembandingan perpasangan) – Why
1. Berangkat dari prinsip bahwasanya: tiap hal, masing-masing
mempengaruhi dan dipengaruhi oleh setiap dan masing-masing hal
lain – “exchange value of each and every other thing” atau “bilateral
exchange ratios” - Contoh dalam ekonomi: price is “bilateral exchange
value of each commodity for every other commodity”
2. COMBINING: menemukan pilihan kombinasi “beberapa hal dari segenap
hal” misalnya “dua hal dari segenap hal”
3. WHY COMBINING?.. Because we need to prioritize (rank) capabilities
(knowledge) which we can readily transformed into product(s)
4. Prosedur ini adalah computing with collaborative minds. Berpikir
otonom dan sekaligus kolaboratif. Berangkat dari pikiran
individual, subjektif, menemukan (men-discover) pikiran kolektif/objektif.
Tanpa pendiktean/diktator.
5. Prosedur ini sebaiknya dilakukan secara iteratif, periodik/ reguler.

19. Appendices, next following slides
• Some explanations / reasoning about
increase in complexities when or if
relationship and or interaction increases
- Between persons
- Between tasks (assuming 1 task per
person)

20. The number of possible interactions
The number of possible interactions can be computed in the following way.
Let n be the number of subordinates reporting to a supervisor. Then, the number
of possible relationships of direct single type which exist in the organization
is identical with the number of organizational members: n.
The number of possible interactions between organizational members is
n (n - 1), and
the number of possible task interactions (assuming one task per person) is
n (n-1)2.
The figure provides a good impression of the dilemma of coordinating work. A
more realistic example for a single person can illustrate this. A manager having 3
subordinates and adding a fourth, faces 4 additional direct relationships to
monitor, i.e. that each new subordinate increases the number of direct
interactions with (n+1). This figure does not even consider the fact of possible
group interactions, which would boost the total number of possible interactions
exponentially.

21. Number of possible
person relationships & task interactions

22. exchange value
of each
for
every other
thing

23. Thou shall not, alone eat the fruit of knowledge.
Share it with others.
Oops!