The Inflexion Point Of Generalization - Aditya Yadav

1. “Running an Agile Fortune 500 Company”
Aditya Yadav, aditya.yadav@gmail.com
in.linkedin.com/in/adityayadav76
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2. *
*A Typical Global Company
*Fortune 500/1000
*200 Divisions
*40 Countries
*25000 Employees

3. @ Acme Inc.
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4. *
*Original Question “China has a Billion
population, you cannot Generalize like this…”
*The Correct Question - “Well! Lets start from
the first principles and look at what and why
we generalize and in what situations. And
where its applicable and where its not. Shall
we?”

5. And The Philosophy Behind The Answer
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6. *
*What is Statistics?
*Statistics is the Math’s and Science of Means
and Proportions
*In other words – Generalization!!! Across
Specific

7. *
*What is Strategy?
*It is nothing but abstracting away the
specifics, and generalizing, by creating Models
and Frameworks
*Which are then applied across
Industry, Businesses and Situations…
*The very act of Generalization allows us to
make Broad Conclusions

8. *
* So What Changed?
* Why are we discussing this now?
* Why does this matter? This has been done since centuries…
* But, the world changed in the last decade…
* We have tools to collect and process large amounts of Data
* We can analyze and process so much data that we can analyze each
customer, each transaction…
* Why does that matter?
* For a couple of reasons
* Now every Customer is a Market Segment by himself… within the limits of
Customization of our offerings which are not that elastic. So probably
more limited in Manufacturing, but extremely malleable in Services
* We probably don’t need to Generalize anymore, ok! Atleast not that much

9. *
*Call it Big Data, Data Science, Analytics, Micro
Markets, Micro Segments…
*It basically means that every Subject can be
modeled with very high accuracy using its own
historical data and the historical data of a related
population.
*To make extremely reasonable inferences about its
future actions, needs, wants, desires etc.
*The very act of being able to Model successfully
implies Rationality! In the Problem Space…

10. *

11. *

12. *

13. *
* Fine Grained / Coarse Grained
* Data Availability/Quality/Types…
* Uniqueness of Situation
* The Industry/Market Beta
* Scale
* Complexity
* Speed
* Automation
* Change
* Learning
* Innovation (Radical…Disruptive… Incremental)
* Hyper-Dimensionality
* Reliability & Assurance
* Predictions
* Qualitative vs Quantitative
* Subjunctive vs Indicative

14. *
* When you don’t have Data … Strategy Models & Frameworks are the only way to go
* Strategy Models & Frameworks are Abstractions/Generalizations… they are great
enablers as Black Boxes… but when things start going wrong or when the progress stops
or when everyone in the industry is doing the same things using the same models
making the same conclusions, the veil has to be lifted…
* Soon they will become very useless as the World Evolves as Differences will Override
The Commonalities… Not only in Consumer Business but even in B2B scenarios
* Data can be used at a very Fine Grained Level while Models & Frameworks are mostly
limited to Aggregates
* The Term That Best Suites Data Science applied to Strategy is “DESIGNER STRATEGIES”
* We have long ago extinguished almost all value we could derive from generalized
qualitative models and frameworks in comparison to what others including our
competitors have derived, in e.g. marketing, sales, management and strategy in
general…
* Rule: But Strategy Models & Frameworks are very valid today for one and only one
thing “TO SET THE BROAD DIRECTION OF THE COMPANY” which is the foundation of
EMERGENT STRATEGY…
* Rule: Generalizations are most useful to give you Mental Models…

15. *
Aditya!!!