The Inflexion Point Of Generalization - Aditya Yadav

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 *

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…

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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!!!

The Inflexion Point Of Generalization - Aditya Yadav

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