Why We Wrote the Book “Developing a Path to Data Dominance”
Introduction
Art Langer and I recently published a book on the topic of “Data Dominance”. I thought that it would be of some interest to describe why we wrote a book on this topic, and why the topic is relevant to our times.
AI is the buzzword of the day. We live in a world where all intellectual activity performed by humans is going to be augmented or replaced by AI software. Whether we like it or not, we humans need to survive this giant tsunami of change in the world. So, what to do?
It seems that there are two choices that we have. The first is to get ahead of the AI wave, and learn to use AI to augment our own skill sets. The other is to fall behind the wave and be replaced in our jobs by AI automation. If you find the former choice to be more attractive, read on.
The Idea of Dominance
A few organizations that have learnt to build scalability through hyper-automation have become the dominant companies of public markets. These organizations have been able to ride on exponential growth waves, outpacing their competitors on both revenue acquisition and customer acquisition. They have become what we call dominant companies.
Closer observation reveals that the dominance achieved by these companies is based on using massive amounts of data/information to create value for the customers. Data is the basis of Dominance!
Developing a Path to Data Dominance: Strategies for Digital Data-Centric Enterprises
Publisher: Springer; 1st ed. 2023 edition (April 26, 2023)
Language: English
Hardcover: 300 pages
Publisher: Springer; 1st ed. 2023 edition (April 26, 2023)
Language: English
Hardcover: 300 pages
Developing a Path to Data Dominance: Strategies for Digital Data-Centric Enterprises
Most existing companies struggle currently because they lack the tools and strategies to move product departments into independent platforms that can be retrofitted to form dynamic new products based on consumer demands. This book provides managers and professionals with the necessary approaches for designing software and hardware architectures to support data platform organizations. Specifically, it demonstrates how to automate the decomposition of existing platforms into smaller parts that can be reused to form new variations …
So What Should We Do?
Given that data-dominant companies are going to have a massive competitive edge in the foreseeable future, we need to behave more like these companies if we want to get ahead of the wave. This means that we need to learn about AI and data, and become familiar with what AI can & cannot do.
Having educated ourselves, we need to decide
- whether we can work for a data-dominant organization,
- build a data dominant-organization, or
- retreat to sectors that will not be impacted significantly by AI.