Workbook: Building a sustainable data-driven organization, part 2

Unbundling AI: Building a sustainable data-driven organization | Perspectives for defensibility | Workbook, part 2/5

Hello,

This workbook is a non-technical tool for structuring early conversations across the multiple roles needed to implement a Human-AI interactions when building a sustainability-focused system. You can find more about this in part 1.

We are sharing the workbook on Substack as an inclusive tool for our premium members. It will be available for sale via our various platforms and website.
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The following parts briefly explain the various perspectives we can obtain from the patterns expected by founders, entrepreneurs, and decision-makers in their data-related decision-making process.

The priority for organizations to build next-generation systems falls into three areas: 

• improving data management, 

• enhancing data analytics and machine learning, 

• expanding the use of all types of enterprise data, including streaming and unstructured data.

To help organizations become data-driven, the core business must be deployed on a wide adoption of data-driven systems and cloud-based technologies, including analytics tools with machine learning capabilities.

All need to be supported by the ability to generate actionable insights.

Building a sustainable data-driven organization

1. Introduction to the data transformation era (what does it mean for the next generation business?) | Last week’s post

2. Perspectives for defensibility | This week’s post below [Not a member? Subscribe now]

3. Growth and resilience

4. Barriers to scale in a complex environment

5. AI technologies, democracy, and culture—conclusion: visions of the future.