Skip to content

The growing cultural cliff between people and companies

IS THE FUTURE OF BUSINESS TOTALLY HUMAN CENTRIC?

Young entrepreneurs

Today, we see a lot of young developers and designers that grew up with technologies, new social habits and a lot of new tools that did not exist for the previous generation (actually, a generation is no more than 10 years today!).
As a consequence, entrepreneurs in their early 20’s are creating and innovating using technical stacks they have known their whole life, unaware of the details of a CPU, who Turing was and what a methodology can bring to a development project. They just create and diffuse their ideas!
… and people consume their products, get new habits and change their way of viewing/judging things.

Why do they target consumer users? Because that’s what they used to be in their younger years and because they know that it’s the people who has the most likelihood to change some habits quickly, to adapt to a new situation and to spread the word of mouth.
Darwin would explain that those characteristic are specific to living organisms and that this adaptation capability is what makes people evolve towards the better.

Why is it so difficult for companies and organisations? One can bet that it’s this difficulty that discourage smart young entrepreneurs to think for companies rather than for flexible, adaptive and fast learner human consumers.

The difference between human individuals and companies in term of evolution the last ten years is spectacular.
The journey of human people went from the sole ability to get in touch with his contact list through a phone call (when he had some network) to the extended ability to share his data resources with all interested parties of his broaden network, to add augmented context to its communication and to fasten his way to any goal he pursues.
In the same time, the journey of companies lead them from the hosted CRM to the CRM as a service…
Should they inspire themselves from the consumers?

 

Eric Delacroix
Twitter: @edelax


 

Releated Posts

Evaluation of GraphRAG Strategies for Efficient Information Retrieval

Traditional RAG systems struggle to capture relationships and cross-references between different sources unless explicitly mentioned. This challenge is common in real-world scenarios, where information is often distributed and interlinked, making graphs a more effective representation. Our work provides a technical contribution through a comparative evaluation of retrieval strategies within GraphRAG, focusing on context relevance rather than abstract metrics. We aim to offer practitioners actionable insights into the retrieval component of the GraphRAG pipeline.
Read More

Flight Load Factor Predictions based on Analysis of Ticket Prices and other Factors

The ability to forecast traffic and to size the operation accordingly is a determining factor, for airports. However, to realise its full potential, it needs to be considered as part of a holistic approach, closely linked to airport planning and operations. To ensure airport resources are used efficiently, accurate information about passenger numbers and their effects on the operation is essential. Therefore, this study explores machine learning capabilities enabling predictions of aircraft load factors.
Read More