The Real Trait Of A Data-Driven Organization
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The Real Trait Of A Data-Driven Organization

Carlo Torniai, Head of Data, Insights and Artificial Intelligence, Esselunga
Carlo Torniai, Head of Data, Insights and Artificial Intelligence, Esselunga

Carlo Torniai, Head of Data, Insights and Artificial Intelligence, Esselunga

One of the most used terms in recent years (after we barely survived during the 2010s the flood of buzzwords such big-data, digital transformation, and the likes) is the term data-driven.

Almost every organization claims to be (or being on the path of becoming) data-driven, putting lots of effort and money in transformation roadmaps that should guarantee them to reach the desired status. This short article gives a perspective on what is really needed when it comes to becoming a data-driven organization from the vintage point of significant experiences in a wide range of companies, industries, and organizational settings.

It’s not about technology

 We all have seen repeatedly the tech-first/ resource-first approach giving the illusion that success can be guaranteed with the proper investment in tech stack and the allocation of a bunch of FTEs. Don’t get me wrong: having adequate resources and the proper tech stack for data and Artificial Intelligence it’s important, but, by themselves, these two things don’t automatically make us successful in creating a data-driven organization. There is something that must come first and, unfortunately, it requires more time and effort than setting up the latest and greatest cloud infrastructure and assembling a team to put it to good use.

it’s all about culture

Becoming a truly data-driven organization is hard because it requires a profound mindset shift, a “cultural” change that transforms (and keeps evolving) the DNA of a company.

This change can be summarized in the creation of a cultural context that formally and constantly can foster, structure, and adapt approaches around advanced data analytics and Artificial Intelligence solutions that can affect and change the decisionmaking process of the whole organization.

Traits of such cultural context were formalized within the “System of Insight” approach which was born in a setting where the development and deployment of advanced analytics and Artificial Intelligence solutions required a fast but rigorous decision-making process and had strong impacts in user experience, product design and related costs.

The idea behind the “System of Insight” approach is that when dealing with complex data and AI solutions, a strong social/ cultural context is required for a robust and effective decision-making process.

"Becoming a truly data-driven organization is hard because it requires a profound mindset shift, a “cultural” change that transforms (and keeps evolving) the DNA of a company"

The traits of this cultural context can be summarized as follows:

a) It is multidisciplinary: it has a high degree of diversity (educational, cultural, professional history) specifically across people within the same discipline, function, and role

b) It is agile: has effective and quick turnarounds

c) It is informal: it doesn’t have to be formalized in an org chart) and lives better within “flat” organizations

d) It is argumentative: critical thinking, arguing, and debating are the structured way of working.

e) It is transparent: the approach is based on trust and operates in full transparency internally and towards the rest of the organization.

The creation and preservation of this space is the “cultural change” that makes it possible to truly and effectively become a data-driven organization. It allows to assess hypothesis, design experiments, argue to find possible corner cases that make the identified solutions perform poorly or bring unwanted outcomes, and iterate continuously on the above steps to move fast towards finding new solutions and improve the existing ones.

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