From the digital revolution to the data revolution
A digital big bang
The advent of the Web in the 90's and e-commerce in the 2000's pushed society to start a new kind of revolution: the digital revolution.
This massive digitalization is the most "radical" form of evolution that society has experienced since the industrial revolution that began in the second half of the 19th century. The network era, in which communication becomes permanent thanks to digital media, has been in full swing for more than 20 years.
The sharing of information, the exchange of knowledge and opinion, commerce, and new forms of expression are gradually shaping the society of tomorrow: a virtual consumer society.
Data at the heart of the issues
Every day millions of people connect and surf the web from site to site, from forum to forum, from search to search, from social network to social network.
Billions of pieces of information are exchanged, consumed and stored around the world. After humans, it is now the turn of objects to become information "collectors"? For what purpose? To be analyzed to create new forms of consumerization for the economy, science or civil society.
The Big Data revolution
Let's face it, the digital revolution we have been experiencing for 30 years is THE data revolution. The terminology "Big Data" was born at the end of the 90s through a concept modeled in 4 dimensions: the "4V" (Volume, Variety, Velocity, Veracity). It aims at an ultimate goal: the creation of "Value". We then talk about the 5V.
Big Data " materializes " the reality and the foundations of this new " digital " era. Combined with a dazzling evolution of technologies (performance/cost ratio) and advanced analysis techniques, it allows the creation of new ideation paradigms from a voluminous amount of data. Moreover, the degree of sophistication, speed and precision that it achieves exceeds all expectations.
The Data Driven enterprise: an irreversible transformation
In short, Big Data should serve a single cause, the creation of value or knowledge. No field is spared: economy, education, industry, research, energy, services, defense, agriculture and civil society.
For the market, the challenge is clear: create new forms of value by exploiting this new "black gold" that is data to the maximum.
Data as a strategic axis for organizations...
This data becomes vital, considered as a strategic "asset" for the company at the heart of all concerns.
From the 2000s onwards, companies quickly saw the opportunity to use these billions of digital data for commercial or innovation purposes. This lever for development, or even survival, has become vital in corporate strategies.
The upheaval of the uses and organization of work by technology is forcing companies to rethink their raison d'être, their societal commitments, and their culture, in particular to consolidate their durability.
... but which can be painful
However, the implementation of a data-driven culture within a company is not easy. If the evolution concerns the processing of its data, it also concerns the expertise that must adapt to these new uses.
Several surveys, including NewVantage Partners' Big Data and AI Executive Survey (2019), reveal that most organizations are failing to become data-driven. Even more concerning, the share of companies that consider themselves data-driven has declined over the past three years. From 37.1% in 2017, it has dropped to 32.4% in 2018 and 31% in 2019.
Transform your business and succeed
Management at the center of the chessboard
Becoming data driven is not something that can be decreed, it is a commitment. Management is the cornerstone of the whole strategy. It is about putting the company in a position to define a clear digital strategy around data.
This inevitably involves answering two major questions: "What are our major challenges for the coming years? What information do we need to be able to respond concretely to these challenges?
Identify your data
It is then necessary to imagine which data sources, present in the company, can participate in the design of the information sought. Then, a work of collection of the "missing" data outside the company is necessary.
A change expected at all levels of the company
This approach is therefore committed to profound changes within the company itself. First of all, the transformation or acquisition of key skills around data, dictated by the 4V concept (Big Data), is essential.
4V, what are we talking about?
The notions of "Volume" and "Velocity
Every second on the internet sees more data passing through the world than the internet stored in an entire year just 20 years ago. All of them are potential sources, a "data fuel" that can be useful to the company.
The challenge lies in the ability of companies to identify, collect, clean and organize these "oceans" of data in order to take advantage of them. Of course, the technology is there today for those who know how to "tame" it. However, the expert's footwork is essential to apprehend these data flows without being overwhelmed by the wave and its speed of movement.
The notions of "Variety" and "Truthfulness
"What counts is not quantity, but quality. What is true in some cases is not necessarily true in others. We will observe later that, in general, the performance of some AI mechanisms requires both quality in the data, but also volume.
In any case, here again, the expert with a particularly sharp data analysis capacity is essential to make this data refinement chain efficient.
Added value is achieved through expertise
We can therefore easily imagine that in order to become a data-driven company, a large majority of the company's players will have to play a key role. The organization must be designed around different links (expertise) that fit together in the data processing chain.
The roles are multiple:
- Data collectors
- The data cleaners in charge of eliminating the poor material (noise),
- Data Wranglers, who gather scattered data to make it consumable.
- The analysts in charge of transforming this raw fuel, already refined by the other experts.
It is during this last step that everything is played out. It is at this moment that the data, crossed and enriched, is transformed into a diamond: the information and the value it contains.
Data-driven company profiles vary
We can distinguish three profiles of data-driven companies:
- Data "users " from all sources have a central concern for using data internally to help them meet their challenges.
- Data "providers/integrators" play a role as collectors, transformers and injectors of data for the benefit of data "users".
- Data "facilitators"bring technology and/or expertise either by providing outsourced infrastructures or by consulting with the business actors of "user" companies.
Multiple issues
The digital economy we have been talking about since the beginning of this article is intimately linked to data, which is one of its essential drivers. This economy maintains a major ambiguity, centralized around the concept of "value creation".
Indeed, while it bases a significant part of its development on a process of collecting and transforming "free" value, data is increasingly being transformed into market value. This ambiguity is constantly growing. Moreover, many digital business models are built around this idea.
