From the digital revolution to the data revolution
A digital big bang
The advent of the Web in the 1990s and e-commerce from the 2000s prompted society to start a new form of revolution: the digital revolution.
This massive digitalisation 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 era of networks in which communication becomes permanent thanks to digital media has been growing for more than 20 years.
Information sharing, exchange of knowledge and opinion, trade, new forms of expression are gradually shaping the society of tomorrow: a virtual consumer society.
Data at the heart of the stakes
Every day millions of people connect and surf the web from site to site, from forum to forum, from research to social networking.
Billions of information are exchanged, consumed and stored all over the world. After humans, it is the turn of objects to become “collectors” of information? For what purpose? To be analyzed to create new forms of consumerization in the service of the economy, science or civil society.
Big Data Revolution
Let us say it frankly, the digital revolution we have been experiencing for 30 years is THE data revolution. The terminology “Big Data” was born in the late 1990s through a concept modelled in 4 dimensions: the “4V” (Volume, Variety, Velocity, Veracity). It aims at an ultimate goal: the creation of “Value”.
The Big Data “materializes” the reality and foundations of this new “digital” era. Combined with a tremendous evolution of technologies (performance/cost ratio) and advanced analytical techniques, it allows to create new paradigms of ideation from a voluminous amount of data. Moreover, the degree of sophistication, speed and precision that it manages to achieve exceeds all expectations.
Data Driven: an irremediable change
In short, Big Data should serve a single cause, the creation of value or knowledge. No field is spared: economy, education, industry, research, energy, tertiary, defence, agriculture and civil society.
For the market, the stake is clear: to make new forms of value by making maximum use of the new “Black Gold” represented by the data.
Data as a strategic axis of organizations…
This data becomes vital, considered a strategic “asset” for the company at the heart of all concerns.
Starting in the 2000s, companies saw very quickly the opportunity to use these billions of digital data for commercial or innovation purposes. This lever of development, or even survival, has become vital in business strategies.
The change in the use and organization of work by technology forces companies to rethink their raison d’être, their societal commitments, their culture, in particular to consolidate their sustainability.
… but which can be painful
However, the development of a data-driven culture within a company is not easy. While the evolution concerns the processing of its data, it also concerns the expertise that has to adapt to these new uses.
Several surveys, including the Big Data and AI Executive Survey of NewVantage Partners (2019), show that most organizations fail to become data-drivers. Even more worrying, the share of companies that consider themselves “data-driven” has declined over the last three years, from 37.1% in 2017, to 32.4% in 2018 and 31% in 2019.
Transforming your business and succeeding
Management in the center of the chessboard
To become a data driver is not to be decreed, it is a commitment. Management is the cornerstone of the whole strategy. It is to put the company in a position to define a clear digital strategy around the data.
This inevitably involves answering two major questions: “What are our major stakes for the next few years? What information do we need to be able to respond effectively to these challenges?”.
Identify 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 collecting “missing” data outside the company is necessary.
An expected trasnformation at all levels of the enterprise
This approach is therefore undertaken with profound changes within the company itself. First, the transformation or acquisition of key skills around the data, dictated among other things by the concept of 4V (Big Data) is indispensable.
4V, what are we talking about?
The notions of “Volume” and “Velocity”
Every second on the Internet sees the world transit more data than the Internet stored over a whole year just 20 years ago. All 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 to take advantage of it. Of course, technology is there today for those who know how to “dump it”. However, the expert’s leg play is essential to understand these flows of data without being overwhelmed by the wave and its speed of movement.
The notions of “Variety” and “Veracity”
“What matters is not quantity, but quality.” This is true in some cases not necessarily in others. We will later observe that, in general, the performance of some AI mechanisms requires both quality in the data, but also volume.
In any case, again, the expert with, in particular, a sophisticated data analysis capability is essential to make this data refining and refining chain efficient.
Value added requires expertise
We therefore imagine quite easily that in order to become a data driver, a large majority of the company’s players, is required to play a crucial role. The organisation must be imagined around different links (expertise) that fit into the data processing chain.
The roles are multiple:
- Data collectors
- Data cleaners in charge of eliminating poor matter (noise),
- Data Wrangling which gathers the scattered data to make them consumable.
- Analysts responsible for transforming this raw fuel, already refined by other experts.
It is during this last stage that everything is played out. It is at this moment that the data, crossed, enriched, become diamond: the information and the value it contains.
Profiles of data drivers that vary
Three company profiles can be distinguished:
- The “users” of data, from all sources, having as their central concern the in-house use of data to help them identify their issues.
- Data “providers/integrators” acting as data collector, data injector transformers serving data “users”.
- The “facilitators” of data providing technology and/or expertise either by providing outsourced infrastructure or advice to the business actors of “user” companies.
Multiple stakes
The digital economy that we have been talking about since the beginning of this article is intimately linked to the data that is one of the essential drivers. This economy maintains a major ambiguity, centralized around the concept of “value creation”.
Indeed, if it supports a significant part of its development on a process of collection and transformation of a “free” value, the data is becoming more and more market value. This ambiguity continues to grow. Moreover, many digital business models are built around this idea.
