Data: value through exploitation

In the beginning, we traded metals, which had the value of money.
In the beginning, we exchanged information within the company.

And then one day we created the gold standard.

And then one day the information became data. The data!

In both cases, it is about awareness of value. Gold becomes valuable through its use in several areas: jewelry, technology, investors and central banking. Data is enhanced by the uses made of it by the various business lines of the company: improving decision-making, analyzing profitability, strengthening customer knowledge, improving services, etc. Data users are therefore the "creators of value ".

Before, the emphasis was on the "collector" of data. Companies tried to designate a "native" owner of the data, without very often succeeding in doing so ... This designation was intended to empower a reference profession in the definition and in the quality of the data. However, for customer data, the customer himself is the sole owner. It makes its data available to enable a company to serve purposes related to its activity. The company therefore sets the terms of data acquisition according to the use that will be made of it, a bit like the alloy or the carat of gold for a particular job.

Once collected / acquired, data has an “economic” value. It can serve other purposes: it is the pooling of data and therefore of value. This pooling invites organizations to break down the silos that still exist, within the authorized sharing limits (GDPR, confidentiality, conflict of interest, etc.). Pooling also makes it necessary to set up governance for the acquisition and use of data in order to integrate the constraints of all the referring businesses. Therefore, the strongest constraint will prevail: data collected daily can be used for monthly use.This pooling approach can be implemented for any new use. On the other hand, there is also the question of data already collected n times to meet n needs. There are then several possible sources for a data. The lack of rationalization of sources and therefore of data collection induces a significant cost for the company. Data acquisition is a significant part of the cost of an IT project. In addition, this does not promote quality since an action on one source will not necessarily be passed on to other sources. The single collection of data for shared use is a real vector of gains.

New technologies make it possible to capture and exploit data in the service of these ambitions. The subject of processing a large volume of data is now behind us with Big Data technologies and offers / solutions around data are multiplying (data virtualization, data quality, etc.). But before being charmed by these new possibilities, preliminary work around data (data!) Must make it possible to question the purposes of these new technologies upstream of investments and associated projects. A bit like gold: before buying the safe, you first counted the gold you have.

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