4 steps Towards Data-driven Companies

With the advent of Big Data, improving data performance, whether its source is internal, from surveys or market studies, is eminently strategic. Effective internal corporate structuring is therefore essential.
4 steps Towards Data-driven Companies



Today, having the right information at the right time is crucial to grow a business or improve a strategy’s effectiveness. With digital tools, collecting data, especially through market studies, is always easier, faster, and more accurate. But the data is then more voluminous, complex, and sophisticated.


Today’s challenge is to capture its strategic value to produce operational results that can be provided to the right people at the right time. And because we know that 88% of existing data is not analyzed, we can see that companies have a tremendous opportunity to leverage it.



Each department has information that is potentially useful for others, but due to ignorance or strategy, it is not shared, to the eventual detriment of the entire company. Designating a project leader before performing a market study or when implementing a data collection system will ensure that there is someone within the company who can oversee that the collected data is used.


Ideally, the project leader should be at the origin of the need. At the very least, they must own it in order to bear responsibility, from design to dissemination. It is this person who identifies the needs and defines the objectives, signs the contract and establishes a relationship with the provider, collects, stores, secures, and analyzes the data, selects the recipients, and determines when to share the results.


When truly responsible for this data, they can then guarantee its quality, its reliability, its use, and its collection strategy. Without this work, there’s a strong likelihood that the market study’s results (or any other kind of data) will end up underneath a pile of files.



This approach is so crucially important that the project leader’s scope of action must be cross-functional. Whatever their position within the company, they must dialogue with all departments that might be interested in the data, and not just with marketing. These include IT, innovation, communication, marketing, etc. These departments must perceive the person as a partner and an asset when determining the company’s overall strategy, just as they are themselves. This is not always easy to do.


To achieve this, they must intervene upstream and solicit all stakeholders to assess their needs and expectations. The study will be designed as accurately as possible for maximum usefulness. When the results are available, they will be able to disseminate them in the clearest and most relevant way possible.


This cross-functionality provides them with an overview, thanks to which they will be able to focus on the data supporting the processes and the growth of the entire company. They will then be able to disseminate it at the most strategic level. Moreover, according to a study by Data Galaxy, over time 83% of Chief Data Officers will be part of a company’s senior management, compared to only 50% today.


Measure and improve every meaningful interaction


Data quality is also essential and an important lever for improving its performance. According to a Gartner study, large companies estimate losses related to poor data quality at $15 million per year. The project leader must therefore be equipped with flexible, powerful tools to make the most out of the data.


For example, popular data platforms are becoming more powerful and now provide greater finesse and better relevance when processing the mass of information collected. Historically popular CRM (Customer Relationship Management) tools have been joined and complemented recently by DMPs (Data Management Platforms) or CDPs (Customer Data Platforms).


Then, the data must be decoded, interpreted, and above all “translated” to make it useful and operational for everyone. Visual analysis is one of many tools that facilitate understanding and ensures more global ownership. It enables a more fluid, more efficient exchange of sometimes different languages and codes between departments.



In smaller businesses or where data is less massive, a project-mode organization is often preferable. It is proven to be efficient enough. We know that the bottom line is to make someone responsible to oversee the project internally and who has the legitimacy, authority, and means required to carry out the company’s data management.


In companies in which the data collected is both high volume and hyper strategic, implementing a “data-driven” strategy often requires the creation of a Director or at least a dedicated position. According to the 2017 BCD2O barometer of the Chief Digital/Data Officers, in France, 18% of the companies reported having a Chief Data Officer in 2016, and then 23% in 2017. According to a Gartner study, 90% of large companies worldwide will have a Chief Data Officer by 2019.