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Data driven: Definition, benefits and methods

- Reading Time: 4 minutes

In the era of Big Data, companies are collecting ever larger amounts of data. But not all companies are making the most of it. And yet, organizations that place data at the heart of their strategy generally see their performance improve. So what are the benefits of a data-driven approach? And how to implement it? That’s what we’ll look at in this article.

What is a data-driven organization?

When we talk about Data driven organization, this means that strategic decisions are based on the analysis and interpretation of data. In other words, companies take full advantage of business intelligence to improve their customer and market knowledge. In the end, this brings more value and improves the competitive advantage of organizations. For example, through more targeted communication, more personalized products or offers that better meet the needs of the target. 

But beware, it is not enough to collect data. It is also necessary to interpret the available information and make decisions according to the situation.

Why develop a data-driven strategy?

The concept of data-driven management consists in basing its decision-making on concrete and analyzed information. And there are many advantages for all organizations, whatever their sector of activity (e-commerce, supply chain, industry…)

Help to take decisions

The use of data and adequate analysis in the decision-making process contributes to better results. And this is for several reasons: 

  • Data understanding: data-driven companies improve their knowledge of the market and their targets. 
  • Predictive analysis: beyond a detailed understanding of the data, data-driven management allows us to anticipate different hypotheses. Depending on the possible scenarios, the company can make the best decision to achieve the desired result.
  • Risk reduction: thanks to predictive analysis based on reliable data.
Improve the customer relationship

Through a sales and marketing strategy based on analytics, companies gain a better knowledge of their target. In doing so, they can address their customers and prospects in a more personalized way.

For example, through segmentation for emailing campaigns, marketing teams can send a different message to prospects who are new to the brand, who have abandoned their shopping cart, who have already purchased products, etc. This allows them to improve the effectiveness of their campaigns. This improves the customer experience and multiplies the conversion potential.

If the data-driven strategy applies perfectly to prospecting, it is also the case for customer loyalty. Indeed, the collected data allow to better understand the customers and to anticipate their needs. For example, it is possible to segment existing customers according to their purchase frequency. As soon as a drop in purchase frequency is observed, the sales teams can discuss with the customers to understand the cause.

A better use of customer Data

It is possible to use the data to improve the offer proposed to customers. The idea is to develop a product that perfectly fits their needs. Beyond customer data, companies can also retrieve information from competitors. This will allow them to suggest an improvement to a product or create a new one. 

Reduce the costs

Although data-driven management is generally applied to marketing and sales, it concerns all areas of the organization. And notably the company’s finances. Indeed, thanks to the data collected, it is possible to :

  • Improve employee and/or machine productivity
  • Identify non-essential costs and make the most of available resources; 
  • Find partners offering a better quality/price ratio, etc. 

In fact, according to a study conducted by the Harvard Business Study, 48.4% of companies that have started a data-driven approach have seen a significant reduction in costs.


How to focus your strategy on data?

The implementation of a data-driven strategy relies above all on good data governance. Here are the steps to follow.

Set up a data collection

This is the basis of a good data-driven strategy. For this, it is possible to collect data from the organization’s website, social networks, internal information, or from other players in your sector of activity. 

But be careful, if the data sources are multiple, it is useless to collect all the existing data. You need to focus on the relevant data to your objectives, but also, and above all, the data that is reliable and unbiased

Data processing

The aim is to guarantee the data quality to simplify its understanding and access by all. That is, data analysts or data scientists, but also business experts. Indeed, the data-driven culture must be applied by a maximum number of employees to be effective. And this is true both when enriching the database and when using it.

To make data more accessible, it is necessary to clean it up (remove unnecessary information or duplicates) and standardize it (in particular through a standard format for all the company’s data). As this work is particularly time-consuming, it is preferable to use automation tools (Hadoop, CRM, Power BI, …) and to define processes.

Data analysis

This is the center of the data-driven strategy. It is about giving meaning to the collected information. It is about transforming data into real decision-making tools. It is precisely the work of the data analysts and data scientists that makes it possible to give value to data.

After analyzing the data, it is mandatory to present reports to decision-makers. These dashboards must then provide context to the data so that it can be applied to the business. Thus informed, the business experts will be able to select the best strategic choices.

A data-driven strategy for better decisions

In the context of a massive increase in the use of technology and data volumes, companies must develop a data-driven culture. This means optimizing data collection, processing, and analysis. In doing so, companies will have all in their possession to make better decisions, whether it be in terms of customer relations, products offered, cost reduction, etc.

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