(White paper) Three simple solutions to create value with your data
Data quality management has thus become an imperative for any company, regardless of its stage of digitalization. Because poor quality data has a cost: 10 million euros per year, according to Gartner.
We are all data workers
To explain what a data worker is, let’s take an example. Mehdi is an intern in the sales department of a large company. He targets prospects and makes calls to present the service he wants to sell. He fills in the information about the customer and the call process in an Excel file.
The problem is that Mehdi doesn’t really care about the quality of the data he fills in: he misspells the prospect’s last name, forgets to fill in the company’s location and only transcribes 2 of the 3 questions raised. He had to move fast and after all, he thought, these errors would have little influence on a database already containing 500 prospects.
However, not only is Mehdi not the only one to make this type of mistake, but he is mistaken in thinking that these data are not essential. In fact, they will be used by the marketing department, which wants to automate the analysis of consumer expectations based on their place of work.
At 21, Mehdi is already handling data that will have a strategic impact on the company. He is a data worker.
Exploiting your data: an imponderable
Therefore, for many companies, data management has a huge influence on their business model: the ability to analyze information becomes more important than the product sold. We are witnessing a paradigm shift: from a service provider logic to a data provider logic.
For example, in retail, with the emergence of online sales platforms, product data is becoming the core of companies’ selling power. In the banking sector, it is customer data that is most valued. The same goes for the pharmaceutical industry, which is in the midst of a revolution with “health tech” representing a total of 55 billion euros raised worldwide in 2021, with the main players vying for control of health data.
Having data, and more specifically quality data, is therefore vital for companies, whatever their sector of activity.
The financial impact of poor data quality on businesses
- According to Gartner, companies lose between 10 and 13 million
each year due to poor data quality.
- Every year, 55 hours of work and €35,000 are lost by companies
companies because salespeople use bad lead data.
- Incomplete and inaccurate data leads to a decrease in
of 20% per year.
Employees spend nearly half their time solving data quality
data quality issues.
- 21% of companies have lost reputation due to poor data quality.
quality of their data.
Fortunately, solutions exist!
Download our book and discover simple solutions to :
- to exploit more simply the ever-increasing quantities of data;
- Build a corporate culture based on smooth data exchange;
- Launch and grow using the right tools and processes.
To discover, it’s here !