Did you know that the average annual cost of bad data is about $12.9 million ?

In the digital world in wich we live, data is at the heart of many businesses. Almost no economic activity escapes the "data", this black gold coveted by web giants like Google, Facebook, or Amazon. Indeed, the core of their business and marketing strategy revolves around collecting user data because it allows them to make their services more efficient, or in the case of internet actors, to better target potential customers with their advertisements.

More broadly, all organizations rely on data to manage their activities, teams, customer relations, and marketing. Data offers many advantages: it makes the company more efficient, tracks market or competition changes, understands customer needs through their behavior, and of course, is essential for commercial prospecting and marketing. Since the advent of digital technology, data is literally everywhere.

While large companies have organized themselves accordingly, this is not always the case for smaller businesses. However, SMEs continue to be encouraged to embrace digital evolutions and organize around strategic choices based on data, even though many traditional companies (SMEs) still overlook the digital aspect.

But collecting and using data is not everything. Indeed, data is like a website: having it is good. But it must be updated subsequently. If information is correct and relevant at a certain point, nothing is permanent. News, market context changes, and the evolution of the data itself can quickly make it obsolete or outdated. And nothing is worse than relying on poor quality data. "Poor quality" means many things at once. It can be erroneous, incomplete, or outdated data. But it can also be poorly maintained or validated information. And this happens quickly: data may have been poorly collected, maintained, or updated, either due to human errors, computer problems, etc.

The impact of poor quality data on your company can be particularly damaging

According to a Gartner study, the average annual cost of bad data is about $12.9 million. Of course, this is a global study involving large companies, which can inflate the figure mentioned. But beyond the amount, the negative effect on a company is real and takes various forms: poor sales forecast evaluation, missed sales opportunities, and therefore loss of revenue. But it can also lead to cost increases if your company relies on erroneous information leading to less efficient processes, less well-calibrated operational costs, etc. In the marketing field, bad databases can be particularly damaging. Imagine launching a mailing campaign based on an outdated client file where half of the addresses are incorrect… And this doesn't even address the reputational risks for your company.

In short, there's no need to beat around the bush: optimal data quality for your company has become an absolute must-have. Last year, the renowned Gartner Institute published a list of 12 tips for companies to ensure their data quality, focusing on the importance of identifying and defining what good data is, determining who is responsible, monitoring, and enriching data to continuously improve it.

Before this, of course, a crucial starting point lies in choosing which data you can rely on. Whether it's commercial prospecting or market analysis, Inoopa can help you have qualitative and up-to-date data to rely on (plan a meeting). We can also help you enrich your current databases and make them more relevant and, therefore, more efficient.