Expert opinion

Why are data-driven decisions not always reliable?

Intelligent and informed decision-making in companies always poses the problem of the method… and if companies are now convinced that the answers lie in the exploitation of their data, they remain no less suspicious about how to implement a Data Driven strategy, based on the analysis and interpretation of data. Indeed, a doubt about the relevance of this data constitutes a real risk for any decision-making.

95% of European companies are crippled by a lack of trust in data-driven decisions.

Source QUANTEXA – Rapport recherche mondiale Data in Context: Closing the Data Decision Gap

“Company data” is a real asset of the company, but it is still necessary that the reference data on which operational data is based is administered correctly so that it is accurate and thus truly useful!

Many companies are still moving from siloed management, manual or semi-automated processing and processes, to which data is subjected, and the situation is worsening with increasing volumes from disparate sources.

79% of respondents agree that data degradation has increased as a result of the Covid-19 pandemic. This is largely due to the fact that many employees have changed positions. Their phone number, address and function have also changed.

Source VALIDITY – Rapport The State of CRM Data Management in 2022

Companies do not always measure the extent of change. They sometimes simply set up processes to validate the quality of the data, without focusing their efforts on the value of the data and the resulting generation of relevant indicators. These indicators must be accessible to all trades to help them define efficient strategies.

More and more organizations are realizing that it is difficult and costly to aim for perfect data accuracy.

Source MCKINSEY – Rapport The Data-Driven Enterprise of 2025

This is where setting up an MDM makes sense. A Single Data Repository will enable global and centralized governance to orchestrate, deploy and control the internal control of the company’s master data It will automatically detect and resolve inconsistencies. It will also be able to integrate collaborative processes and quality controls throughout the life of the data.

But beyond the implementation of such a tool, awareness of the value of data implies close collaboration between IT and business lines.

IT is responsible for managing the architecture (tools for acquiring, storing, managing, structuring and exploiting data) and the business lines for managing content, defining collaborative processes to manage and ensure data quality, exploiting data.

More generally, the entire company must evolve towards a Data Driven culture so that its employees can make their decisions based on qualified, structured and actionable data via ready-to-use but also self-service services.