What goes into an ESG data management strategy?
It’s a good start to have the data that you need. But successful data management makes it comprehensive, easy to find, and full of actionable insights for teams and business leaders.
Ambiguity and gaps in the data that you collect lead to mismatches between expectations and actual outcomes (in the most flattering terms).
Though the data you collect for ESG will be particular to your firm and its areas of interest, the principles that go into creating a successful data strategy are the same, regardless of your intended aim.
The foundations of a data management strategy are as follows:
1. Data Governance
Effective data governance ensures that your data says the same thing to everyone who reads it.
For example, if your supply chain emissions data reads differently from one team to the next, how can you - or anyone else - trust your ESG credentials?
Competing versions of the truth simply don’t fly when it comes to raw data. This is why solutions such as Master Data Management (MDM) and Product Information Management (PIM) ensure coherence, reliability and value in the data you collect.
Our free, downloadable guide walks you through the 5 steps needed to achieve better data governance.