Bleckmann aims to maximize the impact of their data on the entire organization, resulting in a need for proper data management and clear processes. They looked to us for guidance.
Bleckmann is a third-party logistics expert for omnichannel fashion & lifestyle commerce. Python Predictions has previously collaborated with Bleckmann to create a data strategy that is aligned with their business strategy.
Last summer, we started a follow-up track on data governance and information management. We first conducted a maturity assessment to identify which data issues led to the most double work and frustration. We then installed a pragmatic data governance framework, in which we focused on:
- Setting up an information structure, making sure that information is easily accessible and with the right level of detail. The structure is applied from a business glossary and data dictionary, all the way up to a company-wide intranet.
- Establishing a common understanding of business concepts and data points.
- Identifying existing and introducing new data roles and responsibilities across the organization.
- Setting up processes to improve master data management.
Our work resulted in better communication across teams, enhanced data quality, and less time spent searching for information.
