DAMA fan talking here! Data Management and Data Governance Policies are not a goal, but a means. Policies describe the best or preferred way of doing things to get desired outcomes. Policies are often enforced, but not explained and when people have to do something they do not understand, they will push back. According to DAMA, data governance is a means for data management and data management's goal is to enhance the value of data. So the first thing to do is to explain he value of DG in general for your organisation, and of policies specifically to the people that need to adhere to them. Always, I repeat always, make sure that your DM and DG activities and policies link to real business requirements and outcomes. We work for them!

Implementing Data Governance framework in modern & dynamic business indeed is a great challenge. What is key is to explain the context & impacts properly. In my opinion the best way is to use live examples. It's best to illustrate the impacts of issues linked to lack of proper Data Governance. It could be examples from Supply Chain and logistics issues, maybe challenges on invoicing or bringing accurate reporting. Spotting key impacts and explaining those in business language usually help to have the buy-in.

Facing difficulties and pushback from colleagues on data governance policies is a usual matter in Data Governance. They are often deployed by a centralised model as a starter but it can evolve when it is mastered. Data policies are here guide usage, sharing and valorisations patterns of data within an organisation and not everybody can agree at some given time. However it is possible to convince stakeholders with the right arguments focused on their own priorities. Explaining to them that they will be able to drive data access, enforce data security, trace more easily data shared with others, and contribute to a global compliance factor and Data Governance mastery within the organisation are some leads you can give to reluctant actors.

I believe incorporating peer feedback increases a sense of ownership and can reduce resistance as they will feel part of the process. Involve colleagues in developing and refining policies by listening to their concerns and suggestions. Show the value of data governance by explaining how it improves accuracy, efficiency, and security. Trainings and workshops can help colleagues understand the benefits and importance of following these policies in the long term. Show tangible short-term results, such as improving data quality or streamlining processes, by adopting governance policies. Small wins help build trust and demonstrate the value of governance.

To overcome resistance to data governance policies, start by engaging colleagues in open discussions to understand their concerns and perspectives. Clearly communicate the benefits of the policies, such as improved data quality, security, and compliance, and how these align with organizational goals. Provide training and resources to help them understand the policies' importance and implementation. Involve key stakeholders in the policy development process to foster ownership and buy-in. Lastly, highlight success stories or case studies that demonstrate the positive impact of effective data governance.