Organizations – and in particular their data governance programs – flourish when the people within them are able to collaborate effectively. But what are useful ways to facilitate collaboration that will enhance the data governance program and help the broader organization to more effectively achieve its goals? We explored this topic at a recent user group and found there are really two parts to collaboration that are crucial – first is collaboration between the business and the data governance team; the second is the growing trend toward data sharing that should be supported by transparent agreements that build trust.
Collaborating successfully with the business
It’s important for core data governance teams to engage with the business in a proactive and constructive way from the very beginning of any project. Here are a few best practices that were shared:
- Focus on value delivery first. Early on, focus on just a very few key projects, and do these well. Choose projects that will deliver real, observable value to the business. If possible, select a part of the business that could potentially evangelize data governance.
- Learn to speak the language of business stakeholders. Data governance people may use terms that are second nature to them, but business stakeholders may not understand what those mean. Translate terms into language the business user will connect with.
- Ask the business what their pain points are early in any project. Then work to address those pain points through the project, and communicate this to the business. Show them how the project will enhance their ability to reach their goals.
- Create an impact map. For example, identify who the key stakeholders are in the project directly, and which stakeholders across the organization need to be brought on board to drive adoption. Also, look to see who the team’s business partners are and if the data governance project will have an impact on them.
- Communicate, communicate, communicate. Develop a communication strategy about a data governance project early on, and communicate intensively with key stakeholders. Remember to reach out to the wider business unit, too. For example, consider using guerrilla marketing techniques such as a short “101 Guide” style summary of the project left on desks.
By engaging with the business as partners, data governance teams are not just sowing the seeds of success for their current project, but also for projects to come.
Enhancing collaboration through data sharing agreements
As the technology ecosystem evolves, the need for data is increasing. As a result, data sharing is becoming a real driver for growth. Data sharing is the disclosure of data from one or more organizations to a third-party organization or organizations, or the sharing of data between different parts of an organization.
The best practice is to have data sharing agreements (DSAs) in place between all parties involved. Having a formal DSA is beneficial because it makes it clear what data is being shared, and how it can be used, for example. It can also state what regulatory responsibilities the parties have, and desired operational goals or outcomes. Driving the growth of DSAs are several trends, including:
- Data as a service– Many organizations are moving towards providing data as a service to the consuming parties by creating Open API environments, and so they are using DSAs to help manage relationships with partners who are receiving data as a service.
- Data-driven decision-making – Organizations want to use data to support analysis of the choices they have to make. Having DSAs in place allows executives to have more trust in the information they are working with, and to use information from a wider range of sources.
- Protecting market reputation – Failing to have proper agreements in place can seriously damage the brand, as Facebook learned in the Cambridge Analytica scandal.
- Regulatory compliance – Privacy regulations like GDPR are enforcing organizations to have DSA’s in place when data is transferred between the legal entities or different regions to make sure safeguards in place for data in rest and during the data transition.
In short, having DSAs in place helps build trust and provide transparency for organizations that wish to engage in data sharing. Automating data usages – connecting these agreements directly with the data they refer to through a robust data governance platform – can further enhance these outcomes.
Tackling collaboration is a critical part of successful data governance projects and a stepping stone to creating data-centric cultures within organizations of all kinds.
Ram is responsible for fast-tracking Collibra engagements and centralizing data governance thought leadership to influence product features.