Foundational governance policies
The first step is to ensure key governance policies are clear and easily accessible for non-data people. Once clear, concise policies are created, data leaders can present these to the senior management team for sign off and to receive feedback on ensuring their accessibility. It is imperative to highlight the importance of data to senior executives and stakeholders and to create a vision of how and why these policies will improve value and processes.
Once the policies are signed off, it will encourage buy-in from stakeholders and have a higher chance of earning their long-term support for the strategy. To bolster this, data leaders need to include the importance and value of the data office in the storytelling to achieve buy-in. Then, when buy-in has been achieved, the delivery of the strategy and the division of data ownership needs to be agreed upon.
Data ownership
With the support of the stakeholders and the C-suite, the building of a data ownership model is needed. One DataIQ member suggests dividing the organisation into key areas known as buckets to identify data owners. These buckets own the information and must agree to the foundational practices before moving forward.
Some suggested categories for bucketing are:
- Customer data
- Colleague data
- Finance data
- Product
An effective strategy is to identify who sits at the top of which bucket and have the data team work directly with them to support on issues and challenges. This will further help improve trust and collaboration as well as enhancing the ever-evolving data culture of the organisation.
Encourage collaboration with the data team
Working with each of these buckets separately is a good start, but can others within the organisation be encouraged to work with and trust the data function? A top tip from the session attendees is to focus on specific problems, use a data lens to give a fresh perspective to these problems, and then work with the function in question to solve the problem. When it comes to identifying problems and assessing a hierarchy of importance, data teams need to work with business areas and stakeholders and then clearly explain how and why this priority list has been created.
It is recommended that data quality is the best starting area, as helping to improve data quality and automating processes is a quick way to enhance efficiency. Once a few use cases and success stories have been achieved, it is important that these are filtered throughout the whole organisation to highlight the positive work the data function do and encourage future collaboration.
Another way to encourage collaboration is by utilising data champions and data stewards. Finding people who are interested in data within different organisational functions to be internal champions is a great way to make sure data is always in consideration as well as improving data culture. Deploying people from the data function into these other non-data functions to act as data stewards can also help maintain a data-centric agenda in all areas of the business.
Final thoughts
Building data strategy is a hugely important aspect of any data function’s work but numerous DataIQ members find that a business cannot have a strong data strategy without first having foundational governance in place.
Creating clear, concise governance policies and getting support from stakeholders is the strongest start possible, followed by identifying and deciding ownership of the governance in each function. All these steps will build strategy and improve collaboration with the data function, therefore enhancing trust in the data process and data office.
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