Benefits of the roadmap to improve data governance
Posted: Wed Jan 22, 2025 6:02 am
Find out why implementing the roadmap to improve data governance and align it with the company's data management.
Implementing good data management often clashes with the company's Data Governance policies . This crossover between data leaders and governance leaders is actually based on a mistaken internal conception of the subject. Let's unravel the misunderstanding.
The limitations generated by management models that are too vertical and segmented, where each area “defends” its portion of responsibility, no longer respond to business objectives in a context where evolution is imbued with a collaborative spirit.
That is why, nowadays, most companies around the world that car owner database to make all aspects of data management coexist in an evolved way have the roadmap as their main tool . This is an extremely useful document to quickly visualize the sequence of objectives and desired results. Having this type of document at hand and accessible allows all interested parties to be aligned and to maintain a clear vision of the milestones reached by the company, in order to continue growing based on the achievements made.
Lack of a standardized approach to governance (56%) and lack of clear roles (49%) are two of the most common issues that prevent achieving harmonious data governance.
Source: Garner
Being ambitious is the key
Limitations and rigidity are not functional to new business models, and when it comes to data governance practices, flexibility is what enables constant scalability.
In this continuous process of adaptability-analysis-growth, it is ideal to implement different governance styles for different business scenarios. There are as many governance models as there are industries and business propositions. That is why the best governance practices are characterized by having a customizable roadmap that allows you to better understand the key stages, available resources, and people involved in each link of the business strategy.
However, in practice many organizations still face frequent problems that stop the natural evolution of the data strategy, and can be expressed as follows:
The governance model is no longer aligned with the company's data and analytics strategy
Data governance is not mature enough to allow business evolution
The teams involved in data governance are not enough
In this conflict-ridden scenario, how can we establish the foundations for more efficient governance?
Every CDO should focus on defining priorities, evaluating options, implementing a governance framework, and defining a gradual progress or evolution plan that not only considers the evolution in management but also in the governance of the new data involved. Discussing strategic ambitions is everyone’s responsibility, and the more involved they are in “laying the foundations” of the strategy, the smoother the growth process will be. Then the time will come to define an action plan and build an effective governance structure. This will be much simpler if the footprints for a strategic monitoring approach were laid in the previous step.
Implementing good data management often clashes with the company's Data Governance policies . This crossover between data leaders and governance leaders is actually based on a mistaken internal conception of the subject. Let's unravel the misunderstanding.
The limitations generated by management models that are too vertical and segmented, where each area “defends” its portion of responsibility, no longer respond to business objectives in a context where evolution is imbued with a collaborative spirit.
That is why, nowadays, most companies around the world that car owner database to make all aspects of data management coexist in an evolved way have the roadmap as their main tool . This is an extremely useful document to quickly visualize the sequence of objectives and desired results. Having this type of document at hand and accessible allows all interested parties to be aligned and to maintain a clear vision of the milestones reached by the company, in order to continue growing based on the achievements made.
Lack of a standardized approach to governance (56%) and lack of clear roles (49%) are two of the most common issues that prevent achieving harmonious data governance.
Source: Garner
Being ambitious is the key
Limitations and rigidity are not functional to new business models, and when it comes to data governance practices, flexibility is what enables constant scalability.
In this continuous process of adaptability-analysis-growth, it is ideal to implement different governance styles for different business scenarios. There are as many governance models as there are industries and business propositions. That is why the best governance practices are characterized by having a customizable roadmap that allows you to better understand the key stages, available resources, and people involved in each link of the business strategy.
However, in practice many organizations still face frequent problems that stop the natural evolution of the data strategy, and can be expressed as follows:
The governance model is no longer aligned with the company's data and analytics strategy
Data governance is not mature enough to allow business evolution
The teams involved in data governance are not enough
In this conflict-ridden scenario, how can we establish the foundations for more efficient governance?
Every CDO should focus on defining priorities, evaluating options, implementing a governance framework, and defining a gradual progress or evolution plan that not only considers the evolution in management but also in the governance of the new data involved. Discussing strategic ambitions is everyone’s responsibility, and the more involved they are in “laying the foundations” of the strategy, the smoother the growth process will be. Then the time will come to define an action plan and build an effective governance structure. This will be much simpler if the footprints for a strategic monitoring approach were laid in the previous step.