Data management is critical for businesses.
To find out more about data governance and the related issues, I met with Marcelo Cardoso, Co-founder of Prodago Solutions, which provides data governance advisory services and markets Prodago (Lean Data Governance Platform).
How does a data governance process add value to a business?
The main value of data governance is the ability to explore data and facilitate innovation using digital transformation initiatives. Without a governance process, the business could be exposed to data quality issues that could have a significant impact. Today, data are at the heart of all organizational decisions and transformations (analytics, business intelligence, artificial intelligence, automation, etc.). Organizational transformation and innovation initiative do not see the light of day without quality data.
What do businesses generally do?
There is always some form of data governance in a business, even though it may go by another name. Defining data formats for new IT systems or configuring intranet user access rights are examples of data governance. The main issue is that, generally, organizations react to problems rather than identifying the risks underlying data used in the most critical business processes and operations and applying preventive corrective measures.
What are the greatest errors to avoid and what approach do you suggest?
The most common error when implementing such processes is the failure to link governance measures and business objectives. The traditional approach consists in setting up an “organization”. A committee is created and a network of data managers for the various sectors is identified, but this does not always work.
We suggest identifying a sector’s business objectives and analyzing transformation initiatives in terms of these objectives (for example, a 3600 view of clients). The critical processes associated with these initiatives and the data they use are then identified. Corrective measures (data rules and responsibilities) are applied if gaps are found in the quality of data needed to ensure the performance and security of the processes.
It’s important to have some traction within the organization and set priorities because data governance cannot be implemented across the board unless the relative importance of the data has been determined. This requires considerable effort.
Technology is evolving rapidly and data are increasingly more prevalent (internet of things, megadata, etc.). How does this impact governance?
Organizations are aware that data are no longer just the result of a business process, they now see data as an asset. More and more, data are becoming the responsibility of the business side of an entity rather than just the IT department. In recent years, advances in areas such as artificial intelligence, predictive analyses, etc. mean that entities are making more intensive use of data and not necessarily in the context in which the data were created. Data are collected from various sources and cross-referenced to generate value. Governance is essential in this context.
To call on the services of Marcelo and his team, visit website contact page.
If you would like to further explore this topic, Marcelo suggests visiting this site for some interesting articles.
25 Apr 2017 | Written by :