80% of D&A Initiatives will Fail by 2027 due to lack of Crises

By 2027, 80% of data and analytics (D&A) governance initiatives will fail due to a lack of a real or manufactured crisis, according to Gartner, Inc.

“A D&A governance program that does not enable prioritized business outcomes fails,” said Saul Judah, VP Analyst at Gartner. “Through recent crises, such as COVID-19 or increased energy costs, chief data & analytics officers (CDAOs) who successfully helped their organizations navigate through those disruptions, understood the crisis and quickly pivoted D&A to help business leaders address it.”

Taking a strategic approach to D&A governance and positioning it as an essential business-centric model is more significant than a tactical approach, where D&A teams operate governance reactively, focusing on just one asset – data-only governance.

“CDAOs should stop taking a center-out, command-and-control approach to D&A governance, and instead, rescope their governance to target tangible business outcomes, make it sensitive to opportunity and risk, and agile and scalable as their organization evolves,” said Judah.

Gartner analysts said that the typical “one-size-fits-all” governance approach used today is not the approach needed by most organizations (see Figure 1).

Figure 1. One-Size-Fits-All Model Is No Longer Enough

Source: Gartner (February 2024)

Adoption of GenAI Will Refresh Outdated D&A Governance

As the adoption of artificial intelligence (AI) and generative AI (GenAI) technologies accelerates, CDAOs also have the chance to renovate outdated D&A governance practices, and include AI as part of their improved governance program. AI governance is the process of assigning and assuring organizational accountability, decision rights, risks, policies and investment decisions for applying AI.

At the same time, CDAOs should incorporate AI and GenAI-enabled capabilities to their D&A governance program. Gartner predicts that by 2027, the application of GenAI will accelerate time to value of D&A governance and master data management programs by 40%.

“Before CDAOs embark on delivering GenAI use cases, they must ensure their organization’s core, genetic information is well governed. For this, they should use and prioritize GenAI capabilities that would lead to faster time to value for their governance program,” said Anurag Raj, Sr Principal Analyst at Gartner. “GenAI capabilities can help in this through ramping productivity in governance activities such as cataloguing and classification, broader and easier adoption (e.g., better self-service capabilities), or capabilities that solve specific business challenges, such as enriching customer data for better targeting.”

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