Why Top-Down Data Governance is Failing
Posted: Tue Feb 11, 2025 4:27 am
Every year, enterprises worldwide waste millions of dollars on failed data initiatives. While there are a number of factors that contribute to this, data governance is often cited as a major hurdle. That’s because too many organizations view data governance as a monolithic undertaking that can only be achieved using a top-down approach. But that line of thinking is outdated and doesn’t align with the needs of the modern enterprise.
Here are three reasons top-down data governance is failing, and what you can do about it.
Reason 1: Waterfall culture
The first reason top-down data governance fails is because of the “waterfall” approach to policy management. Using this model, all decisions are made by a small group of individuals. Their job is to plan out every detail of the governance program and then cascade policies down to practitioners.
Traditional Data Governance Model
As Tomasz Tunguz describes in his book, “Winning with Data,” there are several problems with this methodology:
These programs lack agility and resilience due to bottlenecks at the data producer/consumer threshold
Data teams spend more time navigating denmark whatsapp number data bureaucracy than working with data, which negatively impacts ROI
In most organizations, those who try to understand the availability and use cases of data assets encounter inefficiencies, partial answers, and confusing systems
When data work isn’t transparent, people don’t trust it, leading to data brawls, a.k.a. people showing up with different versions of the same analysis and arguing over the method by which they got there
Limiting collaboration and access means missing out on new ideas and opportunities for innovation
The hard truth is that it’s impossible to build data-driven cultures under waterfalls. In fact, 69% of data engineers say their current governance program makes their jobs more difficult. That’s because they didn’t have a voice in developing the program, even though they play a significant role managing the data.
You won’t gain adoption within your organization if you don’t bring your community along for the ride.
Reason 2: Only focused on risk avoidance and compliance
Another reason top-down governance programs fail is because they only focus on risk avoidance and compliance. Although data protection is a critical component of your data governance strategy, it should not be the only consideration. Data governance should holistically address the entire data and analytics process, enabling safe, efficient, and reliable project collaboration.
Locking down all access to data is counterproductive. It slows down your team and keeps them away from valuable, revenue-driving insights. Data producers can’t keep up with never ending ad-hoc requests, and data consumers are frustrated with the delays in getting what they need.
Here are three reasons top-down data governance is failing, and what you can do about it.
Reason 1: Waterfall culture
The first reason top-down data governance fails is because of the “waterfall” approach to policy management. Using this model, all decisions are made by a small group of individuals. Their job is to plan out every detail of the governance program and then cascade policies down to practitioners.
Traditional Data Governance Model
As Tomasz Tunguz describes in his book, “Winning with Data,” there are several problems with this methodology:
These programs lack agility and resilience due to bottlenecks at the data producer/consumer threshold
Data teams spend more time navigating denmark whatsapp number data bureaucracy than working with data, which negatively impacts ROI
In most organizations, those who try to understand the availability and use cases of data assets encounter inefficiencies, partial answers, and confusing systems
When data work isn’t transparent, people don’t trust it, leading to data brawls, a.k.a. people showing up with different versions of the same analysis and arguing over the method by which they got there
Limiting collaboration and access means missing out on new ideas and opportunities for innovation
The hard truth is that it’s impossible to build data-driven cultures under waterfalls. In fact, 69% of data engineers say their current governance program makes their jobs more difficult. That’s because they didn’t have a voice in developing the program, even though they play a significant role managing the data.
You won’t gain adoption within your organization if you don’t bring your community along for the ride.
Reason 2: Only focused on risk avoidance and compliance
Another reason top-down governance programs fail is because they only focus on risk avoidance and compliance. Although data protection is a critical component of your data governance strategy, it should not be the only consideration. Data governance should holistically address the entire data and analytics process, enabling safe, efficient, and reliable project collaboration.
Locking down all access to data is counterproductive. It slows down your team and keeps them away from valuable, revenue-driving insights. Data producers can’t keep up with never ending ad-hoc requests, and data consumers are frustrated with the delays in getting what they need.