Why is Data Governance Important?

Master Data Management Blog by Stibo Systems logo
| 4 minute read
January 27 2022

In today's data-driven world, data has become a valuable asset for businesses of all sizes. The ability to collect, store and analyze various amounts of data has transformed the way organizations operate, make decisions and compete in the marketplace. However, with this power comes responsibility. Organizations must ensure that their data is accurate, reliable, secure and compliant with regulatory requirements. This is where data governance comes into play. Data governance refers to the set of policies, procedures and standards that organizations implement to manage their data assets effectively.

In this blog post, we will explore why data governance is crucial for organizations, the benefits it provides and how it can help organizations achieve their business objectives. Whether you are a small business owner or a large enterprise, understanding the importance of data governance is essential to stay ahead of the competition and make informed business decisions.

 

Table of contents:

 

blog-data-governance-strategy

 

What is data governance and why is it important?

Data governance is the process of managing the availability, usability, integrity and security of the data used in an organization. It involves the development and implementation of policies, procedures and standards for managing data across the organization.

At its core, data governance is about establishing clear rules and processes for managing data throughout its lifecycle, from collection and storage to use and disposal. This includes defining data quality standards, ensuring compliance with regulatory and legal requirements, managing risks associated with data and facilitating collaboration between different teams and departments within the organization.

Data governance also involves defining data ownership and accountability, establishing roles and responsibilities for data management and providing training and education to employees on data governance practices. It requires a collaborative approach that involves stakeholders from across the organization, including IT, data management, legal, compliance and business teams.

Ultimately, the goal of data governance is to ensure that an organization's data is accurate, reliable and secure, and that it can be effectively used to support business decisions and objectives. By establishing clear rules and processes for managing data, organizations can increase the value of their data assets, reduce risks associated with data and improve their overall business operations.

 

Who works with data governance within an organization?

Data governance involves multiple stakeholders from different teams and departments within an organization. Here are some of the key roles and functions that typically work with data governance:

  • Executive management

    Executive management plays a critical role in establishing the strategic direction for data governance within an organization. They are responsible for ensuring that data governance aligns with the overall business objectives and for providing the resources necessary to support data governance initiatives.

  • IT

    The IT department is responsible for implementing and maintaining the technical infrastructure necessary to support data governance, including data management tools, data storage systems and data security measures.

  • Data management

    The data management team is responsible for developing and implementing data governance policies, procedures and standards. They ensure that data is accurate, complete and consistent across the organization and that data quality standards are met.

  • Legal and compliance

    Legal and compliance teams ensure that data governance practices are in compliance with regulatory and legal requirements, such as data privacy laws and regulations.

  • Business

    Business teams use data for decision-making and are responsible for ensuring that data governance practices align with their business objectives. They may be involved in defining data requirements, identifying data sources and developing data models.

  • Audit and risk management

    Audit and risk management teams provide oversight and assurance that data governance practices are effectively mitigating risks associated with data management.

  • Data stewards

    Data stewards are responsible for the day-to-day management of specific data sets, ensuring that data is accurate, complete, and consistent. They may also be responsible for data entry, data cleaning and data validation.

Overall, data governance requires a collaborative approach that involves stakeholders from across the organization. By working together, organizations can effectively manage their data assets, reduce risks associated with data and improve their overall business operations.

 

 

What are the benefits of data governance and why do organizations need it?

Data governance provides several benefits to organizations, including:

1. Improved data quality

Data governance helps ensure that data is accurate, complete and consistent across the organization. This is achieved by defining data standards, policies and procedures for data management, which helps to improve the quality of data and increase the confidence in data-driven decisions.

2. Compliance

Data governance helps organizations comply with regulatory and legal requirements related to data privacy, security and governance. By implementing data governance practices, organizations can avoid penalties, fines and reputational damage associated with non-compliance.

3. Risk management

Data governance helps organizations identify and manage risks associated with data, such as data breaches, data loss and unauthorized access. By defining policies and procedures for data management, organizations can ensure that data is protected from internal and external threats.

4. Improved efficiency

Data governance helps organizations improve their data management processes, reducing duplication and streamlining workflows. This helps to reduce costs and improve efficiency in data management, freeing up resources to focus on other critical business activities.

5. Increased collaboration

Data governance promotes collaboration across different teams and departments within an organization. By defining data standards and policies, organizations can create a common understanding of data, facilitating communication and collaboration across the organization.

6. Better decision making

Data governance helps organizations make better-informed decisions by ensuring the accuracy and reliability of data. This helps to reduce the risk of making decisions based on incorrect or incomplete data.

Overall, data governance is essential for organizations to effectively manage their data assets and achieve their business objectives. By implementing data governance practices, organizations can improve data quality, comply with regulatory requirements, manage risks associated with data, increase efficiency, promote collaboration and make better-informed decisions.

 

Will the importance of data governance increase in the future?

Yes, the importance of data governance is likely to increase in the future. Here are a few reasons why:

  • Increasing amounts of data

    The amount of data generated by organizations is growing at an unprecedented rate. With the rise of the Internet of Things (IoT), social media and other digital technologies, organizations are collecting vast amounts of data every day. As the volume of data increases, so does the complexity of managing that data, making data governance even more critical.

  • Regulatory requirements

    As data privacy concerns continue to rise, regulatory requirements related to data governance are becoming more stringent. For example, the General Data Protection Regulation (GDPR) in the European Union and the California Consumer Privacy Act (CCPA) in the United States both require organizations to implement specific data governance practices to protect personal data.

  • Data security concerns

    Cybersecurity threats continue to increase, and organizations need to take appropriate measures to protect their data assets. Data governance practices, such as access controls, data encryption and data masking, can help to protect data from unauthorized access and mitigate the risks associated with data breaches.

  • Business value

    Organizations are increasingly recognizing the value of their data assets and the potential benefits of using that data to drive business decisions. To realize the full potential of their data assets, organizations need to implement data governance practices that ensure the accuracy, reliability and consistency of their data.

In conclusion, the importance of data governance is likely to increase in the future due to the increasing amounts of data generated by organizations, regulatory requirements, data security concerns and the growing recognition of the value of data for driving business decisions. Organizations that prioritize data governance will be better positioned to manage their data assets effectively and realize the full potential of their data.


Topics: 
Master Data Management Blog by Stibo Systems logo

As Managing Consultant at Stibo Systems since 2011, Sabine Schmidbaur has helped many companies from different industries through their digital transformation. She has deep experience in data governance, business process design and IT strategy with a particular focus on master data and ERP systems.

Discover Blogs by Topic

  • MDM strategy
  • Data governance
  • Customer and party data
  • See more
  • Retail and distribution
  • Manufacturing
  • Data quality
  • Supplier data
  • Product data and PIM
  • AI and machine learning
  • CPG
  • Financial services
  • GDPR
  • Sustainability
  • Location data
  • PDX Syndication

Navigating Change: Engaging Business Users in Successful Change Management

9/20/24

What is Digital Asset Management?

9/11/24

How to Improve Your Data Management

9/3/24

The Future of Master Data Management: Trends in 2023-2025

9/1/24

Digital Transformation in the CPG Industry

8/30/24

5 CPG Industry Trends and Opportunities for 2024-2025

8/29/24

What is the difference between CPG and FMCG?

8/27/24

Responsible AI relies on data governance

8/27/24

6 Features of an Effective Master Data Management Solution

8/15/24

Great Data Minds: The Unsung Heros Behind Effective Data Management

8/13/24

A Data Monetization Strategy - Get More Value from Your Master Data

8/6/24

Introducing the Master Data Management Maturity Model

8/4/24

What is Augmented Data Management? (ADM)

7/31/24

Data Migration to SAP S/4HANA ERP - The Fast and Safe Approach with MDM

7/30/24

Data Governance and Data Protection: A Match Made in Heaven?

7/17/24

The Difference Between Master Data and Metadata

5/26/24

Master Data Management Roles and Responsibilities

5/20/24

8 Best Practices for Customer Master Data Management

5/16/24

What Is Master Data Governance – And Why Do You Need It?

5/12/24

Guide: Deliver flawless rich content experiences with master data governance

4/11/24

Risks of Using LLMs in Your Business – What Does OWASP Have to Say?

4/10/24

Guide: How to comply with industry standards using master data governance

4/9/24

Digital Product Passports - A Data Management Challenge

4/8/24

Guide: Get enterprise data enrichment right with master data governance

4/2/24

Guide: Getting enterprise data modelling right with master data governance

4/2/24

Guide: Improving your data quality with master data governance

4/2/24

Data Governance Trends 2024

1/30/24

NRF 2024 Recap: In the AI era, better data can make all the difference

1/19/24

Building Supply Chain Resilience: Strategies & Examples

12/19/23

How Master Data Management Can Enhance Your ERP Solution

12/14/23

Shedding Light on Climate Accountability and Traceability in Retail

11/29/23

What is Smart Manufacturing and Why Does it Matter?

10/11/23

Future Proof Your Retail Business with Composable Commerce

10/9/23

5 Common Reasons Why Manufacturers Fail at Digital Transformation

10/5/23

How to Digitally Transform a Restaurant Chain

9/29/23

Three Benefits of Moving to Headless Commerce and the Role of a Modern PIM

9/14/23

12 Steps to a Successful Omnichannel and Unified Commerce

7/6/23

CGF Global Summit 2023: Unlock Sustainable Growth With Collaboration and Innovation

7/5/23

Navigating the Current Challenges of Supply Chain Management

6/28/23

Product Data Management during Mergers and Acquisitions

4/6/23

A Complete Master Data Management Glossary

3/14/23

4 Ways to Reduce Ecommerce Returns

3/8/23

Asset Data Governance is Central for Asset Management

3/1/23

4 Common Master Data Management Implementation Styles

2/21/23

How to Leverage Internet of Things with Master Data Management

2/14/23

Manufacturing Trends and Insights in 2023-2025

2/14/23

Sustainability in Retail Needs Governed Data

2/13/23

NRF 2023: Retail Turns to AI and Automation to Increase Efficiencies

1/20/23

5 Key Manufacturing Challenges in 2023

1/16/23

What is a Golden Customer Record in Master Data Management?

1/9/23

Innovation in Retail

1/4/23

Life Cycle Assessment Scoring for Food Products

11/21/22

Retail of the Future

11/14/22

Omnichannel Strategies for Retail

11/7/22

Hyper-Personalized Customer Experiences Need Multidomain MDM

11/5/22

What is Omnichannel Retailing and What is the Role of Data Management?

10/25/22

Most Common ISO Standards in the Manufacturing Industry

10/18/22

How to Get Started with Master Data Management: 5 Steps to Consider

10/17/22

What is Supply Chain Analytics and Why It's Important

10/12/22

What is Data Quality and Why It's Important

10/12/22

An Introductory Guide: What is Data Intelligence?

10/1/22

Revolutionizing Manufacturing: 5 Must-Have SaaS Systems for Success

9/15/22

An Introductory Guide to Supplier Compliance

9/7/22

What is Application Data Management and How Does It Differ From MDM?

8/29/22

Digital Transformation in the Manufacturing Industry

8/25/22

Master Data Management Framework: Get Set for Success

8/17/22

Discover the Value of Your Data: Master Data Management KPIs & Metrics

8/15/22

Supplier Self-Service: Everything You Need to Know

6/15/22

Omnichannel vs. Multichannel: What’s the Difference?

6/14/22

Create a Culture of Data Transparency - Begin with a Solid Foundation

6/10/22

The 5 Biggest Retail Trends for 2023-2025

5/31/22

What is a Location Intelligence?

5/31/22

Omnichannel Customer Experience: The Ultimate Guide

5/30/22

Location Analytics – All You Need to Know

5/26/22

Omnichannel Commerce: Creating a Seamless Shopping Experience

5/24/22

Top 4 Data Management Trends in the Insurance Industry

5/11/22

What is Supply Chain Visibility and Why It's Important

5/1/22

The Ultimate Guide to Data Transparency

4/21/22

How Manufacturers Can Shift to Product-as-a-Service Offerings

4/20/22

How to Check Your Enterprise Data Foundation

4/16/22

An Introductory Guide to Manufacturing Compliance

4/14/22

Multidomain MDM vs. Multiple Domain MDM

3/31/22

Making Master Data Accessible: What is Data as a Service (DaaS)?

3/29/22

How to Build a Successful Data Governance Strategy

3/23/22

What is Unified Commerce? Key Advantages & Best Practices

3/22/22

How to Choose the Right Data Quality Tool?

3/22/22

What is a data domain? Meaning & examples

3/21/22

6 Best Practices for Data Governance

3/17/22

5 Advantages of a Master Data Management System

3/16/22

A Unified Customer View: What Is It and Why You Need It

3/9/22

Supply Chain Challenges in the CPG Industry

2/24/22

The Best Data Governance Tools You Need to Know About

2/17/22

Top 5 Most Common Data Quality Issues

2/14/22

What Is Synthetic Data and Why It Needs Master Data Management

2/10/22

What is Cloud Master Data Management?

2/8/22

How to Implement Data Governance

2/7/22

Build vs. Buy Master Data Management Software

1/28/22

Why is Data Governance Important?

1/27/22

Five Reasons Your Data Governance Initiative Could Fail

1/24/22

How to Turn Your Data Silos Into Zones of Insight

1/21/22

How to Improve Supplier Experience Management

1/16/22

​​How to Improve Supplier Onboarding

1/16/22

How to Enable a Single Source of Truth with Master Data Management

1/13/22

What is a Data Quality Framework?

1/11/22

How to Measure the ROI of Master Data Management

1/11/22

What is Manufacturing-as-a-Service (MaaS)?

1/7/22

The Ultimate Guide to Building a Data Governance Framework

1/4/22

Master Data Management Tools - and Why You Need Them

12/20/21

The Dynamic Duo of Data Security and Data Governance

12/20/21

How to Choose the Right Supplier Management Solution

12/20/21

How Data Transparency Enables Sustainable Retailing

12/6/21

What is Supplier Performance Management?

12/1/21

What is Party Data? All You Need to Know About Party Data Management

11/28/21

What is Data Compliance? An Introductory Guide

11/18/21

How to Create a Marketing Center of Excellence

11/14/21

The Complete Guide: How to Get a 360° Customer View

11/7/21

How Location Data Adds Value to Master Data Projects

10/29/21

How Marketers Should Prepare for the 2023 Holiday Shopping Season

10/26/21

What is Supplier Lifecycle Management?

10/19/21

What is a Data Mesh? A Simple Introduction

10/15/21

How to Build a Master Data Management Strategy

9/26/21

10 Signs You Need a Master Data Management Platform

9/2/21

What Vendor Data Is and Why It Matters to Manufacturers

8/31/21

3 Reasons High-Quality Supplier Data Can Benefit Any Organization

8/25/21

4 Trends in the Automotive Industry

8/11/21

What is Reference Data and Reference Data Management?

8/9/21

What Obstacles Are Impacting the Global Retail Recovery?

8/2/21

GDPR as a Catalyst for Effective Data Governance

7/25/21

All You Need to Know About Supplier Information Management

7/21/21

5 Tips for Driving a Centralized Data Management Strategy

7/3/21

Welcome to the Decade of Transparency

5/26/21

How to Become a Customer-Obsessed Brand

5/12/21

How to Create a Master Data Management Roadmap in Five Steps

4/27/21

What is a Data Catalog? Definition and Benefits

4/13/21

How to Improve the Retail Customer Experience with Data Management

4/8/21

How to Choose the Right Master Data Management Solution

3/29/21

Business Intelligence and Analytics: What's the Difference?

3/25/21

Spending too much on Big Data? Try Small Data and MDM

3/24/21

What is a Data Lake? Everything You Need to Know

3/21/21

How to Extract More Value from Your Data

3/17/21

Are you making decisions based on bad HCO/HCP information?

2/24/21

Why Master Data Cleansing is Important to CPG Brands

1/20/21

CRM 2.0 – It All Starts With Master Data Management

12/19/20

5 Trends in Telecom that Rely on Transparency of Master Data

12/15/20

10 Data Management Trends in Financial Services

11/19/20

Seasonal Marketing Campaigns: What Is It and Why Is It Important?

11/8/20

What Is a Data Fabric and Why Do You Need It?

10/29/20

Transparent Product Information in Pharmaceutical Manufacturing

10/14/20

How to Improve Back-End Systems Using Master Data Management

9/19/20

8 Benefits of Transparent Product Information for Medical Devices

9/1/20

How Retailers Can Increase Online Sales in 2023

8/23/20

Master Data Management (MDM) & Big Data

8/14/20

Key Benefits of Knowing Your Customers

8/9/20

Women in Master Data: Kelly Amavisca, Ferguson

8/5/20

Customer Data in Corporate Banking Reveal New Opportunities

7/21/20

How to Analyze Customer Data With Customer Master Data Management

7/21/20

How to Improve Your 2023 Black Friday Sales in 5 Steps

7/18/20

4 Ways Product Information Management (PIM) Improves the Customer Experience

7/18/20

How to Estimate the ROI of Your Customer Data

7/1/20

Women in Master Data: Rebecca Chamberlain, M&S

6/24/20

How to Personalise Insurance Solutions with MDM

6/17/20

How to Democratize Your Data

6/3/20

How to Get Buy-In for a Master Data Management Solution

5/25/20

How CPG Brands Manage the Impact of Covid-19 in a Post-Pandemic World

5/18/20

5 Steps to Improve Your Data Syndication

5/7/20

Marketing Data Quality: Why Is It Important and How to Get Started

3/26/20

Panic Buying: Navigating Long-term Implications and Uncertainty

3/24/20

Women in Master Data: Ditte Brix, IMPACT

2/20/20

Get More Value From Your CRM With Customer Master Data Management

2/17/20

Women in Master Data: Nagashree Devadas, Stibo Systems

2/4/20

How to Create Direct-to-Consumer (D2C) Success for CPG Brands

1/3/20

Women in Master Data: Anna Schéle, Ahlsell

10/25/19

Women in Master Data: Morgan Lawrence, Infoverity

9/26/19

Women in Master Data: Sara Friberg, Acando (Part of CGI)

9/13/19

Improving Product Setup Processes Enhances Superior Experiences

8/21/19

How to Improve Your Product's Time to Market With PDX Syndication

7/18/19

8 Tips For Pricing Automation In The Aftermarket

6/1/19

How to Drive Innovation With Master Data Management

3/15/19

Discover PDX Syndication to Launch New Products with Speed

2/27/19

How to Benefit from Product Data Management

2/20/19

What is a Product Backlog and How to Avoid It

2/13/19

How to Get Rid of Customer Duplicates

2/7/19

4 Types of IT Systems That Should Be Sunsetted

1/3/19

How to Use Customer Data Modeling

11/15/18

How to Reduce Time-to-Market with Master Data Management

10/28/18

How to Start Taking Advantage of Your Data

9/12/18

6 Signs You Have a Potential GDPR Problem

8/16/18

GDPR: The DOs and DON’Ts of Personal Data

6/13/18

How Master Data Management Supports Data Security

6/7/18

Frequently Asked Questions (FAQ) About the GDPR

5/30/18

Understanding the Role of a Chief Data Officer

4/26/18

3 Steps: How to Plan, Execute and Evaluate Any IoT Initiative

2/20/18

How to Benefit From Customer-Centric Data Management

9/7/17

3 Ways to Faster Innovation with Multidomain Master Data Management

6/7/17

Product Information Management Trends to Consider

5/25/17

4 Major GDPR Challenges and How to Solve Them

5/12/17

How to Prepare for GDPR in Five Steps

2/21/17

How Data Can Help Fight Counterfeit Pharmaceuticals

1/24/17

Create the Best Customer Experience with a Customer Data Platform

1/11/17