5 minute read 9 Apr 2021

5 tips to make Data Governance work in your organization

Authors
Patrice Latinne

EY Belgium Financial Services Data & Analytics Leader

Passionate leader in the broad data science & AI systems. Energized by team empowerment, success and focus on client satisfaction. Married and father of 3.

Ali El Maghraoui

EY Belgium Financial Services Data & Analytics, Information Strategy Executive Director

Passionate about Data & Analytics, Technology & Innovation. Focused on enabling organizations to unleash the full potential of their data. Obsessed by client satisfaction. Proud husband and father.

Riccardo Magnani

EY Belgium Consulting Associate Partner

Great passion for new challenges and curiosity for new professional adventures.

5 minute read 9 Apr 2021
Related topics Analytics and big data AI

Since Data has become a crucial asset for organizations, you have to manage and govern it correctly. But what does that mean? And, more importantly, how do you make it work?

In brief

  • What is Data Governance?
  • What can you do to implement it effectively within your organization?

In this digital era, Data has become one of the most valuable assets of any organization, whatever its size or the industry it operates in.  As it is the case for any asset, you must therefore manage , but also govern it correctly.

When reading this, you are probably wondering what we mean with “govern”.

This article sheds some light on the topic and gives you practical tricks to implement Data Governance effectively in your organization.

1. What is Data Governance?

Data Governance is about how well an organization knows its data. It is about having a common and shared understanding of it, and efficiently and effectively managing it in order to optimize business value.

In practice, it is a combination of:

  • Policies, standards and processes;

  • People and organization; and

  • Technology.

A company puts these in place to manage its data throughout its full life cycle, and to give it high availability, usability, integrity and quality.

Let’s have a closer look at these three core components of Data Governance.

Policies, standards and processes

Policies indicate the general rules about data that everyone within an organization must follow.

An example of a data policy could be : “Verify and maintain the quality and integrity of data through all the steps of its lifecycle.”

Every organization should take time to define its data policies, which must be aligned with its current business objectives and realities. This means you need to:

  • Review these policies on a regular basis to verify whether they are still relevant;

  • Check that they provide the right trade-off between data privacy and security, and availability of data for analysis and value generation;

  • Translate the policies into standards, on which processes and procedure can be based.

 

People and organization

These policies, standards and processes are executed by people, and guaranteed by an organization.

There are different Data Governance operating models. They go from completely independent or decentralized, to fully centralized. There is of course no good or bad model and organizations often opt for hybrid models with different splits of responsibilities between the Data Governance Office and the business lines. The most important is that every organization has to choose the model that best matches its reality and ambition.  


Tools and technology

Technology enables people and organization to efficiently comply with data policies, standards and processes. The minimum requirement is for it to support  the processes of defining the data and managing its metadata, performing data lineage and impact analysis, and implementing and monitoring data quality.

 

2. Tips and tricks for an effective Data Governance

Now that you know what Data Governance entails, one more question is probably on your mind: what makes a Data Governance program succeed or fail?

Before we explore some tips and tricks, it is important to understand that Data Governance is not a one-shot effort or program, and is definitely not achieved in one corner of an organization, be it IT or business. It is first and foremost a continuous effort of refinement and improvement, driven by a partnership and collaboration between all departments.

 

Tip #1 Drive the scope

The Data Governance program must have a clear scope and clear objectives and, as we have seen before, these must be aligned with the organization’s business goals and priorities. It is important to define what Data Governance means to the organization, and how it will help it achieve its global goals. This scope and these objectives must be evaluated on a regular basis to verify whether they are still relevant to the organization at any strategic point in time.

 

Tip #2 Make the change

Data Governance is about people & organization more than anything else. Many such programs have failed because they were not paying enough attention to them.

A successful Data Governance should be accompanied by the appropriate change management and Data Literacy program, where:

  • People should clearly understand what is in it for them and how this is impacting their jobs,

  • Each stakeholder should understand what is needed from her/him during the data lifecycle, and

  • Everyone in the organization understands the data lifecycle, and how is it transformed through the business process she/he is working on.

 

Tip #3  Connect teams around data

The people and the underlying organization need to be connected, have common data objectives, and speak the same data language. The glue between all these is the metadata and the data catalogs in which this metadata is stored and managed.

Having this single metadata management system within the organization, where all the stakeholders can create and share definitions, knowledge, and understanding of the data will facilitate the integration and leveraging of data assets across the different departments, processes, and applications.

 

Tip #4  Better data

Is Data Quality part of Data Governance or not? This is the eternal debate… Whatever the answer is, a solid Data Governance program must consider putting in place a strong framework to implement monitor and remediate Data Quality checks regularly. These checks must be made available to all stakeholders to optimize the transparency of the data the organization uses, thereby increasing its trustworthiness.

 

Tip #5 Measure and sustain

This is the last but probably the most important tip. Remember, Data Governance is a continuous effort of refinement and improvement. To achieve this, the organization must:

  • Define from the beginning clear KPI’s and baselines that are aligned with program objectives,

  • Evaluate on regular basis, via different audits (compliance, security, quality, etc.), how much the program is on track with regards to these baselines, and

  • Make the necessary adjustments when required.

 

3. Conclusion

Data Governance is not just an initiative you carry out at a given time. It is a continuous program that you need to embed within the very fabric of your organization. Of course, it is about technology and policies. But most of all, it is about people. It is about defining the right reflexes to communicate and build together a shared understanding of the organization’s data. This is easier said than done. But it is the only way to unleash the true power of data, the gold mine of the 21st century.

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Summary

Since Data has become a crucial asset for organizations, you have to manage and govern it correctly. But what does that mean? And, more importantly, how do you make it work? This article sheds some light on the topic and gives you practical tricks to implement Data Governance effectively in your organization.

About this article

Authors
Patrice Latinne

EY Belgium Financial Services Data & Analytics Leader

Passionate leader in the broad data science & AI systems. Energized by team empowerment, success and focus on client satisfaction. Married and father of 3.

Ali El Maghraoui

EY Belgium Financial Services Data & Analytics, Information Strategy Executive Director

Passionate about Data & Analytics, Technology & Innovation. Focused on enabling organizations to unleash the full potential of their data. Obsessed by client satisfaction. Proud husband and father.

Riccardo Magnani

EY Belgium Consulting Associate Partner

Great passion for new challenges and curiosity for new professional adventures.

Related topics Analytics and big data AI