In our previous article, we explained why data governance is critical for enterprises. We also talked about the differences between defensive and offensive data governance to achieve your data strategy.

In this new article, we want to focus on what kind of data governance you need and its trend according to your business sector.

When it comes to implementing data governance, the approach an enterprise will take and where it fits on the data strategy spectrum is solely based on its business environment. Indeed, a data governance strategy isn’t set up uniquely: it’ll change from one sector to another.

Here we’ve taken a look at three different sectors: the healthcare/hospital sector, the retail/eCommerce sector, and the banking/insurance sector. We’ve identified which approach each of these industries takes today, and how it will differ from tomorrow.

Healthcare and Data Governance

As hospitals have a highly regulated environment, their Data Governance strategy will take on a very defensive approach.

Indeed, today in the healthcare department, data quality and protection are essential. This sector has a large amount of sensitive information regarding its patients. Their data is used to save lives, treat specific symptoms, and find new cures…so bad data can lead to big risks.

However, with the rise of “Healthtech” companies, the industry is becoming more and more competitive. Hospitals and other healthcare businesses will have to merge towards a more offensive strategy in the years to come. This sector will have to balance between keeping their defensive approach to their data, and continuously innovating on their services in order to keep up with the competition.

Retailers / eCommerce and Data Governance

On the other end of the spectrum, retailers and eCommerce actors take on an offensive data governance strategy.

This industry sees new actors come into the market every year, even every month! With all of this competition, it is crucial for retailers and online businesses to produce value with their data in order to offer personalized services, innovative products, etc.

With that said, consumers are now more and more protective with their data. With the rise of machine learning and AI techniques, people are questioning the ethics around their data’s uses. Also, the increasing rules and regulations regarding data privacy and security are forcing enterprises in this sector to change their data management strategies to comply with these new laws.

In the future, retailers will have to take on a defensive approach while still continuously producing value and innovating.

Banks / Insurance and Data Governance

The banking and insurance industries are right in the middle.

Both require strong defensive data governance because of the regulatory pressures they face. These sectors also work with very personal data, so it is essential to implement a strong defensive strategy.

Regardless, the banking and insurance industries are seeing new actors come in the market. With these new online infrastructures, digital services, and fully personalized options, this sector is seeing a rapid shift in data governance strategies.

Banks and insurance companies will have to not only keep focusing on their data quality and security but also take on a more offensive approach to their data in order to face these new web giants and offer innovative products and services.

How to Start Implementing a Data Governance Strategy

Getting started with implementing Data Governance can be a very overwhelming task.

We’ve created a Lean Data Governance Canvas to help you ask and answer the right questions. Just like the famous “Lean Canvas”, we’ve re-arranged elements to help enterprises set up “Lean” Data Governance and help your business find the right approach to take on data governance.

About Author

About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Organizations trust Actian data management and data intelligence solutions to streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data and AI division of HCLSoftware, at actian.com.

Enterprises dealing with their data are realizing how important it is to implement data governance to effectively and efficiently manage their data assets.

To fully understand what Data Governance is, many definitions exist:

“Data governance is a quality control discipline for adding new rigor and discipline to the process of managing, using, improving, and protecting organizational information.”
IBM Data Governance Council

“Data governance is the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.” Dama DMBok

“Data Governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.”
The Data Governance Institute

“Data governance is the formal orchestration of people, processes, and technology to enable an organization to leverage its data as an enterprise asset.”
MDM Institute

What is certain is that these definitions are far from being fun, but before we get into defining what data governance is, let’s see the reasons why it has become a strategic subject for enterprises.

What Drives Enterprises to Implement Data Governance?

In our experience, we’ve learned that enterprises tend to have one or several of these issues within their organizations:

Tribal knowledge: Usually enterprises have a person or select group of people who produce, work with and understand their data assets. However, the rest of the organization has no knowledge on their data (where it comes from, its value, its quality, etc.). This results in enterprises having siloed information that is difficult to use and share.

Big mess: In the last decade, many complicated information systems have appeared resulting in enterprises having massive amounts of unorganized data. Data users are therefore subjected to data where their quality, uses or even location is unknown.

Compliance: All enterprises are subjected to some form of compliance may it be data privacy, general data usage or ethics. Those that do not have governance in their organizations will suffer from these rules and regulations.

Implementing Data Governance therefore helps enterprises resolve these problems.

With Data governance, enterprises are able to create a data fluent organization, organize their data and comply to the increasing regulatory demands.

Why Data Governance Fails in Enterprises

However, enterprises often look past implementing Data Governance. These organizations believe that:

• Governance implies control and not value.
• It slows down business.
• It is more of an IT concern than a business concern.
• Governance projects implemented in the past have failed too many times before.
• It is too big, there are no resources available.
• It’s nice to have, but not a priority.

What is a Good Strategy for Data Governance?

With all of that said, it is essential for enterprises to build the right sized Data Governance. There is not a unique way of implementing data governance: enterprises must know what kind of governance they need, the right style, and where they stand in the governance landscape.

We’ve identified two types of strategies when to comes to implementing Data Governance:

Defensive Data Governance

This dimension of Data Governance is more focused on risk control and risk management. Here, enterprises are making sure they respect data compliance (such as GDPR), privacy, and security. This framework goes hand in hand with some of the definitions seen above where it is more about “control”.

Offensive Data Governance

This dimension is more focused on producing value with data. With an offensive approach to Data Governance, enterprises are prioritizing value production and innovation.

Learn more about defensive & offensive data governance.

About Author

About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Organizations trust Actian data management and data intelligence solutions to streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data and AI division of HCLSoftware, at actian.com.