Inside Analysis

Who Owns the Data?

Based on an InsideAnalysis webinar sponsored by Experian “Who Owns the Data? Don’t Get Surprised.”

When we say “data”, a lot of topics come to mind, like big data, analytics, data governance, data quality, machine learning, IoT and artificial intelligence, just to name a few. However, an interesting question related to these disciplines that one should be asking is Who owns the data? It is surprising that this topic has not been discussed earlier.

This article touches upon two research studies conducted by Experian, which focus on data priorities. We take a look at standard policies on data ownership and structures, and how to effectively empower Chief Data Officers.

What is data ownership?

There are many ways to look at data ownership.

Ownership implies responsibility. Can something that is not owned be stolen? The answer is No. Data is actually owned by organizations or individuals in organizations. And we need to know who is responsible for this data.

Ownership also implies accountability. There are situations of data hoarding, when people don’t want to share data, possibly because of concerns with copyright issues, especially those involving sensitive information. Or it could be quality issues, or sometimes just a lack of willingness to share. There are protocols and procedures around sharing data and knowing the owner of data makes things easier.

Nonetheless, the question of data ownership raises a lot of other questions – Where did it come from? How would it be used? Once we have the data, there is also the question of how one would manage that data. In order to answer these questions, it is pretty important to know who really owns the data.

 Why Chief Data Officers?

All the talk about data has given rise to this new role in organizations, called the Chief Data Officer.

But then, is this role really necessary?

Traditionally, information and data have been managed by Chief Information Officers. However, these CIOs invariably manage applications and not data. And Chief Technology Officer or CTO roles are usually focused on the technological infrastructure – the purchase, usage, and management of applications and technology, and not really data per se.

Thus, came the role of Chief Data Officer or a CDO, which focuses on who owns the data, how data is used, how it gets shared, how it is managed and so on. This role has grown immensely over the last couple of years, with a lot of organizations already having them or seriously thinking about having them.

Strategic business priorities with respect to data

Experian conducted a research study and developed a report called the Global Data Management Benchmark Report. In this study, they talked to over a thousand professionals, primarily in the UK, US, Brazil and Australian markets. The objective was to know what organizations are trying to accomplish with data and the business objectives and goals they are trying to meet.

The chart below shows findings from this study – areas that use data heavily, comparing global and US markets.

In today’s digital environment, a lot of areas require heavy usage of data. A major area of focus for most executives surveyed is customer experience. Digital transformation efforts across organizations have driven the need for extensive data in order to develop more proactive customer success models. The emphasis is on understanding customers better through data.

Talent and Workforce Development seems to be another key priority for businesses. As businesses compete for talent, there is a huge shortage of data talent (for example, data scientists), with not many people being formally trained in this domain. When the C-suite responses were isolated, it was found that talent management and workforce development was the topmost priority for these executives.

Achieving cost efficiencies, growing on a scale and managing the associated risks were found to be other areas which relied heavily on data.

Data Inaccuracy

The success of these efforts depends on the accuracy of data, the trust we have on that data and organizations’ ability to access this information whenever necessary. However, this data is not always accurate and accessible.

“On average, 30% of customer and prospect data is considered to be inaccurate in some way, with the main contributors to this inaccuracy being human error, lack of communication between departments and an inadequate data strategy.”

Over 89% of executives believe this inaccuracy is undermining their ability to provide an excellent customer experience. Synergy among business units and advancements in analytics would eventually be able to overcome these inaccuracies to a great extent. However, organizations need to have leaders who can take ownership of this data and set the right strategy concerning data.

Many executives also raised concerns about the sheer volume of data.

“89% of executives agree that increasing volumes of data make it difficult to meet regulatory obligations.”

It becomes crucial for businesses to accurately ‘filter’ this data, prioritize and use it in a way that best meets business objectives and goals.

Data inaccuracy, compounded by sheer volume would eventually bleed into other processes, leading to poor governance and hindering organizations’ ability to gain meaningful insights from this data. Data ownership thus becomes even more critical for businesses.

 Data ownership – current vs ideal scenarios

The question of data ownership is two-pronged – who actually owns the data and who ideally ought to own it.

 Who currently owns data?

When asked who currently owns data in their organizations, most professionals felt it was the IT department. This has been a legacy way of managing data, in which access to information is obtained by making a request for it and waiting for one or two weeks. In today’s digital environments which require information in real-time and where time is of the essence, this might not be the right way to manage data.

Many executives said the CEO responsible for data, which has been an interesting finding, as it shows how far organizations have come with respect to data ownership.

The CDO role has been growing steadily over the past few years and looks set to become a norm over the coming years.

Who should own the data?

“89% of US businesses believe that responsibility for data should ultimately lie within the business, with only occasional help from IT. “

The reasoning behind this is that business users also happen to be subject matter experts and know when and how data needs to be used and analyzed. 91% of executives and even the IT department agreed, with both groups feeling that IT should be merely supporting them, without sole ownership.

Organizations need access to information in real-time, and cannot afford to wait for weeks on end to get hold of it. An ideal scenario would be to have somebody at the helm to understand the technology and the underlying challenges better.

The CDO role is thus gaining popularity in many organizations, especially those in regulated industries like financial services and healthcare.

Top motivations for wanting a CDO

Capitalizing on big data opportunities and achieving a competitive advantage in the market seem to be top factors for organizations wanting to have a CDO.

Data-driven projects would invariably bring in a certain amount of risks, in which case organizations feel that having a CDO at the helm who is well-informed and in charge of implementing data management policies and processes would be crucial.

CDO Perceptions

Once an organization has a CDO, the perception of the business looks uplifting, with the CDO seen as making a significant difference.

“76% of CIOs say their role fails to cover a majority of the responsibilities that a CDO would have, with 88% of them feeling a CDO role would add value to their data management strategy.”

Most CDOs agree, with 86% reporting they feel they have an important role to play in keeping companies on track with digital transformation plans.


CDO Resources

When CDOs were asked what kind of responsibility they were given upon joining the organization, and how it has increased since then, the results were interesting and even shocking.


As it turns out, not all CDOs are given full authority when they join, many don’t have the budget they need and do not have ready access to applicable tools and technology.

A shocking observation was the lack of clear remit/objectives. If organizations are spending money on hiring a CDO, they need to make sure that the CDO knows how to use data to meet business objectives. The CDO needs to be given authority to initiate and execute those data-driven projects. Without clear remit/authority, it would be difficult to accomplish business goals.

How do we empower these CDOs?

If organizations want meaningful insights from the data, it is necessary to empower their data officers and staff associated with data management.

“Globally, less than half of data owners (47%) surveyed say they have the budget and authority needed to enact new policies, with a majority of them feeling it is limited in some way.”

Executives don’t necessarily have what they need and empowerment is definitely an issue. It all starts with an organizational mindset – organizations need to be able to divide responsibility, give people authority to institute data governance policies and make appropriate changes to data in a way that it becomes useful.

In summary

In huge organizations, achieving synergy between business units is crucial. While achieving cost-savings through technology would best be handled by CTOs and streamlining processes would best be managed by COOs, the CDO needs to ideally focus on enhancing data quality, accuracy, and accountability. Knowing what kind of data the organization has, how to make use of it and how to add value to further business objectives, would be critical responsibilities of the CDO.

A CDO needs to be a trusted partner working in conjunction with other C-level executives to aid organizational processes, helping them find the best possible data they need when they need it.

It is important for the CDO to ask the right questions, constantly revisiting data sources, implementing data quality monitoring tools, ensuring the business is getting the right insights – in summary, serving the purpose for which it was originally intended.

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