No industry is immune from the impact of technological, social, or economic disruption. Today, Chief Data Officers are playing a crucial role in navigating the complexities of the ever-changing world and engineering response to the changing demands of markets. 

So, what’s next for the Chief Data Officer role? How can CDOs navigate disruption, bring business value to their organizations, and, ultimately, get an invitation to the board of directors? 

In this article, you will learn:

1 – A brief overview of the Chief Data Officer role


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2 – The current state of play & challenges for Chief Data Officers

3 – How to extract the true value of data & use cases

4 – What the future holds for CDOs

What are Chief Data Officers?

Chief Data Officer is in charge of developing and implementing how the organization acquires, manages, analyzes, and governs data. Chief Data Officers are responsible for putting data on the business agenda instead of treating data as a by-product of running a business.

Until the 1980s, the role of the data manager was far from being a senior position. The Chief Data Officer first appeared in the early 2000s. One of the first appointed Chief Data Officers was Cathryne Clay Doss of Capital One in 2002. Five years later, Usama Fayyad took the CDO role at Yahoo!. Today, Chief Data Officers are the driving force that leverages data to drive business outcomes.

Even though businesses recognize the importance of data leadership, data value is still a vague concept for many. Therefore, there’s a lack of meaningful metrics to measure the effectiveness of the Chief Data Officer role. 

Not only are CDOs expected to provide a 360-degree view of the company data that is usually scattered across multiple silos, but they are also expected to use data for the transformation of business models and, ultimately, increase revenues. 

When the inevitable business disruption occurs, CDOs are expected to drive the transformation, put in place the right tools and strategies for innovation and execution.

The two opposing trends

Last year, The World Economic Forum found that 84% of business leaders are currently “accelerating the digitization of work processes” and automating tasks. For many Chief Data Officers, the pandemic is the first significant disruption and a growth catalyst that is yet to be embraced and leveraged. 

Martin Guther (SAP’s VP, Platform&Technologies CoE MEE) says that the pandemic acted as an accelerator that enforces current trends rather than a disruptor by itself. He sees the current trends for CDOs coming from two very different perspectives – legislation and innovation. 

“CDOs need to look into how the data is taken care of. This is actually something that has been mandated by law for quite some time, and now it’s enforced – companies need to put a lot of work into how they treat the data that customers give them,” says Guther. 


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The other trend is innovation – newer techniques to learn from mass data are booming. The usage of breakthrough technologies like AI and machine learning opens up the possibilities to extract insights from previously unavailable data.

The clash of legislative restriction and the increased technical capability for innovation challenges Chief Data Officers to keep a balance between compliance and drive innovation while reinforcing customer trust. In a data-driven world, a growing amount of business data contains personal or sensitive information. If applications use this data for statistical analysis, it must be protected to ensure privacy.

Extracting the value of data

We’ve all heard the saying circulating in the business world for the last decade – “data is the new oil.” But is it possible to measure the value of data to back up this statement? And if it is, then why do Chief Data Officers are struggling to measure their success?

According to SAP’s Martin Guther, data is an intangible asset that is often not valued with accounting standards. 

“Many companies know more about the value of office furniture than about the value of their data. Data is not represented anywhere in the company’s balance sheet – that presents a big challenge for CDOs as they need to find ways to prove the value of their work.”

So how can CDOs measure the value of data? 

“There are three quantifiable elements that drive the data value – incremental revenue, cost reduction, and risk mitigation,” says Guther. Simply collecting more data does not necessarily create more value. 

To extract the data value, CDOs need to look at a combination of three factors: data volume, data quality & data use. Chief Data Officers must actively manage each aspect. 

“All three drivers need to come together as they are multiplied by each other. If one element is out of the equation, the value won’t be extracted.” For example, the data volume and quality are top on the technical side, but the findings are not applied across departments on the organizational side. Ensuring the formula is used correctly on both technical and organizational levels is probably the most complex challenge for a CDO. 

How data helped Saturday Night Live show gain more viewership

For example, the media and entertainment industry quickly realized that extracting the data value from their content is key to long-term growth. In 2015, Michael Martin (SVP Product, Technology and Operations at NBC Entertainment Digital) encountered a challenge – even though much of the SNL show’s library was online, the audience still wasn’t able to access the content they liked. As a result, only recent shows got the most viewership. 

To let fans discover SNL’s content in full, Martin’s team realized they need to address data to drive the viewer’s experience. SNL library wasn’t getting enough visibility because of a mismatch between the content and the metadata. The most reliable data consisted of dates, titles, and characters. The problem was that this data didn’t consider that titles were often vague to conceal a joke, fans didn’t know when the shows were aired, and character names were not always known.

Martin’s team used a mixture of metadata and semantics to model data and capture every character, cast member, season, impersonation, sketch, and each item’s characteristics. This reformulated approach to data mapped the library of the SNL show in much more detail and allowed the fans to discover and access their favorite content. 

Why letting data guide the way is critical

As for recent examples, both the freight and aviation industries experienced accelerated disruption due to the pandemic. With the worldwide approvals of the Covid-19 vaccine, the global distribution of vaccines in extremely demanding circumstances was a challenge for Lufthansa Industry Solutions. 

Susan Wegner, VP Artificial Intelligence & Data Analytics at Lufthansa Industry Solutions, is convinced that following the principle of “letting data guide the way” was crucial for adapting to novel and demanding circumstances. 

The overall network was severely affected by the pandemic, with borders closing and planes being grounded, since a considerable share of the cargo volume is usually transported in the bellies of passenger airplanes. 

“Besides transforming some of the passenger airplanes into cargo freighters, we have algorithms,  which optimize the production planning. With our freight forecast AI we had a clear competitive advantage and the ability to adapt quickly, because we knew we had the algorithms on our side”, says Wegner. 

AI algorithms Lufthansa Industry Solutions deploys were initially designed to learn and retrain themselves continuously. This was particularly beneficial since an unusual event like a pandemic does not paralyze the AI algorithms as they are not solely based on historical data. Thus, within a very short time of taking the pandemic into account, these algorithms adjusted their forecasts and calculations accordingly. 

Another critical element for successful adaptation was the way data and AI leaders managed their teams. AI and data teams worked closely together with the process and business departments. 

“With these cross-functional and diverse teams, we make sure that decisions in the process and business departments are based on the optimal amalgamation of data and experience. This proved a valid approach as we all knew quite early that not many of us have a lot of experience with pandemics, and data never lies”, says Wegner. 

While some departments analyzed data for decision-making purposes on demand, others utilized AI to automate processes and tasks, not only in terms of speed but process efficiency and costs, since the latter one is also quite important.

“From a leadership position, Covid changed a lot,” says Wegner. She took the role at the beginning of Covid-19 and could not meet the whole team in person. It was a huge challenge to build up relationships and trust, encourage and motivate the team virtually. 

“I was very lucky since the team is basically digital native and had great ideas on how to connect virtually. But personal meetings count, and therefore I tried to arrange additional one-to-ones always when it was safely possible.” 

From Decentralized Data Teams to Data Evangelism

Mina Saidze, Data Evangelist at idealo (a German price comparison service), shared how her company approached generating the most value from data. “The advantage of having a decentralized data team structure is that each unit can specialize in a certain domain. However, the pitfall is that silos can evolve over time and, hence, the lack of communication and collaboration hinders innovation”, says Saidze.

The company decided to combine the best of two worlds – a hybrid approach between decentralized domain specialization and inspiring an understanding of how important data is for an organization as a whole. 

The Data Leadership Team and the CTO approved the centralized Centre of Excellence and the Data Evangelist role to help strengthen the collaboration among tech and business units within the organization. 

Mina’s role is developing best practices, identifying relevant use cases, and building up an Analytics Community to tackle the current challenges.

What’s next for the CDO role? 

Even though organizations have woken up to the fact that data deserves a place on the board, the CDO role is not yet defined. Gartner estimates that by 2025, 90% of large organizations will have a CDO. So what does the future hold for the Chief Data Officer role?

“If a CDO wants to go into the direction of being a senior business leader, being a part of the board of directors, the data assets that she or he is managing and the value must be clear,” says Martin Guther.

Chief Data Officer is one of the most critical roles right now as it brings together innovation, compliance, technical & business perspectives. There’s a lot of risk yet a tremendous opportunity if you get it right.

According to Mina Saidze, a Chief Data Officer role should not be seen as encroachment by CIOs and CTOs. In fact, a CDO is a person that underpins the company strategy with data and ensures the data quality and generates value out of this asset.

“A future trend I observe is that CDOs do not treat data as a liability but as an opportunity. Until recently, many CDOs were focused on limiting the downsides of data, such as GDPR policies or ensuring data quality. Soon, we will need CDOs who have a vision and the know-how to generate new revenue streams for the company by developing data-driven products, services, and processes. An entrepreneurial mindset, paired with a data background can help the CDO of the future to succeed in this role”, said Saidze.

As Martin Guther states, “CDOs should ask themselves what they truly want to achieve. Do they want to be innovative thinkers and risk their ideas being too progressive to be applied in the organization? Do they want to be a technical master working behind the scenes? Or do they want to become a transformational leader acting across all these domains of expertise? I think that there’s a great opportunity to grow and take their place at the board of directors.”

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