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COVID-19 has changed the workplace into something that even two years ago would have been unimaginable. Millions of workers are still working from home and despite indications that the management in many companies would like to see everyone back in the physical workplace, it seems unlikely that this is going to happen. Numbers are all over the place on how many people will continue to work remotely. Depending on where you look, anything up to 100% of the work force is going to stay home.

The Future of Data Jobs

In fact, at the end of last year, The Future of Jobs 2020 report from the World Economic Forum, found that COVID-19 has caused the labor market to change faster than anyone had expected. The research indicated that what used to be considered the “future of work” has already arrived.

It predicts that by 2025, automation and a new division of labor between humans and machines will disrupt 85 million jobs globally in medium and large businesses across 15 industries and 26 economies. Roles in areas such as data entry, accounting and administrative support are decreasing in demand as automation and digitization in the workplace increases. More than 80% of business executives are accelerating plans to digitize work processes and deploy new technologies; and 50% of employers are expecting to accelerate the automation of some roles in their companies. In contrast to previous years, job creation is now slowing while job destruction is accelerating.

There is also a dramatic shift in the emphasis in terms of employment. Citing LinkedIn data gathered over the past five years, the report suggest that some 50% of career shifts into data and artificial intelligence are from fields that are not directly related to either discipline. That figure is much higher for sales roles (75%), content creation and production positions, such as social media managers and content writers (72%), and engineering roles (67%).

Related Article: Is a Single Source of Data the Way Forward for Data Governance

Digital or Data Officer?

Above all that is the management of these data-driven roles through either the Chief Data Officer, or the Chief Digital Officer. While the two titles share the same abbreviation the two are not the same job. The chief data officer has a significant measure of business responsibility for determining what kinds of information the enterprise will choose to capture, retain and exploit and for what purposes.

The similar-sounding chief digital officer or chief digital information officer often does not bear that business responsibility, but rather is responsible for the information systems through which data is stored and processed. A chief data officer's purpose is to connect the technological results to the needed business results. 

Various other roles entail understanding the business value. It means using data to derive business outcomes. Some responsibilities include the governance, advising & monitoring enterprise data. In terms of operations, it means enabling data usability along with efficiency and availability. Do organizations need a chief data officer if they have someone in charge of digital technologies?

The Primary Metrics for an Effective Chief Data Officer

Chris Bergh is CEO of MA-based DataKitchen, a DataOps consultancy and platform provider that manages analytics creation and operations. He points out that data operations are a factory. Data continuously enters on one side of the pipeline, progresses through a series of steps and exits in the form of reports, models and views.

“The data pipeline is the operations side of data analytics. It is helpful to conceptualize the data pipeline as a manufacturing line where quality, efficiency, constraints and uptime must be managed. As manager of the data factory, the CDO oversees the data factory, including new analytics creation,” he said. The effectiveness of the CDO is encompassed by two metrics: analytics cycle time and errors.

  1. Analytics Cycle: Analytics cycle time is the time required from the inception of a new idea (or a new request for analytics) to the final delivery of charts and graphs. The reason that this matters, is that analytics cycle time determines business agility. Decision-makers need information to respond to competitive opportunities and threats. Companies with the shortest analytics cycle time behave more nimbly and pull out ahead of competitors.
  2. Analytics Errors: Analytics errors are a double-edged sword. First, they erode trust in data, which ultimately infringes on the success of the data team. Second, errors create unplanned work, which pulls data scientists and analytics away from creating new analytics, impacting cycle time.

“The job of the CDO is to view the data factory from the 30,000-foot level and institute change that reduces cycle time and errors,” Bergh added. This can be accomplished using new methods and automation called DataOps.” DataOps incorporates agile development, devops automation and statistical process controls to compress analytics cycle time and reduce data factory errors to virtually zero. Agile analytics can more effectively add value to business operations, assuring the data organization's strategic role in the enterprise.

CDO Needs to Build a Community of Data Citizens

Organizations need a chief data officer because data is a key asset. To benefit from data, organizations need to make it meaningful. CDOs are the change agents in organizations that are responsible for that. And if they are not, they must evolve, said Stan Christiaens, Chief Data Citizen at NY-based Collibra.

CDO responsibilities remain a moving target. No matter what people say, the reality today is that this position is typically not a board- or executive-level position. And it's definitely not yet an established role.” It is up to CDOs to put data as a real item on board and executive committee slide decks. By that, I do not mean as a sub-bullet in compliance conversations. I mean as a real priority,”

Christiaens added: “Data is an important company asset — just like money or people. If the CFO is the only one at an organization who is thinking about money, that organization will likely not be successful. The same is true for data. CDOs who want to be successful data change agents need to expand their focus to consider the larger organization and its users.” To do this, CDOs must work to ensure employees across the organization become data citizens — people who rely on access to trusted data to do their jobs, make business decisions and drive business transformation.

This is still an ideal. Most people are not data citizens today, meaning they either do not know where to go for data or, more commonly, they do not trust the data they can access. That means the decisions they make are usually not based on data, which can pose a serious risk for the business. “Building a culture of data citizens — and data intelligence — requires a data-first mindset and the ability for employees to use trusted data to do their jobs.”

Chief Digital Officer vs Chief Data Officer: Should the Roles Be Separated?

Carter Busse is CIO at Mountain View, CA-based Workato, believes that there is no real need to sperate the roles of chief digital officer and chief data officer. Sometimes, he said, it is helpful to segment roles where additional insight is needed — ie. CISOs versus CIOs — but in this case the division in responsibility between chief data officer and chief digital officer is an unnecessary one.

The division in roles comes from a perceived incompatibility between IT leaders and business objectives. “As an IT leader that leads with the business in mind, I know that incompatibility is untrue. So, to me, this division presents a larger call to action for IT leaders: to incorporate business goals, objectives, and messaging into the core of their organizations,” he said. This includes owning the data strategy for their companies and providing a trusted framework for business leaders to make data driving decisions.

“Something I learned early on in my career was to own my organization as an IT leader with business partnership in mind. Instead of just “keeping the lights on” I doubled down on messaging my team’s value-add to the business, and framing our collective action as a business driver,” he added.

“Not only did that help accelerate my personal career path, but it proved to the larger organization that my team was a “load bearer” for the company. You can hire great talent for more technical data management, but you cannot have a successful IT organization without intentional, top-down business collaboration. “