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Seven Core Responsibilities of a Chief Data Officer (CDO)

Chief Data Officer in a strategy meeting

The trend in companies hiring Chief Data Officers (CDOs) creates new opportunities for data management professionals who may think that they have reached a plateau in their data careers. Data management experience in multiple disciplines combined with business acumen and executive-level credibility opens doors to leadership in the age of data-driven business.

Data is making massive changes to how we work and how we provide value to an organization. Organizations that view data as an enterprise asset are better prepared to seize opportunities and mitigate risks than those organizations with siloed data efforts. A Chief Data Officer (CDO) not only defines a data strategy to meet current needs but also evolves the strategy to ensure that the organization derives value far into the future.

The purpose of this article is to bring some clarity to the role and responsibilities of CDOs. Let's review the core responsibilities where a CDO must demonstrate knowledge, experience, and a commitment to leading change. These are essential to having a successful CDO career.

Create Business Value: The CDO has the responsibility to seek out opportunities to create value from data. To find those opportunities, requires discussions across the organization, starting with C-level peers. The CDO should be asking such questions as:

  • How can we get value from data?
  • What can the data tell us?
  • Do we want to monetize data, and if so, how will we do that?
  • Are we going to use data for innovation to stay ahead of the competition? If so, how will we do this?
  • How can we use data to drive revenue?
  • How can we use data to optimize processes and reduce costs?
  • What routine decisions do we make that can be automated?

Create a Data Culture: Becoming a data culture is about changing mindsets, ways of thinking, and ingrained practices. It is an evolutionary process that impacts all aspects of an organization. It is a slow and arduous process that starts with using data to create very visible value to the organization. Let's look at some of the ways to move this effort forward.

Promote Self-service Data Analysis: CDO's remove the IT bottlenecks in accessing data and provide ready access to enterprise data, while also balancing the free flow of data with the safeguards that are necessary to protect sensitive data.  Educate the business units so that they don't have to wait for IT to complete their data projects. 

C-Suite Partnerships: Work as a peer in the C-suite because data impacts everyone. A primary role for CDOs is to be an influential voice across the entire organization.  Data only becomes an enterprise asset when data achievements resonate with the CEO, CFO, CIO, CTO, etc. Hear their needs and be highly responsive. 

Data Literacy is the ability to understand the data that you are working with, preparing data in the right ways for analysis, conducting analysis in ways that give meaningful and informative business information, and presenting the analysis results visually.

Advance Data and Analytics Maturity: The following list represents the steps that an organization makes as it matures its data practices. The table below shows eight levels of data and analytics maturity where each increased level of maturity corresponds with expanded opportunities to get value from data. A CDO needs to be well versed in each area to plan and lead the evolution of data maturity.

8

Drive Innovation
Using data analytics to spark innovations that differentiate the organization in a competitive market.

7

Drive Organizational Learning
Using data science, artificial intelligence, and machine learning to adapt to changing business conditions, recommend and/or automate decisions and actions, and increase efficiencies and competencies.

6

Look into the Future
Using data mining and predictive analytics to understand probable future conditions and events, and to inform and guide the strategies and tactics that shape the organization’s future.

5

Understand Cause & Effect
Using data for causal analysis, to understand why things happen, and to identify leverage points to effect change—knowing how to create more of desired outcomes and to reduce or eliminate the undesirable.

4

Understand Patterns & Trends
Using data for analysis and visualization to understand correlations and connections among business variables, and to see behavior over time of various business metrics.

3

Know What Has Happened
Using data for descriptive and retrospective analysis of business outcomes (know what has happened), to quantify the outcomes (know how much), and to see the outcome historically (know when).

2

Reporting
Using data to produce reports about business entities, events, and results—from internal reference and management reporting to external corporate, compliance, and enterprise reporting.

1

Record Keeping
The most basic level of data management uses data simply as a digital record of business transactions and events.

Protect the Data: Data protection is critical to guard against intrusion, corruption, and loss of data. Protection is important and continues to be a data governance concern, yet data breaches are occurring at an accelerating rate.

Regulatory compliance is a key data protection concern. The continued growth of new data protection regulations, including the European Union's General Data Protection Regulation (GDPR), California’s Consumer Privacy Act (CCPA), and New York's Cybersecurity Requirements for Financial Service Organizations should alarm organizations without strong data governance and data protection practices in place.

Data security is another key concern for data protection. Security deals with authorized access to data. In addition to protecting stored data, security must also protect data in transit across networks, using techniques such as encryption. Well-rounded data protection also attends to sensitive data with appropriate measures for compliance and privacy constraints. It is the CDO's role to drive data security awareness throughout the organization.

Improve Data Quality: In years past, businesses were reluctant to take on responsibility for improving data quality. They considered it to be the role of IT professionals. In fact, the entire data quality process was often offloaded to IT. The days are past when the business can abdicate responsibility for data quality.

Data quality is directly connected to data value and data risk, and the business needs to take full ownership for ensuring that the data meets corporate standards for quality. This goes hand-in-hand with making investments in data management and committing to data governance as a business responsibility.

Promote Data Ethics: Data ethics focuses extensively on the appropriate use of data. Facebook and Cambridge Analytica are but two examples that highlight what unethical people do with data. Even artificial intelligence and machine learning algorithms are being examined for their bias in interpreting data, developing conclusions, and recommending or automating decisions. Data ethics is a complex subject for which there is no easy answer. The first step is to bring it out into the open so that small steps and steady progress can be made. The CDO should start the discussions and become a primary advocate for data ethics.

Eliminate Data Territorialism:  Data is most valuable when it is shared across an organization. Beyond providing data access, metadata is necessary to make it clearly understood. Knowledge sharing helps to ensure appropriate use and avoid misunderstandings and misinterpretation. Shared data, shared metadata, and shared knowledge is essential to avoid turning good data into bad information. The CDO must lead the charge to encourage data sharing and eliminate territorialism.

Summary

When building your CDO career, think about your contributions toward each of the areas I've described. Develop a narrative so that you can confidently discuss how you have addressed each, as well as your ongoing efforts. Be able to answer difficult questions, such as how you identify data-driven value opportunities, how you drive data innovation across the organization, and what metrics you provide for strategic-tactical- and operational alignment.

About the Author

Jennifer Hay ([email protected]) provides career advice and creates resumes and LinkedIn profiles for technology and data professionals. Her credentials include:

  • Academy Certified Resume Writer (ACRW)
  • Resume Writing Specialist in Information Technology (CRS+IT)
  • Certified Professional Resume Writer (CPRW)
  • Certified BI Professional (CBIP) in Business Analytics & Data Analysis and Design
Jennifer Hay

As the nation’s first certified resume writer in information technology (CRS+IT), I am a natural choice for global technology professionals and all-around geeks seeking high-impact career marketing documents. My rare...

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