How CIOs Can Collaborate with CDOs to Improve Data Science Success

cdo
Dell Technologies

Whether your organization is taking small, calculated steps toward data-driven insights or you’re adopting data science wholeheartedly, chief information officers (CIOs) are likely to be impacted by the trends that chief data officers (CDOs) say are the future of intelligent data management and data science.  Our research identifies four major trends for succeeding in these areas: organizational trust, data management fit for purpose, data interpretation at scale, and prioritization and measurement. CIOs can partner with CDOs to move their organizations forward on some or all of these to further the organization along the maturity curve.

Trend #1: Organizational Trust

CDOs indicate that successfully implementing decision-making and data management as an organizational discipline requires building trust. CDOs state that when there is trust in the CDO office, the business invests in data-centric value generation. Building this trust requires that the CDO clearly understand and articulate the business objectives, organizational challenges and customer needs, as well as the IT requirements for data management and data science. CIOs can partner with CDOs to help them understand the state of IT in the organization and the investments needed to meet business challenges and customer needs using a data science approach.

Trend #2: Data Management Fit for Purpose

Data management and tools to support data management have been around for decades. These tools include data discovery, security, governance, and orchestration, to name a few out of the dozens of tooling categories.  CDOs indicate that mature data management requires understanding and managing data in a way that is meaningful for both how data is being used now and may be used in the future.  CIOs can partner with CDOs to make way for the adoption of advanced tools that include lineage, the ability for people in their organization to find and access data they need, data context and data trust.

Trend #3: Data Interpretation at Scale

CDOs indicate that data science may become a commodity as a result of AutoML (automation of the process of applying machine learning to enterprise problems) and other technologies. While these tools could enable many more team members to perform the analytical activities of data scientists, access to tooling does not translate to useful insights that yield bottom-line results. CDOs are clear that deriving value from data requires that teams understand the business and the challenges to be solved.  Some methods used to achieve these goals include:

  • Having cross-functional “scrum” (agile) teams that pair engineers with “business interpreters,” such as data analysts, data scientists or quantitative analysts.
  • Hiring data scientists who understand the business (or putting them to work on areas with which they are familiar)
  • Helping people help themselves by supporting business users with data engineers or data scientists through interactive projects. Examples are creating dashboards or enabling simple access to data models.

CIOs can work with CDOs to create organizational transparency and cooperation to understand the business problems to be solved and how IT capabilities, skills and processes can help.

Trend #4: Improved Prioritization and Measurement

Working on the ‘right’ projects is an indisputable way to increase success. However, prioritization and measurement of projects is a challenge for many CDOs. Those who view their organizations as “Mature” in prioritization and measurement have built the ability to understand the ROI of their projects across the business and measure areas such as:

  • Mitigated risk level – Preventing downtime, asset exposure, or other loss event
  • Operational savings – Reducing full-time equivalent (FTE) effort
  • Improved business results – Increasing sales, profitability, customer loyalty, and so on.

CIOs and CDOs can partner to ensure alignment on long-term company goals and what IT needs to do to support those goals. They also can discover and expand projects that can be leveraged multiple times across customers and teams. And, CIOs can be invaluable in helping to capture project revenue and operational savings.

Learn More

The trends above illustrate how CIOs can partner with CDOs to get higher quality and quantity of value from their data. By focusing on forward-looking priorities and collaborating transparently across the business, these leaders can deliver significant value to their organizations. For a quick overview of the findings from our conversations with CDOs, see the infographic

To learn more about the categories of CDOs and four attributes they use to gauge data management and data science maturity, read the paper:  “Chief Data Officers’ Perspectives on How to Achieve Data Management Maturity.”

For more information on how Intel enables innovation in enterprise data management, click here.

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