Every year, technical roles in organizations must adapt to the changing face of the business technology landscape. This year, the CDO is facing a major task, the transition from technical lead to change manager. Read on to learn how you can focus on three core priorities to maximize your effectiveness as a CDO and ultimately extend your tenure.
While the Chief Data Officer, or CDO role, is relatively new—going back just over a decade, the job was almost unheard of—it is already undergoing a radical transformation. Today, many CDO roles are categorized by short tenures, with two years being the average time to hold the position.
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The problem is that many CDOs are drafted to solve data issues and set up organizational systems. The role has been characterized as a technical one, and although sitting alongside other executives in the C-Suite, the job of CDO was understood to be far removed from the business of implementing strategic business decisions.
Many executives needed help to see the ongoing business benefit of having a CDO in a long-term position. It was widely believed that once the technical elements of a data strategy are in place, the CTO could take over. Well, in 2024, with the juggernaut of AI in a full stampede and data infiltrating every aspect of decision-making, the role of the CDO is more important than ever before. However, for CDOs to ensure longer tenures, priorities must shift from technical lead to change manager.
In this blog, we'll explain how the role of the CDO must center on the ongoing business benefits they bring to a company rather than the one-shot technical expertise they provide at the foundational level. We'll explain how CDOs can oscillate their priorities to ensure they deliver innovative data solutions and drive consistent value.
CDOs can position themselves as leaders in business-critical change management processes by focusing on the following three priorities.
As we have mentioned, the most urgent shift for CDOs is to move away from focusing on technology and into a change management role. Ultimately, it can be challenging for executives to accept the value of a CDO's position because it is hard to visualize results.
When it comes down to it, business leaders find hiring a new CDO far easier than changing a business process to achieve better outcomes. The shift away from the technological focus to one that centers on the ongoing management of the solutions implemented is critical. In a recent AWS survey, 41% of CDOs defined success as achieving business objectives, while only 5% measured it in technical accomplishments.
Change management should focus on the changes technologies deliver, not simply their implementation. The success of a CDO should be measured against how effectively they align data-driven initiatives with business objectives. Ultimately, to ensure a longer tenure, CDOs must take ownership of the capabilities of a data strategy to predict customer behaviors and the performance of the organization, and by doing so, achieve solid, tangible business objectives.
Of course, data is fluid, and many business executives will undoubtedly become frustrated when objectives are met slowly. For that reason, it's essential to build strong relationships with business leaders who understand the nature of data-driven technologies and can appreciate the value that the successful management of these technologies will bring.
The most significant technology innovation in 2023 was the widespread development and launch of generative and other AI solutions. Generative AI, in particular, is promising to revolutionize how companies operate, and at the heart of this transformation is data, the fuel that informs and powers AI engines.
Companies in every sector are racing to implement AI-driven initiatives that will not only change the nature of collaboration and productivity but hugely boost the range and effectiveness of analytics. CDOs are perfectly poised to take control of AI and AI-driven analytics in their organizations, possessing the technological know-how and business acumen to deliver the most radical improvements.
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AI isn't a fleeting trend, and establishing yourself as a leader in AI and, consequently, the advanced analytics these technologies provide is an incredibly effective way of demonstrating ongoing value. AI doesn't stop at the implementation phase.
These transformational technologies not only require ongoing management, but new additions to the technology stack are appearing all the time, and it will take an experienced executive who understands how best to utilize data to run and benefit from these technologies to keep their company ahead of the curve.
With so many data platforms, analytics solutions, and applications available, the focus on data-driven initiatives has honed in on specificity. To that end, CDOs should drive the introduction of data products that enable companies and individual user groups to turn particular business ideas into working applications.
Data products succeed in addressing specific outcomes by combining data, AI, and analytics processes with a particular goal. This enables data teams and business users to collaborate on achieving business objectives incrementally instead of taking a Big Bang approach to company-wide analytics, which can be far less tangible for business executives. Working collaboratively, multiple stakeholders are invested in data product ideation, launch, and ongoing success measurements, with the CDO sitting at the top of the management pyramid.
Measuring and documenting the lifecycle of data products and continuing to monitor them is essential. Still, it's important to note that companies with low data maturity will struggle to implement lots of data products in unison. If this is the case, focus on a handful of critical projects that bring the most value to stakeholders.
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Underpinning all the priorities of a CDO must be a focus on governance. Data governance is critical in ensuring that all data products, AI, and analytics processes work compliantly and effectively.
However, as with the approach taken to introduce data products, you must first judge the level of maturity of your organization and proceed by incrementing data governance strategy program by program.
Book a call with us to find out:1. How OvalEdge can help you to ensure the data used to fuel the success of your organization is suitably governed. 2. Why only a comprehensive, end-to-end data governance solution can ensure your data is secure, available, and actionable. 3. How automated tools foster a collaborative data ecosystem that drives innovation in every department, enabling you to demonstrate the ongoing success of your data strategy. |