The ‘data-driven’ chief data officer: 7 steps to success
Businesses understand that their data capabilities — the data they possess and the way they utilize it — can provide a competitive edge and help them in expanding market share and displacing competitors in their sector. Thus, data capabilities are no longer necessary just for their success. In fact, they’re crucial for their existence. Moreover, leveraging data the right way provides firepower for growth. The thing is, for a business to ensure that all kinds of data deliver value requires enterprise-wide governance and organization. And, that is the job of a chief data officer.
This is a relatively new profile, originally meant to oversee data quality, governance, and regulatory issues, but now expanding to the frontlines of the analytics revolution. A chief data officer can show data-driven organizations how to boost growth and revenue in the following ways:
A chief data officer must first devise a comprehensive charter, showcasing a simple vision of what a data-driven company looks like in reality, along with a mission statement of what the business does as well as a narrative that makes analytics and data real for people without a quantitative or data management background.
Usually a part of analytics and data business case, the charter must highlight practical business outcomes to provide a better understanding of the scope, focus, and intent. The trick is to lead by example and then with examples.
To fulfill this balancing act, a bimodal approach is needed. And, a bimodal approach involves managing two distinct modes of IT delivery, one of which is focused on agility while the other is on stability. Careful resource management, as well as the ability to serve new and classic requirements, are important for maintaining balance within the bimodal environment. It is necessary for the chief data officer to regularly revisit the team structure for supporting growth and maintaining agendas.
It is never easy when an organization decides to make the switch from business intelligence to analytics. However, this shift in focus can be made smoother by modernizing the existing business intelligence roadmap and strategy as well as supporting the progress of data science and analytics capabilities.
It is also vital for the business to align with the information management roadmap and strategy so that an integrated plan might be formed — one that carefully monitors signs of interdependence across major infrastructure efforts, especially while the architecture (this is not the same as the architect in the amazing movie “Inception”) changes from the traditional data warehousing to a more logical virtualized environment.
Make it a point to review the critical path, strategy, and roadmap with major stakeholders and shareholders each quarter.
