The 'Chief Data Officer (CDO)' is a company's overall data champion, data visionary, and data thought leader, expected to provide guidance to organizations on how to manage corporate data assets. It is a fast-growing role and also fast 'revolving' role in the industry, but why? What makes a successful Chief Data Officer? The other 'C' roles are well understood, are aligned with executive reporting structure, are fully recognized and are stable enough unless there are significant performance or political storms. Does that mean organizations are still learning about the role of the CDO? Could the perception of the CDO be a lot of talk without much action?
The first step for organizations is to make functional alignments for their CDOs to be successful, then I believe that the critical path to success for CDOs is to be part of the executive team with power similar to the other 'C' roles. Given their challenges, I have some thoughts on the CDO's basic steps once they become well-positioned within the executive structure, with a secured budget, ready to perform.
1. Learn and Listen
The well known first step is to develop knowledge of the organization including its lines of business, services, products, business/corporate functions, and corporate structures. Meet with business stakeholders to understand what they trying to do, and their challenges. Gather business vision, future strategy, roadmap and current state, then put in place data lenses to see how you can help.
2. Culture and Connect
Figure out the culture, and see how you need to adopt that culture. The role must be connected to the culture, business challenges, relate well to the business stakeholders, and develop effective collaboration. It is not different from traditional senior leadership engagement principles but, given the role's challenges, it is key to communicate and educate through lunch & learns, town halls, or conducting internal data symposiums or other channels to build 'citizens of corporate culture.'
3. Assessment and Approach
Before starting to craft your action plan, assess the key business problems that require core data, identify the data required to answer these key problems and identify the data sources that will answer the key business questions. Then categorize and narrow down challenges to map with data management capabilities such as data governance or managed data solutions - including master data management (MDM), reference data management (RDM), big data and analytics or data architecture, and data innovation. Define the overall consolidated strategy and create a delivery roadmap, but focus on a specific problem to address where you can build a foundation of data management eco system before undertaking multiple challenges.
For instance, if you choose to operationalize data governance as a priority, select one data domain and build the required framework to show who should govern the data domain and the data domain should reside. How should the data domain to be governed? How should the accountability framework work for that domain?
4. Team and Talent
Team building is a very important phase of the CDO’s journey. The role requires a team of seasoned data professionals with deep expertise to support implementations and communicate with/train other team members across the organization at each level. Given the complexity of the transformation, it requires collaboration and support from every corner of a company to deliver a successful data program.