Tackling workforce structure is integral to an organization’s digital business transformation success. Data and analytics leaders cannot master today’s opportunities and challenges of digital business using yesterday’s roles and organization design.
Real-time analytics on constantly changing data requires different skills and a different mindset. The need for data and analytics governance policy is leading to smarter, more adaptive governance, resulting in necessary changes in organizations and roles related to data and analytics.”
Jorgen Heizenberg, Senior Director Analyst, Gartner
Chief data officers (CDOs) consistently mention lack of relevant skills or staff as one of the top internal roadblocks to success. The Gartner 2018 CEO Survey highlighted a similar pattern, with respondents listing a “lack of appropriate talent and capability in the workforce” as the biggest inhibitor to digital business progress. Data and analytics ranked first among tech-related skills that CEOs will need most.
Algorithmic business is creating new responsibilities and roles for those managing data and analytics. The growing importance of data and analytics creates new strategic challenges for organizations and data and analytics leaders. Now is the time to create an organization with new data and analytics roles fit for the future.
There are a few things that data and analytics leaders must focus on as they begin their journey to support the transformation required for digital business.
Rethink existing roles
The workforce landscape is changing. Some traditional IT roles are being disrupted by “citizen” roles performed by line-function business users. Other new hybrid roles that span functions and departments and blend IT and business roles are also emerging.
Algorithmic business is creating new responsibilities and roles for those managing data and analytics and requires different, complex skills in areas such as artificial intelligence (AI). Real-time analytics on constantly changing data requires different skills and a different mindset. Furthermore, the need for data and analytics governance policy is leading to smarter, more adaptive governance, resulting in necessary changes in organizations and roles related to data and analytics.
Managing a hybrid and distributed organizational model
Data and analytics use now impacts the entire organization. This means it doesn’t make sense for multiple, disparate teams or even a single centralized team to oversee the assets. The recommendation is to establish a hybrid and distributed organizational model spanning all data and analytics use cases in the organization.
The CDO is the senior executive who bears organizational responsibility for fostering value creation from its data assets and with the external data ecosystem. The CDO should work with the analytics center of excellence as well as the decentralized teams. As transformation toward digital and algorithmic business continues new roles blending IT and business functions will emerge. For example, when business and information leaders agree on monetizing data by generating revenue or other financial benefits from exchanging it, hiring an information product manager is vital.
The office of the CDO will gradually begin to lead more data and analytics strategy, and initiate focused, strategic use cases for experimenting, which will broaden across the company over time. Data and analytics leaders should plan to establish or build out the office of the CDO to manage information assets, deliver insights to the business to improve decision making and generate incremental value.
Key roles to focus on for data and analytics
Presently, a number of roles are important for data and analytics leaders to consider fulfilling, with the CDO at the forefront. Additional positions include data-driven facilitator, analyst(s), data engineer, data ethicist, information architect and master data management program manager.
The emergence of new roles and their importance in the future
Other positions that could add value are data sourcing managers, continuous intelligence roles, algorithmic business domain experts and algorithmic business trailblazers. A data ethicist can also play an important role in what the organization should do with data.
