Data is becoming a strategic asset, across all organizations. It is a source of information and insights. It is a way to drive better decisions and resource allocations. And it is enabling new business models and can be a source of competitive advantage. Most of the decision-makers are very aware of this trend and are working hard to actually make it happen, in the organization they lead.
But this is not a “walk in the park” and many companies are lagging behind, in terms of delivery of “Data projects”. In many organizations, data is siloed and poorly governed (definitions, quality, coherence). The infrastructure is also often missing, to start getting value out of the large amount of data available. There may be a problem of culture: many organizations confine their data scientists to “number generation” tasks, which clearly undermines their potential. Finally, if the potential of data is perceived in a high-level manner, the benefit and return of Data projects tend not to be well framed.
Appointing a Chief Data Officer in an organization is often considered as a way to tackle those challenges. By nature, Data is present across all departments of a company (Finance, IT, Marketing, Operations, Customer Support, Sales). Having a dedicated Data leader is a way to champion Data initiatives and rally all the functions around a common vision. And it allows the CEO to have a single person to call, for any Data-related question…
Therefore, the Chief Data Officer primary mission is to embody and drive the Data agenda, within an organization: elaborate the vision of where data will become a competitive advantage, frame the strategy and be at the forefront in the execution of the key initiatives. This role is clearly emerging. According to Forbes, while 12% of US large companies had a CDO in 2012, it is now the case for 63% of them. According to Gartner, by 2021, this role will be considered as a function as critical as HR, Finance or IT in 75% of large companies.
However, when analyzing the positioning of various Chief Data Officers, it appears the role is far from being normalized. And many of them do not have the right positioning and are not in control of the right resources to succeed in their task.
- The span of control of Chief Data Officers differs a lot from one company to another. A lot of them actually focus on coordination and mobilization activities, without having the capacity to drive concrete initiatives.
- Many Chief Data Officers are focusing on one aspects of the Data value chain (e.g. Governance) ; their scope does not encompass the full Data lifecycle, which limits their potential.
- In some companies, there is ambiguity with the other CDO (Chief Digital Office), which can create some confusion.
- Despite their CxO titles, many Chief Data Officers do not belong to the Executive Staff and hold relatively junior positions.
- Many Chief Data Officers do not own specific KPIs, which results in them being perceived as a “cost center”.
As a consequence, those are our five recommendations to help organizations position their Chief Data Officer for success.
- Your Chief Data Officer is not only “connecting the dots”. He should own a team and drive concrete and sizeable Data initiatives. The best Data talents should be part of his group, or he will not be credible.
- You Chief Data Officer should start with the vision. Data is everywhere, but not transformational on all segments. Your Chief Data Officer should well articulate the areas of focus and subsequent investments.
- You should decide, whether you want a specialist or a generalist. A specialist will be suited to inspire a Data Scientist team and to lead highly sophisticated Data initiatives, in case this is the area of focus. A generalist (with strong Data awareness) will be an agent for change and will ensure results matter more than the beauty of the model.
- There is no need to appoint a dedicated Chief Data Officer, if you already have a strong and senior functional leader, who is fully legitimate to own and drive the Data agenda.
- Your Chief Data Officer should own actionable KPIs and targets (e.g. P&L, valuation of Data asset, Data performance) to make it clear that the contribution of his group is significant and properly measured.