The role of Chief Data Officer (CDO) is still relatively new in many boardrooms.
A necessity to have a CDO today comes from having a relatively mature data programme, simply because these tend to be the companies who can justify having one person in charge of a data team, rather than having a data team of one person. As more companies have seen the necessity for this kind of position, the number of organizations who have employed one has significantly increased.
Randy Bean published an executive report earlier this year which found that 43% of executives reported that their firm had appointed a chief data officer, up from only 19% two years earlier. It shows that it is a role being well appreciated by companies as their data maturity is increasing and they see that there are challenges that can only be solved through having a dedicated Chief Data Officer.
However, this does not tell the story of where the CDO started, which was in response to the financial crisis in 2008. At the time many companies, especially financial institutions, had lost significant amounts of money after their data had been shown to be completely wrong. It meant that none of their analysis was accurate and therefore financial results, predictions and even debt repayments were wide of the mark.
Therefore, these companies created the role in order to have somebody responsible for the validity of their data, both to protect their business against this kind of loss in the future and also to help appease law makers who were going to require change within reporting and storage of data. This broadly represented a consolidation and cleaning process rather than anything that was necessarily growth orientated.
As we have moved away from the mess created by the bad data at this time the role has become less about maintaining data integrity and more about leading a data science team. Although still an important part of it, the importance is now on the leadership of the team in order to find actionable insights, as opposed to making sure the data that is being used is clean. Clean data is now seen as the most basic of needs, something that a data science team does in the same way that a sales team sends emails and makes calls.
The role is likely to become far more strategic, giving support the other board members to make key decisions and helping to grow the company rather than just consolidating what they already have.
Whether it is a role that stands the test of time is yet to be seen, but one thing that we can be sure about is that the next few years is going to see it evolve significantly.