The opportunities are enormous; we all know it. Harnessing data can help us grow revenue, reduce costs and mitigate risks. And the challenges are complex: big data, multi-cloud, data quality, advanced analytics, data literacy and data governance are just a few big pieces that come to mind. So appointing a Chief Data Officer (CDO) seems like a great idea. But organizations realize that they are not cheap, not easy to hire, nor vet.

The CDO is first meant to be an executive. The role should be a transformative one. It is usually borne out of the realization, or rather the decision, that data will take a central, strategic part in crafting the future of the organization. But depending on whom she reports to, and how organizations define the actual position, will make a world of difference and can make it a pétard mouillé (French for wet gun powder). Expectations are too typically in another galaxy, so it is no surprise that a CDO's tenure is generally short around two years.

We are still learning the lessons, but some good practices are emerging. Putting in place a CDO is not a simple endeavour, but we are now better equipped to know about what can be achieved without one. We also know when we will have to bite the bullet and have no choice but to appoint one.

Before we dive into it, let me say that everything worth doing is essential. Examples I will give may need to be done, perhaps even urgently, but the question is, "do we need C-level oversight to get it done?"

We don't need a Chief Data Officer to put in place the basic data management capabilities. Many organizations are still way behind the "data-driven" adoption curve, and there is only so much transformation their teams can absorb. Examples are: adopting cloud capabilities (for speed), improve regulatory reporting or getting systems to exchange data. Even data quality and data governance may not require a C-level executive.

Where a C-level executive becomes required is when we need to start focusing on the data integration and quality aspects AT THE ORGANIZATION level, when we need to agree and collaborate across major LOB's or functional areas. Gartner has a helpful matrix (below) that highlights how to address Data and Analytics based on (1) your core business strategy and (2) a combination of what you wish to achieve and where your organization is on the maturity scale.

Gartner: Approaches to D&A Strategy

Click here for an excerpt of Gartner's reference document in PDF

Each box in this table gets exploded into a full Data & Analytics Strategy carefully adapted to the organization. Whichever framework is used to define, it doesn't matter, but you probably are guessing, correctly, that it is a balanced mix of people, process, technology and data (architecture). Wrap this up with a delivery roadmap that takes into account appetite and urgency to act at the corporate level. These are typical deliverables headed by the Office of the CDO.

If what you require and are working towards is the Utility level, you don't need a CDO. That is because you are merely trying to put in place the tools and platforms, modernize and educate. Gartner defines it as "A generic capability. It should be available to everybody for myriad requirements and all kinds of intended business value." It is centrally managed and made available for any LOB or function to use as they see fit. The capability can even cover specific data sets, like customer or product data curated and made available for all to use.

So when does the CDO become a must?

A company needs a Chief Data Officer when it is ready to fully consider how it wishes to compete with data over the long term and start to build the organizational capabilities it will need to do so in a more concerted way. D&A as an Enabler means tying it to one or more specific business goals. Additionally, you wish to start reusing the data for other business purposes.

D&A as a Driver (or data-driven organization), further requires that D&A become a "means to achieve new business goals. New tools can uncover new insights, and new data types can lead to new business questions; both drive new business ideas and revenue sources. " Here, we might see the need for a Chief Data and Analytics Officer to gain some real end-to-end experience — perhaps making a concerted effort to try out advanced analytics to contribute to one of the strategic three or five-year business objectives.

As I mentioned earlier, selecting a CDO is one thing, but where she fits in the organization and the power to act given should be carefully considered. Data is a lot about leadership, some soft but some more forceful at times. The end-to-end nature of taking raw data to business operations or on the front lines crosses many otherwise traditional organizational boundaries with their own "firewalls."

Another aspect that justifies C-level oversight is time-to-value. Politics, negotiations, standard processes and budgets all take a life of their own when mapped to organizations. By having a C-level executive given oversight and power to act over the means of end-to-end delivery of value, you have a fighting chance of achieving it in a much shorter timeframe.

With C-level functions come new organizations. Think of an Office of the CDO. New data scientists and data engineers, new managers or directors, to set up both a data lab and a data factory, for example. And becoming data-driven entails a profound cultural change that takes major investments in communication and training, not to mention support and leadership from all executives, not just the CDO. Silos in this context will be mortal inhibitors.


An organization is only ready for a Chief Data Officer when it dares to act, with all the implications, cultural changes and investments that will come with it. Seeing the opportunity that this offers and seizing it are very different things.

Still, the data revolution is here and will disrupt every industry. Whether organizations deem it urgent now or not, at some point, it will become urgent, and the decision will be made for you.


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