By Thornton May
Futurist, Senior Advisor with GP, Executive Director & Dean - IT Leadership Academy

In the Victorian England of romance novels, every year a new set of hopefuls [both men and women] would be “introduced to society” at a series of balls and cotillions. While the dancers changed every year, the dance steps, the dance floors and the dance halls didn’t. [See: Sheila Adina, Lady of Devices, A Steampunk Adventure Novel]. Historically, the same kind of dynamic has held sway regarding new comers to the executive suite. Every ten years or so, a new C-level executive would fill the seat of a departing predecessor. In the modern economy, the stately pace of executive change has given way to a frenzy of enterprise musical chairs going on. At this very moment, sixty percent of the global 2000 are on-boarding new C-Suiters [3-6 times the normal executive life cycle]. What is most interesting is the observation that twenty percent of the Global 2000 are creating new C’s. It is not uncommon to bump into Chief Analytic Officers, Chief Digital Officers and Chief Data Officers walking the halls of Mahogany Row. Those who would understand the contemporary corporation now need to stay current not just with new faces in old chairs. We need to understand why these new positions are being created. I undertook a study of who these new C’s were, how they relate to one another and the rest of the executive team.

At the top of the new “C” mystery hit list is the Chief Data Officer. I asked a group of C-level executives what jobs they thought were similar to what Chief Data Officers did. They compiled the following list:

Data Body Guard [as in protecting the data]
Data Champion/Cheerleader [as in always trying to keep data top-of-mind]
Data Cowboy [as in wrangling the resources necessary to herd data]
Data Farmer
Data Janitor [cleaning up the data quality]
Data Miner
Data Vintner [who told the data farmer how to till his fields]
Diplomat [as in getting all the parties in the data supply chain to play nicely with one another]
Orchestra conductor [as in coordinating the many musicians in the data supply chain]
Track coach [ensuring every runner on the data relay team understands their role and has trained for
the critical hand off point]
Sheriff [ensuring data use and data tool selection guidelines are adhered to]
Translator [as in making sure the various tribes of the enterprise understand one another]

Interesting but not terribly helpful. The lack of specificity here indicates that moving forward Chief Data Officers [CDOs] need to spend more time effectively communicating what they do [i.e., the value they bring to the table].

At the CIO Solutions Gallery hosted by the Ohio State University the Chief Data Officer at Raymond James Financial Inc., Jennifer Ippoliti asked attending executives three questions:

How many of you already have a chief data officer in your company?  <5%
How many of you think or know that your company is considering hiring a chief data officer? ~10%
How many of you wish you had a chief data officer?   ~70%

What this troika of responses tells me is that we are very early on in the evolution of the Chief Data Officer. It also reveals that just about everyone realizes that data is an asset that has to be managed. One also catches the wiff of future hard-to-meet/potentially irrational expectations as well [i.e., “We don’t have a Chief Data Officer. If we had a Chief Data Officer things would be better.”]

I welcome your thoughts about how things would be better if more organizations had a Chief Data Officer.

On 19th September 2014 French Secretary of State Thierry Mandon announced that Henri Verdier will be the first French Chief Data Officer. The announcement was symbolic on two fronts – one it signals that the French government views data as an asset that requires specialized and sophisticated attention with every effort being made to make the data available to as broad a community as possible.

More subtly the way the announcement was made sends a signal as well. Rather than a manufactured photo op on the steps of the central government, the Secretary of State traveled to where the data lived, traveled to where the analysts scrubbing, classifying and distributing the data worked to make the announcement. The structure of the announcement highlights the question of do executives [sometimes less sympathetically referred to as “Suits” by the analytic community] have the data delivered to them in final pristine form or do they meet the data half way? Do they engage with the data? Do they get their hands dirty with the data?

I welcome your thoughts regarding the readiness of modern executives to work with raw data.