Tag Archives: cdo
A month ago, I shared that Frank Friedman believes CFOs are “the logical choice to own analytics and put them to work to serve the organization’s needs”. Even though many CFOs are increasingly taking on what could be considered an internal CEO or COO role, many readers protested my post which focused on reviewing Frank Friedman’s argument. At the same time, CIOs have been very clear with me that they do not want to personally become their company’s data steward. So the question becomes should companies be creating a CDO or CAO role to lead this important function? And if yes, how common are these two roles anyway?
Regardless of eventual ownership, extracting value out of data is becoming a critical business capability. It is clear that data scientists should not be shoe horned into the traditional business analyst role. Data Scientists have the unique ability to derive mathematical models “for the extraction of knowledge from data “(Data Science for Business, Foster Provost, 2013, pg 2). For this reason, Thomas Davenport claims that data scientists need to be able to network across an entire business and be able to work at the intersection of business goals, constraints, processes, available data and analytical possibilities. Given this, many organizations today are starting to experiment with the notion of having either a chief data officers (CDOs) or chief analytics officers (CAOs). The open questions is should an enterprise have a CDO or a CAO or both? And as important in the end, it is important to determine where should each of these roles report in the organization?
Data policy versus business questions
In my opinion, it is the critical to first look into the substance of each role before making a decision with regards to the above question. The CDO should be about ensuring that information is properly secured, stored, transmitted or destroyed. This includes, according to COBIT 5, that there are effective security and controls over information systems. To do this, procedures need to be defined and implemented to ensure the integrity and consistency of information stored in databases, data warehouses, and data archives. According to COBIT 5, data governance requires the following four elements:
- Clear information ownership
- Timely, correct information
- Clear enterprise architecture and efficiency
- Compliance and security
To me, these four elements should be the essence of the CDO role. Having said this, the CAO is related but very different in terms of the nature of the role and the business skills require. The CRISP model points out just how different the two roles are. According to CRISP, the CAO role should be focused upon business understanding, data understanding, data preparation, data modeling, and data evaluation. As such the CAO is focused upon using data to solve business problems while the CDO is about protecting data as a business critical asset. I was living in in Silicon Valley during the “Internet Bust”. I remember seeing very few job descriptions and few job descriptions that existed said that they wanted a developer who could also act as a product manager and do some marketing as a part time activity. This of course made no sense. I feel the same way about the idea of combining the CDO and CAO. One is about compliance and protecting data and the other is about solving business problems with data. Peanut butter and chocolate may work in a Reese’s cup but it will not work here—the orientations are too different.
So which business leader should own the CDO and CAO?
Clearly, having two more C’s in the C-Suite creates a more crowded list of corporate officers. Some have even said that this will extended what is called senior executive bloat. And what of course how do these new roles work with and impact the CIO? The answer depends on organization’s culture, of course. However, where there isn’t an executive staff office, I suggest that these roles go to different places. Clearly, many companies already have their CIO function already reporting to finance. Where this is the case, it is important determine whether a COO function is in place. The COO clearly could own the CDO and CAO functions because they have a significant role in improving process processes and capabilities. Where there isn’t a COO function and the CIO reports to the CEO, I think you could have the CDO report to the CIO even though CIOs say they do not want to be a data steward. This could be a third function in parallel the VP of Ops and VP of Apps. And in this case, I would put the CAO report to one of the following: the CFO, Strategy, or IT. Again this all depends on current organizational structure and corporate culture. Regardless of where it reports, the important thing is to focus the CAO on an enterprise analytics capability.
Author Twitter: @MylesSuer
Forget degrees from Harvard or MIT, forget NoSQL, Hadoop or OBIEE. These are all powerful tools but they will not win you the face-off. It starts with who you are (or are not), who or what you are going up against and what has happened in the past. Why should martial arts be a job requirement for Chief Data Officers? I boiled it down to three simple reasons to help you understand.
I started practicing Kendo three years ago and it surprises me every single practice how inadequate I still am, how much I can glean from my opponent to determine future behavior and how unimportant “background noise” really is. Even if I have a good day, some strike from a teenager or a retiree, who has been practicing for a decade or more, will remind me that I got only 1% better compared to last month and I have a long way to go. At our last practice, one of my Senseis told me that the higher ranks get their Ki-Ken-Tai-Ichi (alignment of spirit, sword, body) right maybe half the time. It’s a life lesson every time.
These three facts are probably also true for many one-on-one sports where adversaries study each other for more than just a couple of seconds before their next swing or shot. If you ask me, most western sports are about endurance, strength, mindset and strategy with a heavy focus on the physical aspects. Kendo is 90% strategy and mindset. That is why six and sixty-year olds alike can excel in it. It is more akin to chess with baseball bats.
You study your opponent from the second he walks up to the chair in the middle of the podium for a gentleman-like exchange of cerebral willpower but in the end you will smack him relentlessly with a bat. Everything you do is directly driven from how you feel, what you think, how your opponent moves, what your opponent feels and thinks. The goal is not to react to a hand being raised but to anticipate your opponent’s next move based on their most recent actions. By the time your eyes (and, a tenth of a second later, your brain) capture the right hand going up to strike towards you – you’ve already lost, as it is too late to react.
You are effectively analyzing core data domains and key attributes, like posture. Business data requires the same rigor and focus on the essential. There is also a tremendous amount of process (formalities like repeated bowing) and deeper meaning in everything you do; call it “Governance”.
A Chief Data Officer (CDO) needs to mind the same aspects in his or her existence.
- You are not the professional you think you are (humility)
- Someone else always knows something you don’t, so every additional bit helps to predict future actions (willingness to learn)
- How to eliminate all the noise detracting from the ultimate goal (focus)
In reality, the data problem has not been solved long ago. Something new can be learned to combat this age-old problem. The learning piece comes into play when we are willing to listen to people who have done or seen similar problems being fixed in another environment, not necessarily the same industry or department. The third is that political and technical detractors like procurement processes, M&A, new leadership or transactional volume spikes from more applications will continue to pop up. However, it is on you, the CDO, to uncover, isolate and preach that fixing a process may not always be the root cause of a business issue and as such needs to be put in perspective. As I always say “throwing bad data at a better process” just saved you a step but still renders errors, rework and bad decisions.
So what does this mean in “real” terms:
- Seek and accept opinions frequently, even if they don’t match your issue perfectly. Often a customer is a customer is a customer….admit it. Your business model may not be that special after all.
- Watch what the others do on a fundamental level, i.e. becoming data-driven organizations. These could be competitors, partners, organizations you (should) admire.
- Internalize and socialize what the core asset, goal of the organization is, which will move the needle the most. Often it will be your intelligence (speak for information or data).
I will leave you with these thoughts and invite you to sit down, cross your legs, close your eyes and get all esoteric on me, young grasshopper, but please envision what you organization should look like and how it should make its money in five years from now. Throwing more resources at new problems, ignoring core data issues and reacting when things bubble up at greater numbers will likely not cut it.
And here is where I will bow out. Take a moment and think about it; how does your take on life influence your assessment of what you encounter in your workplace?