- Kingland Platform
A couple of weeks ago, I spent a few days with 500 of my fellow data professionals at the FIMA Europe conference in London. I’ve been going to FIMA events for more than 10 years and it’s been exciting to see this industry evolve. As Peter Serenita, Group CDO of HSBC put it, we can honestly say we’re a profession now.
So what did this gathering of data professional have to say? For those that missed it, here are three of my top observations, coming from my data and technology executive point of view.
Not all CDOs are Created the Same
I found it incredible to listen to the general consensus around the differences between a CDO 1.0, 2.0, 3.0 and even 4.0. Not only do most major institutions have at least one CDO (or many in some cases), there’s growing consideration about the level of impact and the type of focus for these data leadership organizations. The summary here is for early stage CDOs (1.0), the focus is really about governance and evangelism to some extent. The more advanced CDOs (2.0 through 4.0) are more aligned to drive the use of data throughout the enterprise and to begin to take advantage of modern technologies like cognitive. Additionally, I noticed that CDO organizations continue to vary in structure and size. I spoke with some leaders who have a team of 5, others with teams of 50, 800, and as large as 1,500 to 2,000. Now 10 years old, it's nice to see the CDO role advancing, but with significant inconsistency across companies.
Artificial Intelligence (AI) is a Hot and Nebulous Topic
Artificial Intelligence (AI) is a top area of interest. At Kingland, we’ve seen the benefits of using AI and other cognitive technologies with data since 2009 and we’ve been optimistic that leaders would start to take notice. That’s clearly happening – AI is getting a lot of “air time” from CDOs and other leaders, which is positive. The caution I have is the depth of concepts here is still fairly shallow. Having spent time with a group of Chief Analytics Officers a few weeks ago, I find a noticeable difference in the creativity of use cases that Analytics leaders are talking about vs. pure Data leaders. I think CDOs will make progress in 2017 and it is encouraging to see the discussion starting to heat up. I strongly believe that if we fast forward five years, AI and machine learning will be a very large topic in the CDO community.
Tools Aren't the Only Answer
When talking about data governance, we've heard CDOs say for many years that tools can help. The resounding message I'm hearing now is that tools can help, but they won’t solve enough of the problem. There was a subtle difference I noticed this past week, that some tools work, but perhaps the tool approaches of the past number of years are outdated. I think many were created reactively to solve data challenges for CDOs that were still figuring out data strategies, or in response to the growing pressures from global regulations. As CDO strategies have hardened and the regulations are seemingly un-ending, I think leaders are looking for more than tools - they want suites, platforms, and easy to use capabilities from the cloud. CDOs of the future are looking for data applications and platforms that can scale across a business, around the world, much more than a tool. As I think about our platform strategy at Kingland, I’m encouraged as this is precisely why we’re investing the way we are in a more modular, yet integrated architecture to help our clients.
If we think about all three of these points, I see a stronger focus on cost and value in 2017 and beyond. How large should a team be? How can AI create cost savings and allow me to do things I couldn’t do three years ago? How can we “future proof” our data technology investment to generate better returns and improve data usage and quality? Cost is where these questions converge. The successful CDOs will be those that are able to deliver not just governance (1.0) but unique value (3.0) creatively with their budgets.