Have You Hired A CDO Yet?!


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There is no doubt now.  Chief Data Officers (CDOs) are here to stay.  And their role, combined with that of the CIO, is bound to transform the organizations that know how to use them best.  Have you hired a CDO yet?!

Here are some market statistics to consider:

If you don’t have a CDO yet, the time may have come to begin your search.  What should you look for though?  And what initiatives should you launch them on to so they can succeed?  This post attempts to provide some guidance.

Career Aspirations

The first factor to take into consideration when hiring a CDO is where they want to take their careers to.  

At this point, it is not clear where the CDO role leads.  The function has truly flourished in the last 9 years and most of the CDOs I’ve had the opportunity to observe tend to go from one CDO role to the next.  

When they are successful, their scope grows within the same organization from one department to larger ones.  When they switch jobs, they appear to move laterally from one CDO job to the next, often from smaller companies to larger ones.

The latest survey I’ve published on this topic indicates that a CDO’s next job is likely that of the CIO.  This makes sense.  The role of managing data is technical in nature and as the role of the CIO itself is evolving towards that of a COO,  a good blend of technical, operation and business savvy could benefit companies, even the most traditional ones.

The CDO career 2021 survey I launched is still available online, and has gathered hundreds of votes already and over 11, 000 views.  While the majority leans towards CIOs, many in comments explain their preference for CEO and COO jobs.  Be sure to vote here and engage with the community in the comment section.  



What Should Your CDO focus on?!

When they are first brought in, CDOs are inevitably faced with an impossible choice: freely enable all people with more data or focus first on centrally governing access to information.  Randy Bean, Founder at NewVantage Partners, a firm whose annual survey provides great insights on the role of the CDOs, posed this question to his CDO community a few years ago: “are you a ‘business strategist’ or are you a ‘marshal or Stewart’ of data?”  

So far, few organizations have been able to leverage their CDO to execute on their data-driven transformation: according to Accenture, only 32% of organizations reported being able to realize tangible and measurable value from data.

CDOs are challenged to put in place the right framework to govern data, secure access AND make sure the “right” data doesn’t end up in the “wrong” hands.   Another equally undesirable outcome is to rely on poorly designed systems that let the “wrong” data get to the “right” hands.  There is indeed little value in enabling people to make the wrong decisions quickly… 

The reality though is that seeing the difference between either alternative has been a challenge: 42% of leaders do NOT assess, measure or monitor their Data Analytics Governance, according to Gartner. 

The answer to this dilemma might be found in some of McKinsey & Company’s most recent work on modern data architecture.  Their guidance can act as a modernization blueprint for many of the CDOs and CIOs looking to up-level their data game in a world that’s increasingly set to compete on data.  

The research quotes key trends such as the move from “on-premise to cloud based data platforms” or the transition from “pre-integrated commercial solutions to modular, best-of-breed platforms”.  The firm explains that, when “done right”, modernization projects can return significant return on investment:  it quotes “more than $500 million annually in the case of one US bank”, and “12 to 15 percent profit-margin growth in the case of one oil and gas company”.

The architecture blueprint diagram provided by the consultancy calls out a few key terms that your team can use to rationalize with your internal beliefs and context.  The paper breaks down the important components of a modern data architecture into 3 key layers. The below is my interpretation of the diagram as it relates to what I’ve observed with some of the most successful data-driven organizations I’ve had the opportunity to work with. 

  • Systems of records: this refers to the many sources of information your organization relies on: the databases, the applications which contain the data you need to build a foundation of truth.  According to McKinsey, 70% of financial institutions surveyed have had a modern data-architecture road map for up to 24 months but the majority have integrated less than 25% of their critical data in the target architecture. Rationalizing your approach to data seems to be a good first step on your journey to becoming a data-driven organization.
  • Unified Data, Analytics core: as data flows into your organization, either in real-time or in batch mode, your team will need to curate, analyze and serve information and insights to employees.  A unified data and analytics core is an environment that can enable data engineers, scientists and analysts to discover data, work with it at scale, and prepare and curate it for engagement.  Many technologies can be involved in making this part of your stack a reality.  A good place to start is to research the “Data Fabric”, a technology Gartner expects could reduce time for integration design by 30%, deployment by 30% and maintenance by 70%.

Listen to last week’s Gartner ThinkCast below as Rita Sallam, Distinguished VP, puts into context this trend. 

  • Systems of engagement: in this third and final layer of the modern data stack, McKinsey refers to the interfaces your people use to consume data.  The number of ways people turn to in order to interact with data has grown tremendously. Dashboards are no longer the only place employees go to find insights.  Reports are now embedded in most applications.  Artificial intelligence (AI) now powers many of the industry’s most modern applications which use business-specific models to output insights as part of a business workflow or automate tasks that previously required data extraction and manipulation outside of these applications.  Examples include modern Customer Relationship Management (CRM) systems, many of which benefit from embedded AI for lead scoring, information completion, correction and protection.

If you listened to the above podcast, you’ll note that teams building modern systems of engagement leverage reusable and intelligent components so they can assemble applications with great agility.  They rely heavily on the Data Fabric as a foundation to observe, discover and connect the components they require to rapidly assemble them into intelligent applications. 

I covered “composable and intelligent applications” earlier in this column and I believe this is a transformative trend.  

It will require CDOs to hire and train up their teams appropriately and quickly: most have 18 to 24 months to figure this out, if you believe Gartner’s prediction: by 2023, 60% of organizations will compose components from three or more analytics solutions to build business applications infused with analytics that connect insights to actions.  

Have you hired a CDO yet?  If you’re still looking, there are at least three steps you can take:

  1. Register for the upcoming MIT CDO Symposium here.  It’s 15th edition runs on July 20-22.
  2. Register for Gartner’s upcoming Data Analytics Summit here.  This year’s edition is virtual but still a great way to learn from industry experts and practitioners.
  3. Read Scott Taylor’s “Telling Your Data Story” book to learn about “the 4Cs of Data Structure”, the “3 Phases of Digital Transformation” and the “8 ‘ate of Data Value”

Good luck on your hiring, and, if along the way, you gather some learnings, don’t hesitate to ping me, Rita Sallam or any of the authors of the McKinsey report referenced here.  We’re also curious to hear more from the community!

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