US Department of Defense CBAO: Enterprise Leadership, Growth and Change in the Midst of Disruptive Technology

Michael Conlin was interviewed by Robert Lutton, VP Sales and Marketing at Sandhill Consultants

Q: How did you get started in Data Management / Data Analytics?

A: For over a decade I had been in Chief Technology Officer (CTO) roles. The essence of the CTO role is technical leadership. In order to provide technical leadership one must make two commitments. First, commit to continually scanning the environment for ‘weak signals’ of emerging techniques and technologies. This requires you to get past ‘the innovator’s dilemma’. Second, commit to professional development on a foundational of personal experimentation with those techniques and tools in practical settings. There is no substitute for haptic learning. Beware of people who claim to provide technical leadership on the basis of someone else’s learning.

As a CTO I saw that some of the most interesting (at least to me) advances were in the world of data analytics. Given my attitude, I focused a significant majority of my professional development effort on data analytics. I didn’t ignore data management, but it turns out that’s mostly ‘good housekeeping’. It needs to be done but isn’t where the value is generated. Anyway, by the time I came across the opportunity to become the first Chief Data Officer for the DoD, I was already able to demonstrate the competency and capabilities they were looking for. 

Q: How long have you been in Data Leadership? 

A: I have been the Department’s Chief Data Officer for 23 months. It’ll be 24 months in early July. As it turns out, in the commercial sector the average tenure of a CDO is only 18 months so at least I’ve exceeded that average. I benefited from the passage of the Foundations for Evidence Based Policy Making Act, which the President signed into law in January of 2019. For ‘evidence’ substitute ‘statistically validated data’. We leveraged the Evidence Act to drive enormous improvements in the quality of the Department’s business data and in the Department’s cultural shift toward evidence-based decision making. Now I am shifting my focus onto advances in analytics.

Q: Recent stats show that most CDO's have been appointed in the past several years, how have you adjusted to coping of these new responsibilities?

A: This is actually a great time to be a CDO. You’re in control of your own destiny. It’s not for everyone but I thrive on emerging challenges when people are still figuring out what to do, when, why and how. From a Federal government perspective, there is a set of common expectations emerging. But the exact path needed to navigate through uncertainty needs to be discovered organization by organization. You need to work through the organization's full value chain, use case by use case and data story by data story, to get to value from Data Science. When it comes to Data Science, we're all winging it. Even the experts. Especially the experts; we're dealing with cutting edge problems and there's no playbook. This is applied Research & Development. We're figuring it out as we go. If a material percentage of your Data Science projects aren't failing, you're not taking the risks you need to take in order to increase your knowledge and skills.

Q: What qualifications do you think the role needs in the industry?

A: Caveat Emptor! Look, I’m very cynical about qualifications and certifications. The role is still new. It’s evolving rapidly. No two organizations have identical needs when it comes to data talent, data quality, culture and decision-making, analytical tools, partner ecosystem, etc. All these elements create the conditions the CDO needs to manage. The CDO role is in a similar state of maturity to the CIO role in the early 1990’s, with a similar pattern of talent turnover. No question there are a number of universities offering excellent undergraduate and post-graduate degrees in data science. And I’ve participated in some excellent certification programs. But I hesitate to offer a general prescription for the role.

Q: As a follow up what would you rate the top CDO Skills to be and why?

A: Attitude is more important than aptitude. You need a passion for learning and a passion for results. Outcomes are what ‘puts runs on the scoreboard’. You need a high tolerance for risk because of the rapid pace of innovation and change. You need to be willing to submerge your ego and help other executives bask in the limelight of the success you enable. You need a passion for finding and developing talent.

You need business savvy. You need facilitation and coalition-building skills. You need deal-making skills. Soft skills are essential. You need to maintain a hunger for your own continuing professional education. The CDO role is not a hands-on role; it’s not a general manager role either, unless your organization has a very high level of data quality and analytical maturity. Either way you need a strong grasp of statistics. You need systems thinking skills; the failure to consider second order and third order consequences is where you end up in the headlines.

Q: Where do you go to get more relevant information for your position?

A: I subscribe to a number of email newsletters that I read first thing each morning. I’m not supposed to name names because someone might misinterpret it as an endorsement. So let me just say I get: an email devoted to the general news and economics; one devoted to business and consumer news; one devoted to crunching the numbers on various trends; one specific to analytics and data management, and one devoted to marketing. In addition, I look through two news apps on my phone every morning. I follow the usual IT industry analysts, and one the specializes in AI/ML. I also routinely check-in with 5 or 6 VC firms to see where their investment portfolios are going.

Q: What would be the specific items that feel are missing, i.e. topics that you need to feel you need to get more information on or focus on?

A: My biggest challenge is that advancements are happening so rapidly I don’t have enough time to be current in more than a few areas. It’s the Red Queen’s Race.

Q: In what ways have you seen the recent event of the Pandemic affect how you manage your business?

A: We’ve created a Common Operating Picture to provide our executives with an evidence-based view of the Pandemic. We draw on a wide variety of sources and partners in order to show the Pandemic’s effect on the places we operate, and its effects on our people, their families and communities. We’re using this Common Operating Picture to provide executives with the evidence they need to make decisions about telework vs returning to normal work patterns. We’re also using it to analyze our supply chain.

Q: What are some of the things are you working on today that you see and beneficial to the organization?

A: Now that our business data is at a foundational level of quality, the big swing is toward analytics. We can be confident in the operating picture we generate of what happened and why. Now we’re rolling out analytic products that predict what will happen and why.

Q: Organizationally, who do you think the CDO should report to?

A: Let’s start at the start. Organizations invest in data and analytics for one reason - improve the organization’s performance. Whoever owns the organization's results has accountability for value capture in data science. That’s who the CDO should report to. CDOs are increasingly reporting to the CEO, COO or CFO function because data is a critical business priority, not just an IT concern. If your CDO is not reporting to that person then your CDO is not positioned for success.

Q: What do you think is your secret sauce to success in the CDO role?

A: If I have a secret sauce, it’s a relentless focus on learning.

Q: What if any best practices or tips would you like to offer the viewer in the role of the CDO?

A: Foster a data-driven, test-and-learn culture. Let the data speak to the situation. Communicate bad news quickly and without shame. What we learn along the way, and how widely we share that learning, is as important as the immediate outcome. Actively engage in the broader Data Science community (outside your enterprise) to leverage best-practices and learning from completely different fields. Celebrate both the outcome and the learning. Try to figure out what you should do next, not what the right answer is.