If Your Organization Doesn’t Support You… Leave — Gold Nuggets From a Field CTO Cum Academic

Why does David Nicholson, a CTO with 30+ years behind his back, find it necessary to teach in a classroom?
David Nicholson
David Nicholson

David Nicholson is the Field CTO for the Americas at data storage provider Infinidat, as well as the Chief Research Officer at The Futurum Group. He has been in the technology biz for over three decades now, working with organizations like EMC, Oracle, and Virtustream.

Alongside being a C-level tech executive, Nicholson has a fair bit of presence in the academic space, leading a couple of technology and transformation *programs* at the Wharton Business School. He leads Wharton’s “CTO Program” as well as the “Digital Transformation for Senior Executives Program,” and also delivers guest lectures for CTO programs at universities like Cambridge Judge Business School.

The academic side has grown on him, friends might occasionally call him “professor” in jest. However, Nicholson underscores that he could be a program head, a guest lecturer, or a success coach, but not Dr. Nicholson just yet.

He also serves as a confidant and career mentor for “those who want someone to discuss what it means to leverage the ‘CTO Mindset’ in a practical way.”

In this interview with CDO Magazine, Nicholson opens up about his outlook for the storage industry, his take on the GenAI buzz, critical knowledge gaps in today’s data leaders, and the push-pull dynamics between his academic and tech leader selves.

Edited excerpts:

Q: What are the biggest challenges that businesses are facing today when it comes to data storage and management?

I think of this question from the perspective of business leaders, specifically, those who need a “CTO mindset.” The biggest challenge remains the same as always you have finite resources and infinite demands.

You must run the business while changing the business protect data from ransomware attacks and make it more accessible for training AI models. It’s called “Ambidextrous Management.”

It’s the same challenge but increasingly complicated and requires leaders and organizations to align well and execute flawlessly or get devoured by more agile competitors.

Q: Do you foresee any major shifts?

The last two years have convinced me that a focus on fundamentals is critical. If you develop a disciplined approach to leveraging technology to solve business problems, it won’t matter what comes next.

The “Karate Kid” was taught “Wax on, wax off.” Develop those reflexes when it comes to dealing with disruption and driving innovation, and you’ll be way ahead of the average leader who just wings it.

Q: What are some of the most exciting new developments in the world of data storage that you are looking forward to in the next few years?

Developments?! How about acknowledgments? People will realize that saying, “We have a cloud-first philosophy,” is as silly as a mechanic having a “screwdriver-first” philosophy: “I don’t care if it looks like it needs a 10mm socket, I will first try my screwdriver.”

We will be acknowledging that – if your job is to leverage technology in the service of your organization’s mission, then it's all about evaluating the tools available and picking the best one for a given job.

Q: ...and how should data leaders prepare for them?

In the Wharton CTO program, we talk about the virtuous cycles of strategizing, scanning, and executing. All three need to be core competencies when leveraging technology as it develops. Build that solid framework, and you’ll be ready for whatever comes next.

Q: What are the top 5 things you notice when looking at the GenAI buzz?

1. AI really is a revolution.

2. Despite being revolutionary, a lot of the really valuable benefits of AI will be in the area of increasing efficiency. They will be about optimizing the “run the business” side of things and might not be particularly novel…and that’s OK.

3. A lot of what is being called AI in boardrooms today is really just mature machine learning.

4. The larger the organization, the more likely it is to get caught up in the AI hype and forget about the fundamentals of data science and data engineering.

5. A lot of people think that AI is immune from the “garbage in, garbage out” dilemma. It isn’t. Data engineering is more important than ever before.

Q: Please tell us about the academician side of David Nicholson – how and when did it start?

I was happily out on my own, working as a consultant to the worlds of private equity, venture capital, investment banking, underwriting, global systems…um…integrating, etc., when a client introduced me to the Wharton program through someone affiliated with it.

I was invited to be a guest speaker to talk about experiences I had as a CTO dealing with major disruptions in IT. I gave that talk to two different universities and was just thrilled to get the merit badge as a guest lecturer, but they offered me a job. I said, “Yes.”

Q: How do the dynamics work for you between both sides – do they complement each other… How does it work?

It’s the greatest job ever. Without the academics, I had no proper language to convey certain complex principles within an organization aside from what I made up along the way.

My students have someone who is still actively in the game, and organizations I am affiliated with enjoy access to the insights I gain from being surrounded by hundreds of senior executives the smartest minds on the planet.

My roles as Chief Research Officer for The Futurum Group, as well as my CTO work, have certainly benefited from the additional perspectives I get in class.

I honestly came to this program with a sizable chip on my shoulder. After many decades of being immersed in the world of information technology, what could an academic possibly teach me? It turned out to be A LOT.

Q: What would be the most common knowledge gap you see in today’s data leaders and how can they fill them?

Ironically, I am seeing the challenge to be understanding foundational truths. Data center muscles are atrophying and basic computer science fundamentals are being forgotten.

It doesn’t matter where an IT workload is running, we still process, store, and share data. Some have lost sight of these fundamentals and are suffering for it.

Q: The Wharton programs you are involved with – Who are they for and why were they created in the first place?

Both *programs* are designed for senior executives seeking to formalize and receive accreditation for a combination of what they already know, along with new insights and teachings from our faculty.

These programs are frameworks or vessels that need to be filled with the experiences that participants have had in their own journeys to complete the value proposition. A person five years out of graduate school would, generally speaking, be completely lost.

The average participant has 20+ years of experience beyond graduate school. Each has found his/her way with very little in the way of a formalized guidebook. Each has existed in various stovepipes where it is difficult to truly develop peer-to-peer relationships beyond their organizations or industries.

This is an opportunity to make sense of their world by learning disciplined approaches to more efficiently do what they do.

It makes my week to see, for example, a CIO from big pharma and a CTO from big finance light up with excitement as they use newly acquired tools to share experiences and learn from one another. Or, a CEO from biotech and someone from the auto industry talk about how to best build consensus in the boardroom.

Q: Any interesting career recommendations for data/technology leaders (current and future)?

Take time to learn away from your day job. Network with peers outside of your comfort zone and the stovepipe of your area of expertise. Investment in yourself is always a good investment. If your organization doesn’t support you… leave. Life is too short.

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How Should CEOs Think About Generative AI? – Delivering Business Value
David Nicholson

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