Industrial operations have spent decades optimizing for safety, reliability, and uptime. Control systems, sensors, and field equipment were designed to be stable and predictable, often isolated from the outside world. Cybersecurity, by contrast, evolved largely in IT environments, on a separate track, with different tools, assumptions, and incentives.

That separation is no longer holding. Operational technology is becoming more connected, more digital, and more automated. Sensors stream data to the cloud, vendors require remote access, and AI-driven tools increasingly influence operational decisions. At the same time, cyber threats are moving faster, targeting physical systems with the potential for real-world safety and production impacts.

One response is data meshing: combining traditional cyber telemetry with operational data such as vibration, maintenance history, and asset performance to create a richer, more reliable picture of what is really happening inside industrial environments. When these signals are viewed together, anomalies surface faster, false positives drop, and attacks become harder to hide.

In this episode, I'm speaking with Ian Bramson, VP of Global Industrial Cybersecurity at Black & Veatch, and Keon McEwen, Head of Solutions Development for Industrial Cybersecurity. We discuss why the old idea of the air gap is fading, how safety and cybersecurity are converging, what data meshing really means in practice, and why points of operational change are the right moment to rethink cyber risk.

👥 About the Guests

Ian Bramson is Vice President of Global Industrial Cybersecurity at Black & Veatch. He has spent more than two decades working at the intersection of digital transformation, cybersecurity, and critical infrastructure, with prior roles spanning consulting, energy, and operational technology environments. Ian focuses on helping industrial organizations manage cyber risk as systems become more connected and automated.

Keon McEwen is Head of Solutions Development for Industrial Cybersecurity at Black & Veatch. With a background in programming PLCs and operational systems, Keon bridges OT and cyber disciplines, designing practical security solutions that account for how industrial assets actually operate in the field.

🌐 Black and Veatch

🛠️ Additional Tools & Resources

🎬Go backstage and check out my studio

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🔗 Connect with Me

📘 Blog: https://digitaloilgas.substack.com/

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🎤 Contact for Lectures and Keynotes

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Book a brief call about your upcoming event here:

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⚠️ Disclaimer

The views expressed in this podcast are my own and do not constitute professional advice.

Oil and gas companies generate enormous volumes of operational, geological, and production data. Despite this abundance, much of that data remains fragmented, inconsistent, and difficult to trust. Teams often spend a significant portion of their time preparing datasets rather than analyzing them. The result is delayed decision-making, inflated costs, and reduced operational agility.

The core complication lies in data quality, data governance, and data readiness. Duplicate records, null values, drift, and structural inconsistencies make it difficult to move quickly from raw data to actionable insight. Asset teams frequently work semi-independently, each rebuilding transformation processes from scratch. Without reliable data foundations, scaling analytics, automation, or advanced modelling becomes difficult and costly.

In this episode, I'm in conversation with Shravan Gunda, CEO of Kaarvi, to discuss how a structured approach to data ingestion, anomaly detection, ETL transformation, and data lineage can reduce time-to-insight from weeks to hours. He outlines how upstream teams can standardize workflows, support governance requirements such as SOC 2, and deploy platforms either on-premises or via SaaS. Clean, trusted data is a prerequisite for accelerating analytics and enabling more advanced digital capabilities.

👤 About the Guest

Shravan Gunda is the CEO of Kaarvi, an enterprise data platform focused on data quality, governance, transformation, and observability. He previously worked in senior technology roles supporting national oil companies and has extensive experience managing large-scale industrial datasets across upstream environments.

🌐 Website: Kaarvi.ai

💼 Shravan Gunda on LinkedIn

📊 Download the white paper: Operationalizing Agentic AI Across The Entire Data Life Cycle

⚒️ Additional Tools & Resources

🎬 Go backstage and check out my studio:

https://geoffreycann.com/mystudio/

🎓Take my one-day digital strategy training course for oil and gas:

https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me

📘Blog series: https://digitaloilgas.substack.com/

🎧 Podcast: https://geoffreycann.com/broadcast/

💼 LinkedIn: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🐦 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes

I speak regularly on these and related topics. Contact me to book a brief call about your upcoming event needs.

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⚠️ Disclaimer

The views expressed in this podcast are my own and do not constitute professional advice.

Diesel generators have long been the default answer for powering upstream and midstream oil and gas sites. They are familiar, mobile, and deeply embedded in operating practice. Even in regions with abundant natural gas, operators often rely on fleets of diesel gens to run pumps, wireline units, and auxiliary equipment, treating gas as either waste or something to move to market while importing fuel to keep operations running.

That status quo is becoming harder to defend. Diesel is expensive, noisy, logistically complex, and increasingly misaligned with emissions rules, carbon pricing, and community expectations. Operators face growing pressure to cut operating costs, reduce flaring, and lower emissions, while still maintaining reliability in the field. Yet infrastructure change moves slowly, driven more by habit and organizational friction than by technical limits.

In this episode I'm speaking with Michael Lawson, Vice President of Business Development at Enterprise Group, about using stranded or low-value natural gas to electrify well pads and industrial sites. We discuss replacing dozens of diesel generators with a single gas-turbine microgrid, the economics of site electrification, what kinds of gas streams can be used, and why mindset, not technology, is often the real barrier. It's a practical conversation about cost, reliability, emissions, and why electricity is quietly becoming the enabler of digital innovation in the field.

👤 About the Guest

Michael Lawson is Vice President of Business Development at Enterprise Group. Based in Calgary, he has more than two decades of experience across upstream and midstream oil and gas. His current work focuses on site electrification, deploying natural-gas turbines and microgrids to displace diesel power at industrial and energy work sites.

📧 Contact Michael: [email protected]

🌐 https://enterprisegrp.ca

#michaelcjlawson

⚒️ Additional Tools & Resources

🎬 Go backstage and check out my studio:

https://geoffreycann.com/mystudio/

🎓Take my one-day digital strategy training course for oil and gas:

https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me

📘Blog series: https://digitaloilgas.substack.com/

🎧 Podcast: https://geoffreycann.com/broadcast/

💼 LinkedIn: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🐦 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes

I speak regularly on these and related topics. Contact me to book a brief call about your upcoming event needs.

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⚠️ Disclaimer

The views expressed in this podcast are my own and do not constitute professional advice.

Data centers have shifted from supporting enterprise IT to running large parts of the digital economy. They now host AI model training, AI inference, and many critical digital services. As this shift accelerates, data centers are placing greater demands on power systems and operations teams. Managing energy use, uptime, and physical infrastructure has become central to how these facilities operate.

The challenge is that data center growth is moving faster than the tools used to manage it. Many operators still depend on legacy monitoring systems and spreadsheets to understand complex environments. These approaches struggle with rising power density, sustainability targets, and security requirements. At the same time, data sovereignty and grid access are influencing where new infrastructure can be built.

In this episode, I speak with Jad Jebara, CEO and co-founder of Hyperview, about how data center operations are changing. We discuss why cloud-native platforms are replacing legacy tools for managing power, facilities, IT, and OT systems. Jad explains how improved operational visibility supports security, efficiency, and scalability. We also explore what these shifts mean for energy companies and oil and gas producers supplying power to this growing infrastructure.

👤 About the Guest

Jad Jebara is the CEO and co-founder of Hyperview, a cloud-native platform designed to manage and optimize critical digital infrastructure. He is a CPA and CMA with a master's degree in professional accounting from the University of Texas at Austin. Jad previously helped scale a global hosting company from $35 million to over $600 million in revenue, overseeing large-scale infrastructure operations across multiple regions.

🌐 https://www.hyperviewhq.com

💼 https://www.linkedin.com/in/jadjebara/

⚒ Additional Tools & Resources

🎬 Go backstage and check out my studio:

https://geoffreycann.com/mystudio/

🎓 Take my one day digital strategy training course for oil and gas:

https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me

🖥 Blog series: https://digitaloilgas.substack.com/

🎧 Podcast: https://geoffreycann.com/broadcast/

💼 LinkedIn: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

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🎤 Contact for Lectures and Keynotes

I speak regularly on these and related topics. Contact me to book a brief call about your upcoming event needs:

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⚠️ Disclaimer

The views expressed in this podcast are my own and do not constitute professional advice.

Oil and gas operators have always known that surplus equipment is part of doing business. Projects get cancelled. Long-lead items are over-ordered. Assets are parked in yards, warehouses, and sea cans "just in case." Over time, those decisions quietly turn into idle capital sitting on balance sheets, often forgotten until space runs out or write-downs loom.

What's changed is the cost of ignoring it. Tight capital markets, tariffs, long lead times, and supply chain friction make surplus harder to justify. At the same time, operators face pressure to improve capital efficiency, demonstrate sustainability, and recover value from assets that still have useful life. Leaving equipment to rust is no longer neutral. It is a choice with a price tag.

There is, however, a better way. With the right data, photos, documentation, and market reach, surplus assets can be exposed to real demand, often well beyond the local buyer network. Digital marketplaces create price discovery, expand the buyer pool across industries and geographies, and turn forgotten inventory into cash, faster than expected.

In this episode, I'm joined by Xochi Schumann, an account executive in the Energy Division at Liquidity Services. We talk about why surplus builds up, why data really is money, how digital marketplaces like AllSurplus change recovery outcomes, and why many operators are discovering real value hiding in plain sight.

#Surplus #InvestmentRecovery #AssetRecovery #CircularEconomy #OilAndGas #FleetManagement #AssetDisposition

🗣️ About the Guest

Xochi Schumann is an account executive with Liquidity Services, working in the Energy Division. She brings more than 30 years of oil and gas experience, including a decade in operations at a turnkey drilling company, where inventory management was a core responsibility. That background gives her a practical, operator-level view of how surplus builds up and how it can be monetized. Today, she helps energy companies convert surplus equipment into liquidity through AllSurplus' global digital marketplace.

🔗 Connect with Xochi Schumann

LinkedIn: https://www.linkedin.com/in/xochis

email: [email protected]

website: https://liquidityservices.com/energy-surplus-asset-sales

Liquidity Services: https://www.linkedin.com/company/liquidity-services-inc

AllSurplus: https://www.linkedin.com/company/allsurplus

⚒️ Additional Tools & Resources:

🎬 Go backstage and check out my studio: 👉 https://geoffreycann.com/mystudio/ 🎓 Take my one day digital strategy training course for oil and gas: 👉 https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me:

🖥️ Blog series: https://digitaloilgas.substack.com/ 🎧 Podcast: https://geoffreycann.com/broadcast/ 📇 Linkedin: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🤬 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes:

I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. Click here 👉 https://geoffreycann.com/contact/

⚠️ Disclaimer:

The views expressed in this podcast are my own and do not constitute professional advice.

Upstream oil and gas companies continue to be very reliant on spreadsheets, legacy systems, and manual workflows to manage thousands of wells, compliance filings, and capital decisions. It's labor-intensive, error-prone, and slow. In light of global energy transition moves, operators are now facing ongoing margin pressure, a supply glut, tighter emissions regulations, and a shrinking pool of skilled labor.

Digital solutions to soften the impacts of these pressures too often end up in "pilot hell", with limited results, stalled momentum, and no path to scale. Core systems like SCADA and ERP can't be easily adapted, and the early stage AI tools are often dismissed as too risky, inaccurate, or incompatible with real-world operations. Capital markets frown on any moves that sacrifice short term ROI for the possibility of better results later.

New agentic AI tools look perfectly placed to address these constraints, but getting started is daunting.

In this episode, I speak with AI strategy advisor Jeff McKee who outlines how a handful of upstream operators are now using agentic AI (modular software agents), that augment field teams and automate critical tasks across production, compliance, and finance. Already live across 1,500 wells, these tools have delivered a 3–10% uplift in production, 5–15% profit lift, and >90% reduction in compliance workload. Jeff explains how companies can start small, define just a few key KPIs, and stand up agents in under two months, all without touching core systems. From Sarbanes-Oxley readiness to workover economics, it's a roadmap for scaling AI one agent at a time.

👤 About the Guest

Jeff McKee is the founder of Jeff McKee Consulting and an AI strategy advisor to $100M–$1B+ companies. A former Microsoft leader, he created the PIVOT AI™ framework to help executive teams identify high-impact AI use cases and deliver results fast. In oil and gas, he partners with Mango Bites (Pixie AI) to enable production optimization, profitability, and compliance across upstream field operations.

🌐 Website: jeffmckeeconsulting.com

💼 LinkedIn: linkedin.com/in/jeff-mckee

📧 Email: [email protected]

⚒️ Additional Tools & Resources:

🎬 Go backstage and check out my studio: 👉 https://geoffreycann.com/mystudio/ 🎓 Take my one day digital strategy training course for oil and gas: 👉 https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me:

🖥️ Blog series: https://digitaloilgas.substack.com/ 🎧 Podcast: https://geoffreycann.com/broadcast/ 📇 Linkedin: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🤬 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes:

I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. Click here 👉 https://geoffreycann.com/contact/

⚠️ Disclaimer:

The views expressed in this podcast are my own and do not constitute professional advice.

The energy industry is rapidly adopting artificial intelligence. Its promises of improved productivity, safety, and operational insight are too good to ignore. But these tools are only as good as the data that feeds them. And therein lies the problem: data across the sector is often incomplete, inconsistent, and scattered.

This historic lack of discipline around data now has consequences. Poor data quality when used in AI undermines any project leveraging AI, exposing companies to greater audit risk, slowing down decision-making, and derailing expensive digital programs. Worse, AI tools amplify these flaws, making unreliable data more visible than ever. In one instance, a company's emissions breach turned out to be a data error that triggered fines, audits, and reputational damage.

Companies struggle to respond, given the scale of the challenge. Getting control of enterprise data often feels like boiling the ocean, compounded by organizational practices that empower every business unit to do things their own way.

In this week's podcast, I speak with Waseem Sinjakli, who knows this challenge well. As the founder and Managing Director of EPM, a Calgary-based consultancy, he's led enterprise-wide transformation programs that put data governance at the center of AI readiness. In this episode, Waseem shares what good governance really looks like, the cultural barriers companies must overcome, and how to turn data from a liability into a high-value asset.

👤 About the Guest

Waseem Sinjakli is the Founder and Managing Director of EPM, a Calgary-based professional services firm focused on complex digital transformations in the energy sector. Building on his lengthy career with leading organizations in professional services, Waseem brings deep expertise in project delivery, change management, and digital enablement. EPM specializes in transformation programs tied to regulatory compliance, operational efficiency, cost optimization, and AI-driven insights.

🔗 LinkedIn: Waseem Sinjakli

🌐 Website: EPM

⚒️ Additional Tools & Resources:

🎬 Go backstage and check out my studio: 👉 https://geoffreycann.com/mystudio/ 🎓 Take my one day digital strategy training course for oil and gas: 👉 https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me:

🖥️ Blog series: https://digitaloilgas.substack.com/ 🎧 Podcast: https://geoffreycann.com/broadcast/ 📇 Linkedin: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🤬 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes:

I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. Click here 👉 https://geoffreycann.com/contact/

⚠️ Disclaimer:

The views expressed in this podcast are my own and do not constitute professional advice.

Have you ever given thought to the possibility that the suppliers of your core business technology, brands like Microsoft, Oracle, and SAP, might simply turn you off with no warning?

It sounds fanciful, absurd, a black swan event so far beyond any reasonable risk matrix as to be unworthy of consideration.

Yet it happened this year, 2025, to a major oil company in the world's most populous country.

What was once unimaginable is now here, and with it, lessons for every oil and gas organization, indeed every company, about the new risks in the digital landscape.

⚒️ Additional Tools & Resources:

🎬 Go backstage and check out my studio: 👉 https://geoffreycann.com/mystudio/ 🎓 Take my one day digital strategy training course for oil and gas: 👉 https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me:

🖥️ Blog series: https://digitaloilgas.substack.com/ 🎧 Podcast: https://geoffreycann.com/broadcast/ 📇 Linkedin: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🤬 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes:

I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. Click here 👉 https://geoffreycann.com/contact/

⚠️ Disclaimer:

The views expressed in this podcast are my own and do not constitute professional advice.

Most large enterprises rely on a handful of expansive technology platform solutions to run their business, and the most prominent and widely deployed in oil and gas is SAP. As I've outlined in my books, enterprise solutions such as SAP are also migrating to digital technologies, which triggers a major question: what is the optimal upgrade path for an SAP customer, or any enterprise technology, to adopt?

Broadly speaking, there are two strategies to this vexxing question: a brownfield migration or "lift and shift" and a greenfield re-implementation or "start afresh". The problem is that brownfield upgrades rarely deliver any ROI while greenfield is seen as too risky, costly, or complex to execut, especially at the global scale one encounters among the oil and gas majors.

Is there a third path, where organizations can preserve their historical data, stay compliant, and still deliver tangible business outcomes?

In this episode I speak with Don Mahoney, Global Head of Products and Innovation at SNP Group about a new approach, coined 'bluefield'. Bluefield lets companies dial in just the right amount of transformation, one that preserves key data, avoids excessive risk, and achieves a positive ROI. I'm very interested in how Bluefield works, how it supports AI training strategies, when to use it, and why it's becoming an attractive model for SAP S/4HANA transitions, and indeed all major platform solution transformations.

👤 About the Guest

Don Mahoney is the Global Head of Products and Innovation at SNP Group, where he leads strategy for the company's transformative deployment technologies, including its flagship Bluefield methodology. Don brings over 30 years of experience across process industries, enterprise software, and solution management. He previously held senior roles at SAP, overseeing strategic accounts like ExxonMobil and leading SAP's global chemical industry business unit.

🔗 LinkedIn: Don Mahoney

🌐 Website: SNP Group

⚒️ Additional Tools & Resources:

🎬 Go backstage and check out my studio: 👉 https://geoffreycann.com/mystudio/ 🎓 Take my one day digital strategy training course for oil and gas: 👉 https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me:

🖥️ Blog series: https://digitaloilgas.substack.com/ 🎧 Podcast: https://geoffreycann.com/broadcast/ 📇 Linkedin: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/

🤬 X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes:

I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs. Click here 👉 https://geoffreycann.com/contact/

⚠️ Disclaimer:

The views expressed in this podcast are my own and do not constitute professional advice.

Motors are the quiet workhorses of industry. They drive pumps, fans, compressors, and heaters, and they consume more than sixty percent of the power in most industrial operations. When operators need to control motor speed, they historically relied on mechanical adjustments or trial-and-error testing to keep processes stable and safe.

As motors get larger and drive trains more complex, traditional testing approaches no longer work. Bringing every component together for a full string test adds months of delay and millions of dollars in logistics. The industry is conservative and reference driven, which makes it hard for operators to trust new configurations without seeing them proven first.

This is where simulations shine.

In this episode, I speak with Anand Jha, Vice President of Global Sales for ABB System Drive – Process Industries, about simulation twins that let operators model the entire system before it's built. These "virtual plants" replicate the grid, the drives, the motors, and the compressor.

With software-in-loop and hardware-in-loop tools, operators can validate performance, tune configurations, and eliminate expensive string tests. The result is faster execution, lower cost, deeper system insight, better training, and continuous improvement across the plant lifecycle.

👤 About the Guest

Anand Jha is the Vice President of Global Sales for ABB System Drive – Process Industries. With over 20 years of experience in the Oil & Gas and other Process industries, Anand has held various roles from commissioning engineer to sales leader. He is also an accomplished author, having written two books. Anand holds an MBA from the University of Alberta in Canada and a B.Tech in Electronics and Instrumentation.

🌐 ABB Drives | ABB 🔗 Anand Jha on LinkedIn 📧 [email protected] 🧰 Additional Tools and Resources

• Go backstage and check out my studio: https://geoffreycann.com/mystudio/
• Take my one day digital strategy training course for oil and gas: https://www.udemy.com/course/digital-oil-and-gas/?referralCode=0161D4D49AB75735A185

🔗 Connect with Me

• Blog series: https://digitaloilgas.substack.com/
• Podcast: https://geoffreycann.com/broadcast/
• LinkedIn: https://www.linkedin.com/in/advocate-digital-innovation-for-energy/
• X: https://x.com/geoffreycann

🎤 Contact for Lectures and Keynotes

I speak regularly on these and other topics. Contact me to book a brief call about your upcoming event needs: https://geoffreycann.com/contact/

⚠️ Disclaimer

The views expressed in this podcast are my own and do not constitute professional advice.