Cybersecurity Resilience Is an Operating Capability

Most organizations invest heavily in preventing cyberattacks.

Far fewer invest equally in their ability to continue operating when prevention inevitably fails.

That distinction matters.

Cybersecurity resilience is not measured by whether an organization experiences an attack. It is measured by how effectively it prepares for disruption, responds under pressure, recovers critical operations, and learns from the experience.

In today’s environment, resilience has become an operational capability rather than simply a cybersecurity objective.

Cybersecurity Is a Business Responsibility

Cybersecurity is often viewed as a technology function.

It isn’t.

Every significant cyber incident affects business operations, customer confidence, regulatory compliance, financial performance, and organizational reputation. While technology teams manage many of the controls, resilience requires leadership across the enterprise.

Executives, business leaders, legal counsel, communications teams, finance, operations, human resources, and technology all play critical roles before, during, and after an incident.

Organizations that recognize cybersecurity as an enterprise responsibility consistently respond more effectively than those that treat it solely as an IT problem.

Resilience Begins Before an Incident

Technical safeguards remain essential.

Identity management, multi-factor authentication, vulnerability management, endpoint protection, network segmentation, backups, monitoring, and security awareness all reduce organizational risk.

However, resilience requires additional capabilities.

Organizations should understand which business services are most critical, define recovery priorities, establish decision-making authority, exercise incident response plans, evaluate third-party dependencies, and ensure leadership understands its responsibilities during a crisis.

Preparation determines performance.

Leadership Matters Most During Uncertainty

Technology leaders are expected to provide calm, informed decision-making when information is incomplete and pressure is high.

That responsibility extends well beyond technical remediation.

Leaders must balance operational continuity, regulatory obligations, customer communication, executive decision-making, and organizational confidence while technical teams investigate and recover.

Resilient organizations develop these leadership capabilities before they need them.

Tabletop exercises, executive simulations, and cross-functional planning often provide greater long-term value than simply purchasing another security tool.

Recovery Is Part of Security

Organizations often focus heavily on preventing attacks while giving less attention to recovery.

Yet resilience depends on the ability to restore operations safely, validate system integrity, communicate transparently, and return the organization to normal business operations with confidence.

Recovery planning should address not only technology restoration but also business processes, vendor coordination, customer communications, regulatory reporting, and lessons learned.

Recovery is where preparation becomes operational performance.

Continuous Improvement Strengthens Resilience

Every incident, near miss, audit, and exercise provides an opportunity to improve.

The strongest organizations continually evaluate what worked, what failed, and where governance, technology, communication, or decision-making can be strengthened.

Cybersecurity resilience is not a project with a completion date.

It is an organizational capability that matures over time through disciplined leadership, continuous learning, and operational experience.

Resilience Creates Confidence

No organization can eliminate cyber risk entirely.

What leaders can control is how well their organizations prepare, respond, recover, and adapt.

Organizations that invest in resilience protect far more than their technology. They protect customer trust, organizational reputation, operational continuity, and the confidence that stakeholders place in their leadership.

In the end, cybersecurity resilience is not measured by avoiding every attack. It is measured by an organization’s ability to continue fulfilling its mission when adversity inevitably arrives.

Why Technology Leaders Must Speak the Language of Finance

One of the most valuable lessons I have learned throughout my career is that technology leadership is fundamentally a business discipline.

Technology decisions influence capital allocation, operating expense, productivity, risk, customer experience, and long-term enterprise value. Yet many organizations still treat finance and technology as separate conversations.

The most effective organizations recognize they are the same conversation viewed from different perspectives.

Technology Is an Investment Portfolio

Every organization has more technology opportunities than it has resources to pursue them.

Infrastructure modernization.

Cybersecurity.

Cloud adoption.

Artificial intelligence.

Data platforms.

Application modernization.

Digital transformation.

The question is rarely whether these initiatives have value.

The question is which investments should be made first.

Finance brings discipline to capital allocation.

Technology brings understanding of operational capability, technical risk, and long-term sustainability.

Together, they determine where limited resources will create the greatest business value.

Speaking a Common Language

Technology leaders often explain solutions in technical terms.

Finance leaders evaluate decisions through business outcomes.

Both perspectives are necessary.

When proposing a major technology initiative, executives should be able to explain not only how the technology works, but also how it affects revenue, operating expense, productivity, resilience, customer experience, regulatory compliance, and enterprise risk.

Successful technology leaders translate technical decisions into business outcomes.

That translation builds trust.

Cost Is Only One Dimension

Technology discussions frequently begin with cost.

The more important conversation is value.

A larger initial investment may reduce operating expense for years.

Infrastructure modernization may reduce outages, improve productivity, strengthen cybersecurity, simplify vendor management, and accelerate future initiatives.

Artificial intelligence may reduce repetitive work while allowing highly skilled employees to focus on higher-value analysis.

The objective is not minimizing technology spending.

It is maximizing organizational return.

Better Decisions Require Partnership

Finance should not evaluate technology investments after decisions have already been made.

Likewise, technology should not treat financial review as a final approval step.

The strongest organizations involve finance early in technology planning and technology leaders early in financial planning.

That partnership produces more realistic business cases, stronger prioritization, better forecasting, and more disciplined execution.

It also improves organizational confidence because investment decisions are based on shared understanding rather than competing priorities.

Leadership Beyond Technology

The role of today’s technology executive extends far beyond infrastructure and applications.

Technology leaders help organizations allocate capital, manage enterprise risk, evaluate acquisitions, improve operations, strengthen governance, and enable long-term growth.

Those responsibilities require financial fluency as much as technical expertise.

Understanding finance does not make technology leaders less technical.

It makes them more effective business leaders.

A Shared Objective

Finance and technology ultimately pursue the same objective: creating sustainable enterprise value.

Finance provides financial discipline.

Technology provides operational capability.

When both functions work together from the beginning, organizations make better decisions, invest more wisely, and execute with greater confidence.

The strongest technology leaders do not simply understand technology.

They understand how technology creates business value.

Building High-Performing Technology Teams

Technology organizations succeed because of people.

Infrastructure, cloud platforms, cybersecurity tools, automation, and artificial intelligence all matter. But none of them consistently create value without capable teams making sound decisions every day.

Looking back over my career, the strongest technology organizations I have been part of shared several characteristics. They were not defined by the newest technology or the largest budgets. They were defined by leadership, trust, accountability, and a commitment to developing people.

Create Clarity Before Accountability

People perform best when expectations are clear.

That means more than assigning work. Teams should understand why the work matters, how success will be measured, how it supports broader business objectives, and where they have the authority to make decisions.

When priorities continually shift or responsibilities are unclear, even highly capable teams struggle.

Good leadership creates clarity before demanding accountability.

Develop People, Not Just Systems

Technology evolves continuously.

The most valuable investment leaders can make is developing people who can adapt with it.

That includes technical training, certainly, but also communication, business understanding, decision-making, and leadership skills.

Many of the strongest contributors I have worked with grew because someone gave them an opportunity to solve a larger problem—not because they were assigned another routine task.

Organizations benefit when leaders actively create those opportunities.

Trust Produces Better Decisions

Technology work depends on judgment.

Engineers solve problems that cannot always be anticipated through procedures or documentation alone.

Leaders who build trust encourage people to raise concerns early, challenge assumptions respectfully, and share ideas without fear of criticism.

The result is not simply better morale.

It is better decision-making.

Remove Obstacles, Don’t Create Them

Leadership is not measured by how many decisions require executive approval.

It is measured by how effectively leaders enable their teams to execute.

That means eliminating unnecessary bureaucracy, clarifying priorities, resolving conflicts quickly, and ensuring teams have the tools, information, and authority needed to succeed.

The best leaders spend as much time removing obstacles as assigning work.

Build Teams That Learn

Technology organizations improve through continuous learning.

Projects succeed.

Projects fail.

Incidents occur.

New technologies emerge.

Each experience provides an opportunity to strengthen the organization.

High-performing teams conduct thoughtful retrospectives, document lessons learned, improve processes, and share knowledge across the organization.

Continuous improvement is not an initiative.

It becomes part of the culture.

Leadership Is Measured by the Team

One of the most important lessons I have learned is that leadership is not measured by individual expertise.

It is measured by the capability of the people around you.

The strongest leaders develop environments where individuals grow, collaboration becomes natural, accountability is shared, and success continues long after the leader has moved on.

Technology changes constantly.

Great leadership principles do not.

Organizations that invest in their people, encourage learning, and create trust consistently outperform organizations that rely solely on technical excellence.

Ultimately, technology leaders build more than systems.

They build teams capable of solving problems the organization has not yet encountered.

The Gabarée Family Chocolate Babka Recipe

Chocolate babka has become a family tradition in our home. Over the years I’ve experimented with several recipes before settling on this version, adapted from Jerusalem by Yotam Ottolenghi and Sami Tamimi. The result is a rich brioche dough filled with a silky chocolate ganache that has become one of our favorite treats to share with family and friends

Prep Time: 2 hours 
Cook Time: 35 minutes 
Chilling time: 12 hours 
Total Time: 14 hours 35 minutes 
Yield: 2 loaves

Ingredients

Tools and Miscellaneous:

Food scale (if available)

Measuring cup

Tablespoon

Teaspoon

Stand mixer with dough hook

Hand mixer

Spatula to scrape down the sides of the bowl when mixing the dough

Olive Oil to coat the bowl for when the dough is proofing

Plastic wrap to cover the dough bowl when proofing

Serrated knife

Two 9×5-inch bread pans

Butter for the sides of the bread pans 

Parchment paper for the bottoms of the bread pans

Offset spatula (preferred) or a regular one if an offset spatula is not available to spread chocolate filling

Brioche: 

4⅜ cups (530 g) all-purpose flour, plus extra for dusting 

½ cup (100 g) granulated sugar 

1 tablespoon (14 g) instant dry yeast 

3 large eggs 

½ cup (118 ml) water 

1 teaspoon (6 g) fine sea salt (do not use if butter is salted)

⅔ cup (150 g) unsalted butter, cut into small slices and softened to room temperature

Olive Oil to coat the bowl for when the dough is proofing

Butter for the bread pans 

Parchment paper for the bread pans

Chocolate Filling (modified chocolate ganache): 

200g (7 oz.) 70% dark chocolate 

½ cup (115 g) salted butter 

½ cup (60 g) powdered sugar 

⅓ cup (80 ml) heavy cream 

⅓ cup (50 g) unsweetened cacao powder 

Sugar Syrup: 

½ cup (118 ml) water 

½ cup (100 g) granulated sugar 

Instructions

Make the Dough:
Using a hand mixer, cream the butter and sugar together. Using the same hand mixer, mix the eggs with the creamed butter and sugar. Heat the water to between 105F and 112F. Mix yeast into the heated water using a fork.

Place flour, sugar, yeast, and salt in a standing mixer fitted with a dough hook and mix on low speed until combined. Add the water/yeast mixture and continue to mix on low speed until incorporated. The dough will be mostly dry and crumbly at this point. Add the creamed butter/sugar/egg mixture and mix on medium speed until the dough comes together, 2-3 minutes. Continue mixing for about 10 minutes on medium speed until the dough is completely smooth, elastic, and shiny. It will look soft and might be sticky – that’s ok. During mixing, you will need to scrape down the sides of the bowl.

With floured hands, transfer dough to a large mixing bowl brushed with olive oil, cover with plastic wrap, and leave in the refrigerator to proof for at least half a day or overnight. The dough may not look like it has risen much, but that's okay. If placed for a long time in the fridge, the dough can become hard; that’s also okay; leave it at room temperature until it’s easy to work with, usually around 30-60 minutes.

Grease two loaf pans (I usually use 9×5-inch pans, but a bit smaller or larger pans would also work), butter the sides of each pan, and line the bottoms with parchment paper for easy release later. Set aside.

Make the Filling:
In a double boiler (or medium saucepan with an aluminum bowl resting over it), bring water to a full boil. Place chocolate, butter, heavy cream, cocoa powder, and sugar into the top bowl. Lower the heat to moderate and melt together the contents of the top bowl, mixing frequently with a spatula. The mixture will have a fudgy look and consistency at this point. Reduce the heat to low and continue to mix until fully melted and completely smooth. Set aside the bowl to cool. It will thicken and become spreadable as it cools. You can also place it in the refrigerator briefly until you get a spreadable consistency.

Roll and Shape the Dough:
Divide the dough in half. Roll out the dough with a rolling pin on a lightly floured surface, and shape it into a rectangle measuring 16×12 inches (40×30 cm) and 0.25 inches (0.64 cm) thick. Fold the dough onto itself until it is about 25% it's original rolled-out size. Roll the dough out again, shaping it into a rectangle measuring 16×12 inches (40×30 cm) and 0.25 inches (0.64 cm) thick. Repeat the folding and rolling process one more time. Now position the dough so that the long side is closest to you. Repeat the above process for the other half of the dough.

Add the Filling and Shape the Babka:
Using an offset spatula, spread half of the chocolate mixture over the rectangle. It is ok to have some ganache left over. Spread just enough to cover the dough, between 0.15 (0.38 cm) and 0.25 inches (0.64 cm). Too much ganache will make the babka soggy and taste off-balance.

Use both hands to roll up the rectangle like a roulade, starting from the long side closest to you and ending at the other long end. Press to seal the dampened end onto the roulade, then use both hands to even out the roll into a perfect, thick cigar. Rest the cigar on its seam.

Using a serrated knife, gently cut the roll in half lengthwise, starting at the top and finishing at the seam, essentially dividing the log into two long, even halves, with the layers of dough and filling visible along the length of both halves. With the cut sides facing up, gently press together one end of each half, then lift the right half over the left half. Repeat this process, but this time, lift the left half over the right to create a simple two-pronged plait. Gently squeeze together the other ends so you are left with the two halves intertwined, showing the filling on top.

Carefully lift the cake into a loaf pan. Don’t worry if there are gaps in the pan since the cake will rise and will eventually look fine, even if it looks messy at this point. Cover the pan loosely with plastic wrap and leave to rise at room temperature for 1 to 1½ hours until almost doubled in size. Repeat to make the second babka.

Bake the Chocolate Babka:
Preheat oven to 350°F/175°C, allowing plenty of time to heat fully before the uncooked babkas have finished rising. Remove the plastic wrap and place the cakes on the middle rack of the oven. Bake for 30-35 minutes, until golden brown on top. If you have a thermometer, you are looking for an internal temperature of about 200ºF/93ºC degrees.

Make and Apply the Syrup:
While the cakes are in the oven, make the syrup. In a small saucepan over medium heat, bring water and sugar to a boil. As soon as the sugar dissolves, remove from heat and set aside to cool. As soon as the cakes come out of the oven, brush the syrup over them. Use all of the syrup, even if it looks like you used a lot. Let cakes cool until they are warm, then remove from pans and let cool completely before serving.

Serve:
Serve by itself warm or at room temperature. It also pairs nicely with ice cream and coffee.

This Chocolate Babka will stay fresh for 24 hours in an airtight container at room temperature, but will also be just fine for around five days in a plastic bread bag with a twist tie.

Where AI Creates Real Value in Finance

Artificial intelligence is not replacing finance.

It will change what finance professionals spend their time doing.

For decades, finance organizations have focused on collecting data, reconciling transactions, producing reports, and explaining what happened. Those responsibilities remain essential, but AI is changing how much time is required to complete them.

The real opportunity is not simply automating existing work. It is allowing finance teams to spend more time helping the business make better decisions.

AI Is an Accelerator, Not a Strategy

Organizations often begin their AI journey by asking:

“What tasks can we automate?”

A better question is:

“What decisions could we improve if our people had more time, better information, and stronger analytical tools?”

Finance has always been responsible for turning information into decisions. AI simply expands its ability to do that work faster and at greater scale.

Moving Beyond Reporting

Most finance organizations already possess large amounts of data.

Financial statements.

Forecasts.

Vendor spending.

Capital projects.

Procurement.

Contract performance.

Cash flow.

Operational metrics.

Historically, much of the finance team’s effort has been devoted to collecting, validating, and presenting that information.

AI allows those activities to become increasingly automated.

That creates capacity for work that generates greater organizational value:

• evaluating investment alternatives
• modeling strategic scenarios
• identifying operational inefficiencies
• improving forecasting accuracy
• strengthening vendor oversight
• supporting capital allocation decisions

The objective is not fewer finance professionals.

It is better use of financial expertise.

Better Decisions Require Better Data

Artificial intelligence amplifies the quality of the information it receives.

Organizations with fragmented systems, inconsistent data definitions, or poor governance should expect AI to expose those weaknesses rather than solve them.

Successful AI adoption depends on disciplined data management, clear ownership, consistent definitions, and governance that ensures information can be trusted.

Technology cannot compensate for poor data quality.

Finance and Technology Must Lead Together

AI adoption should never be viewed as an isolated technology initiative.

Finance understands business value.

Technology understands platforms, integration, cybersecurity, and implementation.

Together, they create solutions that are technically feasible, financially responsible, and operationally sustainable.

The strongest AI programs emerge when CFOs and CIOs work as partners rather than customers and service providers.

Governance Determines Long-Term Success

As AI becomes embedded within forecasting, financial planning, reporting, procurement, and decision support, governance becomes increasingly important.

Organizations should establish clear expectations for:

• data quality
• model transparency
• regulatory compliance
• human review of significant decisions
• security and privacy
• accountability for AI-generated outputs

Trust is built through governance, not automation.

AI Should Augment Human Judgment

The greatest contribution AI can make to finance is not replacing analysis.

It is creating more time for it.

Finance professionals are uniquely positioned to evaluate tradeoffs, challenge assumptions, assess risk, and allocate capital. Those responsibilities require judgment, experience, and business context that AI cannot provide independently.

Organizations that use AI successfully will automate routine work while elevating the strategic role of their finance teams.

That is where the greatest value will be created.

AI is changing finance, but its greatest contribution will not be producing reports faster. It will be giving finance leaders more capacity to guide better decisions across the enterprise.

What Total Football Teaches Us About Adaptive Organizations

One of the most influential business articles I’ve ever read wasn’t really about manufacturing.

It was about adaptability.

While reading Making Mass Customization Work by B. Joseph Pine II, Bart Victor, and Andrew C. Boynton, I was reminded of an entirely different discipline: Total Football.

Originally developed and popularized by Ajax and the Dutch national team, Total Football challenged one of the fundamental assumptions of team sports. Instead of rigid positional responsibilities, every player understood the broader system. As one player advanced, another instinctively filled the space. The team remained balanced because everyone understood both their own role and how their role fit within the larger objective.

The lesson extends far beyond football.

Adaptability Creates Competitive Advantage

Organizations often define people by job titles.

Engineers engineer.

Project managers manage projects.

Security teams secure systems.

Operations teams operate infrastructure.

Specialization is important, but organizations become fragile when work depends too heavily on rigid organizational boundaries.

The most resilient organizations develop people who understand how the entire system works, not just their individual responsibilities.

When priorities change, customer needs evolve, or unexpected problems emerge, those organizations adapt far more effectively because people know how to collaborate beyond functional silos.

Every Team Needs Positional Flexibility

Positional flexibility does not mean everyone performs every job.

It means individuals understand enough about adjacent functions to contribute when circumstances require it.

I’ve consistently found that organizations perform better when engineers understand customer impact, project managers appreciate technical constraints, security teams participate early in architecture discussions, and infrastructure teams understand business priorities.

People remain specialists.

But they stop becoming isolated specialists.

Shared Awareness Is More Valuable Than Perfect Processes

Many organizations attempt to solve complexity by adding process.

Process certainly has value, but process alone rarely creates adaptability.

Shared awareness does.

Teams that communicate continuously, understand organizational priorities, and trust one another make better decisions even when situations change unexpectedly.

That principle explains why high-performing organizations often respond to disruption more effectively than organizations with more documentation or more rigid governance.

The difference is not process maturity.

It is collective understanding.

Leadership Creates the Conditions

Adaptive organizations do not emerge by accident.

Leaders create environments where collaboration is rewarded, information moves freely, and expertise is valued regardless of organizational boundaries.

That often requires cross-functional projects, rotational assignments, shared objectives, and deliberate investment in developing broader business understanding—not simply deeper technical specialization.

People become more valuable when they understand how their work enables everyone else’s success.

Technology Organizations Need This More Than Ever

Artificial intelligence, cloud platforms, cybersecurity, data engineering, enterprise architecture, and software delivery have become deeply interconnected.

No single discipline can solve today’s enterprise challenges independently.

Technology organizations increasingly succeed through coordinated expertise rather than isolated excellence.

The leaders who build adaptive organizations recognize that the goal is not to eliminate specialization. It is to create enough shared understanding that teams continue moving forward when priorities shift.

The Best Teams Think Like Systems

Total Football demonstrated that extraordinary teams are built on flexibility, trust, communication, and shared purpose.

The same is true for modern organizations.

Competitive advantage increasingly belongs to organizations that can learn faster, adapt sooner, and coordinate more effectively than their competitors.

That begins with leaders who build systems where people understand more than their own position—and recognize that the success of the organization depends on how well those positions work together.

Who Carries the Risk? Lessons from Technology Contracting

One of the most important questions in any technology contract is not the price.

It's: Who carries the risk when conditions change?

Technology projects rarely unfold exactly as expected. Supply chain disruptions, cybersecurity requirements, inflation, changing business priorities, labor shortages, and evolving technical standards all affect cost, schedule, and delivery. Well-structured contracts recognize those realities by clearly allocating risk between the customer and the service provider.

Understanding those tradeoffs is an important leadership responsibility.

Fixed Price Does Not Mean Fixed Risk

Many organizations assume a fixed-price contract transfers all financial risk to the contractor. In practice, risk is shared, even when pricing is fixed.

If specialized hardware becomes unavailable, labor costs rise unexpectedly, or regulatory requirements change during execution, someone ultimately absorbs those additional costs. The question is whether the contract anticipated those possibilities and assigned responsibility appropriately.

In federal contracting, that balance is particularly important. Government agencies seek cost certainty and responsible stewardship of taxpayer resources. Contractors, meanwhile, must manage delivery risk while maintaining financial viability. Successful partnerships recognize that long-term performance depends on both objectives being achieved.

Innovation Changes the Equation

Risk allocation also works in the opposite direction.

As organizations improve delivery methods, automate repetitive work, standardize platforms, or streamline operations, the cost of delivering services often declines. Those efficiencies create opportunities for contractors to improve margins while remaining more competitive in future procurements.

In competitive markets, many of those operational improvements are ultimately reflected in lower bid prices or greater value delivered to customers. Organizations that continually improve how they work often compete more successfully than those relying solely on lower labor rates.

Contracts Should Encourage Better Outcomes

The strongest technology contracts are not designed simply to control cost. They encourage behaviors that improve long-term outcomes.

When incentives are aligned, organizations invest in automation, standardization, cybersecurity, quality, and continuous improvement because those investments benefit both parties. When incentives are poorly aligned, organizations may optimize for short-term contract performance at the expense of long-term operational success.

Technology leaders should evaluate contracts not only for commercial terms but also for how effectively they distribute risk, encourage innovation, and support sustainable performance.

Leadership Beyond the Contract

Technology contracting is ultimately an exercise in governance.

Leaders must understand where risk resides, how changing market conditions affect delivery, and whether contractual incentives continue to support the organization’s strategic objectives.

The goal is not simply to negotiate the lowest price. It is to create partnerships that remain resilient as technology, markets, and organizational priorities evolve.

The organizations that consistently achieve the best outcomes understand that effective contracting is less about transferring risk than managing it intelligently.