Leadership in Action
Real-world examples of building stronger organizations, aligning teams, and delivering measurable business outcomes.
A leadership philosophy is only meaningful when it produces results. These case studies illustrate how I approach complex challenges, build alignment, and create the conditions where great products—and the teams behind them—can thrive.
Executive Case Study 01
Building Product Management from the Ground Up
Organization: Laivly
“Building Product Management wasn’t about introducing new processes—it was about restoring trust, creating strategic clarity, and transforming product decisions from assumption-driven to customer-informed.”
The Situation
When I joined Laivly as its first Product Manager, the organization had no formal Product Management function. Product decisions were engineering-led, customer discovery was informal, roadmap prioritization lacked structure, and little documentation existed to explain what was being built—or why.
The company’s flagship workforce management platform, SuperPunch, supported approximately 15,000 call center representatives by integrating with telephony systems such as Avaya to calculate payroll hours and manage attendance points.
Although executives had mandated its use, the platform had lost the trust of the people it was built to serve. It was unstable, difficult to use, and, most critically, attendance point calculations were inaccurate. Employees were being disciplined—and in some cases losing their jobs—because of system errors rather than actual attendance issues.
Engineering had accumulated a backlog of approximately 150 Jira items, but most represented assumptions about customer needs rather than validated customer problems.
The Challenge
The challenge wasn’t delivering more features—it was establishing Product Management as a strategic discipline, rebuilding confidence in a product users no longer trusted, and shifting the organization from assumption-driven development to customer-informed decision making.
Before introducing new processes, I needed to build trust across engineering, leadership, and the frontline employees who relied on the platform every day.
My Approach
Rather than immediately expanding functionality, I made the decision to restore trust first.
I partnered closely with Engineering to document and evaluate the existing backlog while developing a deep understanding of the platform’s technical architecture and operational workflows.
At the same time, I launched a comprehensive customer discovery initiative that included user interviews, focus groups, competitive analysis, and industry best-practice research.
The findings were revealing. Much of the existing backlog reflected what Engineering believed customers wanted rather than what customers were actually asking for.
Working collaboratively with Engineering and executive leadership, we completely reprioritized the roadmap.
Instead of adding new capabilities, we focused on rebuilding confidence by making the platform accurate, reliable, and predictable. We corrected attendance point calculations, reduced payroll issues, addressed technical debt, and stabilized the application before investing in additional functionality.
Once confidence had been restored, I established continuous customer feedback loops through user interviews, support ticket analysis, payroll monitoring, attendance audits, and customer sentiment to ensure future roadmap decisions remained grounded in evidence rather than assumptions.
Only then did we begin delivering strategic capabilities such as an HR Information System, document management with version control and electronic acknowledgements, and an internal communications platform.
Business Outcomes
35% reduction
in customer support tickets.
52% reduction
in attendance point correction requests, significantly reducing disputes and manual intervention.
23% reduction
in employee turnover, directly correlated with restoring confidence in attendance calculations and ensuring employees were treated fairly.
Established Product Management as a strategic organizational function with repeatable processes for customer discovery, prioritization, governance, and roadmap planning.
Shifted product decisions from assumption-driven development to customer-informed prioritization.
Organizational Impact
The most meaningful outcome wasn’t a product feature—it was rebuilding organizational trust.
Executives had trusted the system because they had no reason to believe the underlying data was inaccurate. Frontline employees had been telling the organization for years that the system was wrong, but their experiences weren’t reaching product decisions.
By introducing structured customer discovery and validating employee concerns with data, we rebuilt confidence on both sides. Leadership gained trust in the accuracy of the platform, and employees saw that their feedback directly influenced product direction.
Product Management became more than a delivery function—it became the bridge between customer experience, business strategy, and engineering execution.
Executive Reflection
This experience fundamentally shaped my leadership philosophy.
Organizations rarely struggle because they lack ideas. They struggle because they lack a disciplined way to understand problems, prioritize opportunities, and make decisions.
I’ve learned that sustainable product success isn’t created by shipping more features—it’s created by aligning customer insight, business strategy, technical expertise, and operational governance around a shared understanding of what matters most.
My role as a product leader is to create the environment where better decisions become inevitable, so organizations consistently build the right things for the right reasons.
Leadership Principle: Build trust before building process.
Executive Case Study 02
Rebuilding SuperPunch Around Customer Needs
Organization: Laivly
“Great product strategy begins by challenging assumptions. By replacing opinion-driven prioritization with structured customer discovery, we transformed SuperPunch from a product built around internal ideas into one shaped by the people who relied on it every day.”
The Situation
When I joined Laivly, I inherited a backlog of approximately 150 Jira items that leadership wanted prioritized for future development.
At first glance, it appeared to be a mature product backlog. In reality, most items consisted only of brief titles with little or no supporting context. Before any prioritization could begin, I partnered closely with Engineering to document each idea, understand the original intent, and build meaningful descriptions.
Once we had completed that work, I asked a simple question:
“Where did these ideas come from?”
The answer surprised me.
The backlog had been created during an internal brainstorming session where developers generated ideas they believed customers would find valuable. While well-intentioned, very little of the backlog had been validated with actual end users.
The Challenge
The challenge wasn’t prioritizing a backlog.
It was determining whether we were solving the right problems.
Rather than assuming internally generated ideas represented customer priorities, I wanted to understand how people were actually using SuperPunch and where they experienced the greatest frustration.
Only then could we make informed product decisions.
My Approach
I shifted the conversation from internal assumptions to customer evidence.
I met directly with chargehands, supervisors, and frontline agents across multiple client organizations. I observed how they used SuperPunch during their daily work, listened to customer support calls, and spent time with operational leaders responsible for payroll and attendance management.
Every conversation included three simple questions:
- What is SuperPunch’s most valuable feature?
- What could SuperPunch do better?
- If you could change one thing, what would it be?
Although the conversations produced many ideas, one issue consistently surfaced above all others.
Attendance Points.
Users had lost confidence in the system because attendance calculations were frequently inaccurate.
As reports continued to emerge, I noticed a clear pattern. Rather than dismissing isolated complaints, I partnered with Engineering to investigate the underlying business logic.
What we uncovered was far more significant than expected.
The Attendance Points engine contained flaws that incorrectly assigned or deducted points under certain conditions. Those inaccuracies affected employee attendance records and, in some situations, contributed to disciplinary action.
Perhaps most concerning, frontline leaders had become so accustomed to the problem that many routinely advised employees to ignore the system because “SuperPunch makes mistakes.”
At that moment, the priority of the product changed.
Business Outcomes
Rather than continuing with the existing roadmap, we completely reprioritized development.
We paused planned feature work and focused on restoring confidence in one of the platform’s most critical capabilities.
Working closely with Engineering, we:
- Corrected the underlying Attendance Points logic.
- Manually repaired attendance records across the platform to restore data accuracy.
- Introduced a self-service workflow that enabled team leaders to resolve attendance issues without relying on Engineering support.
The results were immediate.
Restored trust in one of the platform’s most business-critical features.
52% reduction in attendance-related correction requests.
Significantly improved confidence in attendance reporting.
Reduced manual intervention for operational leaders.
Organizational Impact
What began as a technical defect ultimately became a lesson in customer-centered product leadership.
By replacing assumption-driven prioritization with structured customer discovery, the organization stopped building features based on what we believed customers wanted and began solving the problems customers consistently identified themselves.
As confidence in Attendance Points returned, trust in the broader platform followed.
This created the foundation for future product improvements because customers once again believed their feedback mattered—and leadership had confidence that roadmap decisions reflected validated customer needs rather than internal opinion.
Executive Reflection
This experience fundamentally changed how I think about product leadership.
Good product leaders make decisions using the best information available.
Great product leaders are willing to change those decisions the moment better evidence emerges.
I’ve never viewed changing my mind as a weakness. I see it as one of the most important responsibilities of leadership. Product strategy should never be driven by ego or attachment to existing plans—it should evolve as our understanding evolves.
Once trust in Attendance Points had been restored, we were able to tackle additional customer pain points and continue rebuilding SuperPunch around real customer needs rather than internal assumptions.
One feature at a time, the platform regained the confidence of both frontline employees and organizational leaders.
Leadership Principle: Challenge assumptions. Follow evidence.
Executive Case Study O3
Launching an AI Agent Assist Platform
Organization: Laivly
“Successful AI initiatives don’t begin with technology—they begin with understanding human problems. By introducing AI where it removed friction rather than replacing people, we transformed employee support from reactive issue resolution into proactive employee engagement.”
The Situation
Laivly develops technology for 24-7 Intouch, supporting thousands of customer service representatives across global contact centres.
While the company specialized in delivering exceptional customer experiences, one internal challenge remained largely invisible: supporting its own frontline employees efficiently.
A dedicated employee support team managed a continuous stream of repetitive questions from agents across multiple client programs. Most requests were administrative rather than complex, covering topics such as workplace policies, attendance procedures, nearby amenities, and day-to-day operational guidance.
Although these inquiries were important, they consumed so much of the team’s capacity that little time remained to identify broader trends affecting employee engagement, satisfaction, or retention.
The Challenge
The opportunity wasn’t simply to introduce artificial intelligence.
It was to determine whether AI could eliminate repetitive work while improving the experience for both employees seeking support and the people providing it.
The solution needed to integrate naturally within the existing SuperPunch platform, deliver reliable information, and build trust through consistent, accurate responses.
My Approach
Rather than beginning with the technology, I began with the people.
I interviewed frontline employees alongside members of the employee support team to understand the questions they answered most frequently and identify which interactions were appropriate for automation.
Working collaboratively with the support organization, we built a structured knowledge base of validated questions and responses to establish a reliable foundation for the AI model.
To ensure we were creating a differentiated experience rather than simply replicating existing solutions, I conducted competitive research across AI assistant platforms, evaluating functionality, user experience, visual design, and implementation strategies. That research helped identify opportunities where our solution could better support both employees and the business.
From there, I defined the product scope and requirements while facilitating collaborative planning sessions across Design, Engineering, UX, Operations, and end users to ensure alignment before development began.
Rather than pursuing a broad launch, we intentionally introduced the solution through a phased pilot, allowing us to validate assumptions, incorporate user feedback, and refine the experience before wider deployment.
Business Outcomes
The initiative delivered benefits well beyond operational efficiency.
- 75% reduction in employee support contacts for routine inquiries.
- Significantly increased capacity for the employee support team to focus on higher-value work.
- Faster, more consistent answers for frontline employees.
- Improved accessibility to organizational knowledge and workplace resources.
- Successfully introduced AI into daily operations through phased adoption and continuous user validation.
Organizational Impact
The most significant outcome wasn’t automation—it was transformation.
By reducing the volume of repetitive requests, the employee support team shifted from answering routine questions to proactively improving the employee experience.
Instead of spending their days responding to administrative inquiries, they could identify emerging patterns, monitor engagement, and intervene before issues escalated.
Initiatives such as wellness check-ins, recognition programs, treat carts, and employee engagement activities became possible because the team finally had the capacity to focus on people instead of process.
The organization benefited from stronger employee engagement, lower turnover, and ultimately better client experiences delivered by a more supported workforce.
Executive Reflection
This initiative reinforced one of the most important lessons of my career.
Successful AI projects don’t begin with technology—they begin with understanding human problems.
Rather than asking, “Where can we use AI?” I ask a different question:
“Where can AI remove friction so people can focus on work that creates greater value?”
When implemented thoughtfully, AI doesn’t replace people—it amplifies their ability to contribute where empathy, judgment, creativity, and human connection matter most.
Technology creates its greatest value when it quietly removes complexity, allowing people to spend more of their time doing work that only people can do.
Leadership Principle: Technology should remove friction, not humanity. The best AI initiatives create more capacity for people to do their most meaningful work.
Executive Case Study 04
Leading Organizational Turnaround Through Operational Excellence
Organization: Fry-Day’s Restaurant & Lounge & Interlake Smoke
“Strong organizations aren’t rebuilt through quick fixes—they’re rebuilt by earning trust, creating consistency, and listening to the people they serve. By applying the same leadership principles I used in technology, we began transforming a struggling local business into an organization its employees and community could once again believe in.”
The Situation
What began as a part-time serving position quickly evolved into an unexpected leadership opportunity.
In August 2025, nearly the entire restaurant team resigned on the same day, leaving only one other employee and me. The owners asked me to step into the role of General Manager for both Fry-Day’s Restaurant & Lounge and Interlake Smoke during one of the most challenging periods in the organization’s history.
The restaurant had experienced years of decline. Customer confidence had eroded, operational consistency was lacking, and many long-time patrons had stopped coming altogether.
For me, this wasn’t simply another management position. Having worked at Fry-Day’s over several years, I cared deeply about the restaurant and understood what it had once meant to the community.
The Challenge
The immediate challenge wasn’t simply replacing staff.
It was rebuilding confidence—within the team, among customers, and throughout the community.
The organization needed stability, consistent leadership, and a clear vision for what success looked like.
My Approach
Rather than becoming overwhelmed by the scale of the challenge, I relied on the same leadership principles that had guided my career in product management.
My first priority was rebuilding the team.
Instead of hiring solely based on availability, I recruited three people I had previously worked alongside—individuals who consistently demonstrated professionalism, strong work ethic, and an instinctive commitment to exceptional customer service.
From there, we focused on creating consistency.
Every guest should receive the same experience regardless of which server greeted them or which cook prepared their meal. We established clear service expectations, standardized operational practices, committed to remaining open during all scheduled business hours, and invested in higher-quality ingredients.
At the same time, I turned to the community for guidance.
Through social media, direct conversations with guests, and ongoing feedback from residents, we continually asked one simple question:
“How can we earn your business back?”
One guiding principle influenced many of our decisions.
I often asked myself:
“What would Theresa do?”
The restaurant had flourished under a previous owner named Theresa, and rather than trying to reinvent its identity, I focused on restoring the qualities that had originally made it successful: consistency, hospitality, and genuine community connection.
Business Outcomes
Although the turnaround remains ongoing, the results have been encouraging.
Began attracting former regular customers back to the restaurant through improved service and community engagement.
Successfully rebuilt the restaurant team following the loss of nearly the entire workforce.
Restored operational consistency across both front-of-house and kitchen operations.
Re-established dependable business hours and improved product quality.
Earned multiple new five-star customer reviews within the first six months.
Organizational Impact
The most important outcome wasn’t the reviews.
It was rebuilding trust.
By consistently listening to customers, acting on their feedback, and delivering a dependable experience, the restaurant began earning back the confidence of both employees and the community.
The turnaround reinforced something I’ve seen throughout my career: regardless of industry, people respond to organizations that listen, improve continuously, and consistently deliver on their promises.
Whether the customer is using enterprise software or enjoying dinner with their family, the leadership principles remain remarkably similar.
Executive Reflection
This experience reminded me that leadership principles are transferable.
Organizations may differ in size, industry, and complexity, but the fundamentals remain the same.
High-performing organizations are built by hiring the right people, establishing clear expectations, creating consistent experiences, and continuously listening to the customers they serve.
Technology changes.
Industries change.
People don’t.
The most effective leaders understand that operational excellence is ultimately built on trust, accountability, and a relentless commitment to continuous improvement.
Leadership Principle: Operational excellence isn’t created by processes alone—it emerges when great people consistently deliver experiences customers can trust.