In contact center‑driven businesses, the COO isn’t just “running the back office” anymore. They’re the architect of how revenue, margin, and customer experience show up every day.

Three things boards should expect from a modern COO:

• A clear operating model, not just KPIs. The COO should define what “good” looks like across the value chain, make it visible in a simple system of metrics, and build an operating cadence that leaders at every level can run.
• A practical AI and automation roadmap. Not hype decks—prioritized workflows where AI, speech analytics, and automation are already changing unit economics and experience, with before/after metrics.
• A culture of accountable, empowered frontline leaders. The best COOs invest heavily in frontline leaders who understand the numbers, coach effectively, and can keep operations stable while the business scales or transforms.

This is the lens I bring to SVP/COO roles in healthcare and tech‑enabled services: board‑level clarity on the operating model, and day‑to‑day leadership in the contact centers and service teams that power the business.

Over 18 months, I led a 500‑seat healthcare contact center from flat growth and inconsistent performance to double‑digit EBITDA expansion and stronger CX.

Here’s how we did it:

• Starting point: Stagnant revenue, inconsistent service levels across sites, high overtime and attrition, limited visibility into true unit economics.
• Workforce model: Rebuilt forecasting, staffing, and scheduling using WFM discipline, reduced overtime dependence, and rebalanced onshore/offshore mix.
• AI & speech analytics: Deployed AI‑driven speech analytics and QA to identify friction points, target coaching, and streamline handle times without hurting quality.
• Funnel redesign: Simplified referral and intake workflows, tightened routing, and clarified conversion ownership to reduce leakage in the sales and scheduling funnel.
• Outcomes: Delivered double‑digit EBITDA growth, multi‑million‑dollar revenue lift, improved NPS/CSAT, reduced handle time and booking lag, and stabilized attrition.

This is the kind of work I enjoy most as an SVP/COO: turning complex, multi‑site operations into reliable, scalable growth engines.

P&L Ownership and Workforce Design: Where EBITDA Is Really Won

A lot of leaders say they “support” the P&L. Far fewer have actually carried it.

In my roles, I’ve owned P&Ls ranging up to $60M. I have owned accountability for growth, margin, and capital decisions. When you’re on the hook for the number, you stop treating workforce, operations, and tech as separate conversations. They become the same conversation.

How I think about revenue and margin

On the revenue side, I usually come back to four practical levers:

• Capacity
• Throughput
• Referral flow
• Clean billing

Margin is where most teams say they focus, but the work gets real specific, real fast:

• Staffing models and productivity (what we staff, when we staff, and what “good” looks like)
• Supply discipline and waste (the quiet killers)
• Denial prevention and plugging revenue-cycle leaks
• Capital ROI tied to removing constraints, not “nice-to-have” projects

Budgets and forecasts can’t be “last year plus $x\mathrm{\%}$x%.” I anchor planning in leading indicators and operational drivers that show up weeks earlier than the financials.

Workforce Design is a quality lever and a growth lever

Staffing isn’t just the biggest expense line. It’s the lever that determines speed, quality, customer experience, and capacity creation.

The approach that’s worked best for me looks like this:

• Scheduling templates that match capacity to demand (not gut feel)
• Fixing no-shows, documentation flow, and billing cleanliness to give time back
• Clear productivity expectations that are sustainable, not burnout math

Turnover drops when expectations are consistent and leaders are supported. I use “leadership contracts”: documented goals, decision rights, KPIs, and expectations to keep standards high and coaching real. And when it’s not working, I move quickly and cleanly.

Performance reviews that actually drive outcomes

Monthly business reviews shouldn’t be slide parades. They should answer three questions:

• What changed in our leading indicators?
• What did that do to revenue, margin, quality, and experience?
• What will we do differently in the next 30–90 days?

I also separate what we control (productivity, staffing, workflows, documentation) from what we influence (referrals, provider supply). That keeps accountability fair and makes execution better.

If you’re staring at your P&L and wondering why “operational excellence” isn’t showing up as EBITDA, let’s talk.

A new “Mike Schiano In the Queue” episode

The Alchemy of Human Energy: Beyond the Management Blind Spot with AI Flourishing Partners

1. The Management Blind Spot

In the high-velocity modern workplace, most leaders are effectively “flying blind.” Despite an unprecedented deluge of performance data, managers remain dangerously disconnected from the actual health and psychological engagement of their teams. We track what was done, but we remain oblivious to the human cost of the doing.

Diane Weaver co-founder and COO of Baryons posits a paradigm shift: treating AI not as a productivity whip, but as a “flourishing partner.” Alongside a pedigree team including CEO Mike Hruska (a veteran of Department of Defense organizational tech) and CTO Ryan Krinjek (formerly of AccuWeather), Weaver is leveraging patent-pending semantic processing to transform invisible human signals into actionable leading indicators of team vitality.

2. AI is a Cultural Accelerator (For Better or Worse)

Adding sophisticated technology to a fractured corporate culture is like pouring gasoline on a flickering flame. AI acts as a fundamental accelerator; it does not create trust, it amplifies the existing state of it. If a foundation of suspicion exists, the “black box” nature of AI turns that suspicion into organizational paranoia. Conversely, in ethical, healthy environments, AI serves as a catalyst for unprecedented transparency and growth.

Weaver emphasizes that implementation must be human-centered, recognizing that technology can never replace the human-to-human power of mimicry and mirroring.

“If there’s not trust at work in the first place, there certainly won’t be trust after you add in AI.” — Diane Weaver

3. The “Slow Down to Speed Up” Paradox

True innovation requires the courage to pause. Weaver highlights a nationwide nonprofit where the CEO took a profound strategic risk: intentionally slowing the pace of work to create the cognitive “white space” necessary for AI adoption.

Rather than mandating specific tools, leadership focused exclusively on outcomes, granting employees total autonomy to co-create their workflows. This counter-intuitive slowdown was a prerequisite for the “rapid speed up” that follows when a workforce is empowered rather than coerced. In a post-AI economy, the ability to temporarily decelerate for the sake of long-term innovation is the ultimate leadership competitive advantage.

4. The Vibe Coding Revolution: Why Voice-First Interaction Changes the Brain

We are entering the era of “vibe coding,” where the primary directive for the machine is no longer a rigid syntax, but the vocalized intent, the “vibe,”of the human user. Baryons employs a voice-first, native-language-first approach because the act of speaking engages the brain’s semantic processing differently than typing into a chatbot.

In a world of silent, remote work, the act of vocalizing purpose forces a level of mental clarity and reflection that text cannot replicate. By speaking intentions aloud, workers move from passive task-execution to active “intent-setting,” essentially using their own voice to bridge the gap between human desire and digital execution.

5. Measuring Human Energy, Not Just KPIs

As AI commoditizes routine cognitive tasks, human energy will become the most sought-after resource in the global economy. The Baryons model moves beyond “to-do boxes” to monitor “aggregate enthusiasm” vs. “vocal strain” through brief, two-minute check-ins and check-outs.

While individual conversations remain private, anonymized data feeds into manager dashboards to flag early indicators of burnout long before they manifest in attrition. This approach, currently undergoing efficacy studies with Penn State University, is rooted in the PERMA Model of flourishing:

• Positive Emotions: Tracking the frequency of genuine optimism.
• Engagement: Measuring deep immersion in one’s role.
• Relationships: Assessing the strength of the social fabric.
• Meaning: Connecting daily tasks to a larger sense of purpose.
• Accomplishment: Validating the psychological need for progress.

6. The Anti-Echo Chamber: AI as a Critical Thinker

Standard generative AI models often function as “echo chambers of affirmation,” reflexively agreeing with the user. Weaver argues that a true flourishing partner must be a “critical thinker” that challenges the user’s perspective.

Imagine a hands-free Bluetooth call during a 40-minute commute where an employee practices a high-stakes pitch. The AI doesn’t just listen; it role-plays, identifies blind spots, and helps the user “see around corners.” This transforms a commute into a high-level coaching session, flexing the user’s critical thinking muscles rather than letting them atrophy.

7. Democratizing Executive Coaching

Historically, high-level coaching was a luxury bottlenecked at the C-suite. We are now seeing a radical democratization of professional development. By providing executive-level reflection tools to every employee regardless of rank organizations can trigger a bottom-up transformation. When every frontline worker has the tools to define and pursue their own flourishing, the entire organizational structure evolves from a rigid hierarchy into a living, responsive ecosystem.

8. The Augmented Human of 2026

The “Augmented Human” of 2026 is not a science-fiction concept; it is a strategic necessity. The future of work belongs to those who view individual transformation as the primary fuel for organizational success.

A final thought for the visionary leader: In a world where AI can manage the tasks, how are you intentionally cultivating the energy required for your team to truly flourish?