Consultant: Scott Hagberg

 

Client Profile

 

A large entity in the medical sector, recognized for its extensive operations involving patients, providers, and payors. The organization is structured to facilitate seamless interactions and services among these key entities, ensuring efficient and effective healthcare delivery.

 

The Challenge

The client was locked in an operational paradox: any increase in revenue required proportional increases in staffing and technology spend. This “infinite loop” severely restricted scalable growth and drained profit margins. Existing technologies had reached their performance ceiling, and previous attempts at digital transformation had resulted in tool fragmentation, siloed adoption, and minimal ROI​.

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Adding complexity, multiple business units had trialed AI tools independently—without governance or integration—resulting in redundancy, inefficiency, and inflated license spend. Leaders lacked clarity on where to deploy AI effectively or how to extract value from it, and employees were overwhelmed with full plates, limiting their bandwidth to explore or adopt new tools​.

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The client’s internal teams lacked the time and expertise to build a unified AI roadmap. Scott Hagberg, acting as both consultant and internal change agent, took ownership of learning and translating AI capabilities into real-world business value. With deep technical literacy and leadership trust, he became the de facto AI strategist, bridging the gap between executive ambition and frontline execution​.

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The Strategy

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Scott implemented a multi-layered, human-centered transformation model, customized to fit each division’s pace, structure, and operational rhythm:

Proprietary Framework: The ONS Methodology™

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Scott applied his own ONS consulting framework—a proprietary model built on the principles of Ontology, Narrative, and Strategy. This method helps organizations move from fragmented AI adoption to cohesive, scalable implementation.

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• Ontology: Define the true nature of operational problems by separating symptoms from root causes. This prevents teams from automating inefficiencies.
   

• Narrative: Create shared language around AI’s purpose and benefits, making it easier for stakeholders to visualize value.
   

• Strategy: Design adaptable, low-risk deployment plans tailored to each business unit’s pace and maturity level​.

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Root-Cause First, Tech Second

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Rather than pitching tools, Scott first identified core business problems, separating symptoms from root causes. Once the true bottlenecks were uncovered, he reframed AI not as a “cool new tool” but as a targeted solution to specific pain points​.

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Contextual Frameworks by Business Unit

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• Six Sigma was applied in high-volume operations (e.g. call centers) to shave seconds off transactions and drive measurable efficiencies.
   

• Total Quality Management (TQM) was used in specialized, low-volume environments (like complex rehab) to ensure precision and quality in every interaction​.
   

• Agile + Swimlane Execution: Scott worked in parallel workstreams, targeting “quick wins” in receptive teams while waiting for strategic timing in more constrained departments​.
   

Top-Down Cascade Model

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Recognizing that executive time is the most expensive, Scott deployed AI first at the leadership level. Freeing even 2 hours per week from an executive’s schedule generated cascading benefits down the org chart and built early momentum​.

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Change Management as Culture Design

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Instead of enforcing change, Scott allowed leaders to become internal champions by experiencing the ROI firsthand. Once they recognized personal value, they evangelized adoption organically. The transformation felt like evolution, not disruption​.

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Execution & Transformation

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• Key Insight: The primary bottleneck was no longer the technology—it was the humans. Employees were hesitant not because tools were difficult, but because they couldn’t conceive the possibility that AI could relieve their workload.
   

• Scott shifted from tech delivery to human enablement, breaking AI adoption down to what each person could see, hear, and feel. This reframing unlocked adoption across departments that previously resisted innovation​.
   

• Strategic Structuring: The roadmap wasn’t rigid—it adapted to each division’s active projects and resource availability. By working in agile lanes and meeting teams where they were, adoption felt natural and intuitive​.
   

Results & Measurable Impact

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• Time Efficiency: On average, 8 hours/month were saved per employee. With a baseline $65K/year salary, even 2 hours saved/month covered the cost of AI deployment per seat—making the ROI break-even or better from month one​.
   

• Record-Breaking Growth: While maintaining the lowest hiring rate in years, the company achieved record revenue.
   

• Tool Consolidation: Eliminated redundant licenses and fragmented adoption—aligning AI with the corporate architecture and avoiding new risk or spend​.
   

• Cultural Shift: Adoption rates were as high as 90–95% when AI tools were positioned as solutions to capacity pain, not tech for tech’s sake. Employees welcomed relief, not another system to learn​.
   

Conclusion

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This transformation wasn’t about implementing AI—it was about operational freedom. By approaching technology as a people-first enabler and aligning deployments with real-world friction, Scott didn’t just modernize operations—he rewired the organization’s ability to scale without breaking.

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VAI Consulting’s approach exemplifies what modern CFOs, CIOs, and CTOs are seeking: results without bloat, adoption without friction, and innovation that pays for itself.