Two ways to work together.

Employee-driven performance improvement. Rather than delivering a report and leaving, the program stands up cross-functional Tiger Teams inside your organization, gives them a structured method, and coaches them as they run continuous improvement on the problems that matter most: revenue, cost, quality, throughput, safety, and customer experience.

The teams build the capability as they work, so the improvement continues after the engagement ends. The goal is not a set of findings you receive. It is a way of working your organization owns.

Owners and executive teams across industries, from healthcare and manufacturing to professional services, who want measurable performance improvement and the internal capability to sustain it. The program works best when six to eight cross-functional people can participate, giving the Tiger Teams the range of perspective the method depends on.

• Forty years of performance improvement work, from the profit improvement methodology team at Accenture through American Healthcare Solutions
• The Tiger Team structure, adapted from NASA, for empowered cross-functional problem solving
• Six major hospital financial turnarounds, and quality and patient safety gains across two hundred hospitals, using the underlying methodology
• Coaching that builds internal capability rather than dependence on an outside consultant

Engagements begin with a Test Drive, a working session that applies the method to one of your real problems. The Test Drive fee is credited toward the program if you continue. The full program runs twelve months, long enough for the Tiger Teams to complete cycles, show results, and internalize the method.

AI strategy work where the question is no longer whether to use AI but how to deploy it without breaking the things you cannot afford to break. Workflows where errors are expensive, the cost of getting it wrong is paid in patient harm, financial loss, regulatory exposure, or reputation, and the architectural decisions matter more than the model decisions.

Specific engagement types include AI strategy diagnostics for executive teams, AI infrastructure architecture review, decision-system design for high-stakes workflows, vendor and platform evaluation, AI governance framework design, and full implementation oversight where the work warrants it.

The common thread is that the questions sit above the level of the model and the platform. They are about where AI fits in the organization, what governance the deployment requires, and which classes of decision the AI can be trusted with versus which require human judgment that the AI is supporting rather than replacing.

Senior executives at organizations across healthcare, financial services, technology, retail, transportation, energy, and other industries facing high-stakes AI decisions. Growth-stage startups through publicly traded enterprises. Typically the conversation involves a CEO, CTO, CIO, Chief AI Officer, or board member directly. The organizations are at the stage where AI has moved from pilot to strategic question, and where the cost of getting the architecture wrong is large enough to justify a senior advisor.

• Forty years of consulting and senior executive work across healthcare, financial services, retail, transportation, energy, and technology in high-stakes environments
• Two founder exits in healthcare technology: Total Benchmark to Kaufman Hall and Madison Dearborn Partners; Vizient business intelligence into IBM Watson Health
• Founder of OrbisFramework, a production AI infrastructure platform that operationalizes the alignment-based and weakest-link decision architecture for enterprise workflows
• Direct authorship of the strategic thesis (The High Stakes Decision) used to frame these conversations
• Cross-industry pattern recognition across healthcare, payers, retail, transportation, and energy
• An active research program at the Daniels College of Business advancing Petersen's Theory of Innovation Alignment
• The capacity to translate between technical specialists and business leaders in both directions

Engagements typically begin with a discovery conversation followed by a scoped engagement proposal. Most are advisory in nature. Some extend into longer relationships, and a small set become recurring fractional advisory roles.