Sentinel Matrix, by LEDR, is pioneering a real-time, distributed surveillance and control platform to ensure integrity and compliance across complex ecosystems. The solution continuously monitors diverse information sources, ensuring regulatory standards and security protocols are met, maximizing trust and operational efficiency.

LEDR was founded to tackle the challenges of managing complex systems and overwhelming data, drawing from National Security and technological innovation.In the late 1990s, as the intelligence community faced an explosion of data, shifting from scarcity to overload, LEDR’s co-founders developed advanced modeling techniques to identify system vulnerabilities in real time. Traditional databases couldn’t scale to handle this volume, prompting new approaches that integrated diverse data, applied graph-based analytics, and enabled efficient predictive analysis.At Microsoft Xbox, we encountered similar challenges using agent-based modeling to predict player behavior. While effective, this approach became costly and complex as the system grew, highlighting the limitations of traditional data management.Initially focused on People Analytics, LEDR evolved by combining intelligence community methodologies with agent-based modeling to create the industry-agnostic Knowledge Orchestration hypergraph platform. This platform analyzes complex systems without centralizing data, enabling seamless scalability and real-time monitoring of critical infrastructure while ensuring compliance and integrity.Today, LEDR leads in real-time, distributed monitoring and control of complex ecosystems. Our platform continuously integrates diverse data sources to maintain regulatory standards and security protocols, optimizing operational efficiency. By orchestrating knowledge through interconnected graph structures—our "Big Ass Graph" (BAG)—LEDR turns data into actionable insights, empowering organizations to make real-time, impactful decisions in a data-driven world.

Pioneered a groundbreaking application of agent-based modeling (ABM) to forecast consumer behavior in Microsoft’s entertainment portfolio, dramatically enhancing market prediction accuracy. Partnered with finance, strategy, M&A, product planning, and marketing teams to develop targeted, consumer-driven strategic recommendations.Led advanced consumer segmentation across Microsoft’s entertainment businesses, leveraging deep customer insights to reshape innovation strategy, market forecasting, and content development. Designed and implemented a program to evaluate product concepts from the consumer perspective, standardizing predictive metrics and reducing annual research costs by 50%.

Oversaw Cisco’s strategy, acquisitions, and investments in Unified Communications and Collaboration (UCC), partnering with VPs and GMs to expand Cisco’s collaboration portfolio. Early-stage strategic investments include: Xobni (acquired by Yahoo!) and RingCentral (IPO’d), aligning Cisco with emerging trends in communication technology.Co-led Cisco’s first non-U.S. public acquisition of $3.3B for Tandberg ASA in Norway, advocating for a bolder move to capture the larger company. This decision resulted in one of Cisco’s highest ROI acquisition to date.

Earned multiple fast-track promotions over the course of 2 years while being repeatedly recognized in the top 5% of employees each year. Represented Microsoft as a spokesperson and frequent speaker at industry events like NxTComm and TelcoTV.Developed a groundbreaking framework using Monte Carlo simulations to objectively estimate SLA risk for Microsoft, providing clear financial impact projections for sales and finance teams. This innovative approach reshaped the company's stance on SLAs.

Took on product leadership of $1.7B consumer wire-line portfolio, focusing on pricing, marketing, and brand positioning. Oversaw 12 direct reports (senior managers/managers), an operating annual expense budget of C$4M, and a P&L of C$550M.Led development of a customer segmentation framework and predictive churn model using Monte Carlo simulations, creating targeted promotions that helped Telus mitigate market declines. Achieved outcomes over 300% better than all other North American telecoms.

Before data science became mainstream, and when data was often delivered on CD-ROMs, I was part of a pioneering team at Mercer Management Consulting that developed Interactive Strategy Models. These were among the earliest commercial uses of strategic and operational simulation models, helping global airline, logistics, and telecommunications clients make informed decisions. Using VBA, we built Monte Carlo simulations to predict potential outcomes of various strategic choices, providing clients with powerful foresight and decision-making tools.

I specialized in applying Peter Senge’s Systems Thinking methodology to help global clients drive large-scale organizational change. This approach to understanding complex systems has since become the foundation of my problem-solving strategy.