Data, AI & Technology Leader for Industrial Manufacturing
I build and run the data, AI, and technology stack, then use it to automate the work that slows a business down.
25+ years across professional and military leadership, enterprise technology, and management consulting. Fortune 500 scale at McKinsey; hands-on ownership at industrial companies in Wisconsin and Illinois.
- Teams built and led
- 5-100+ people
- Impact Realized
- $22M+
- Enterprise Scale Governed
- $400M-$30B
- Industries Advised
- 6+
One leader for the data, the systems, and the team
I build and run data, AI, and technology functions, then use them to automate the manual work slowing a business down. At McKinsey & Company, I own platform operations, data governance, and engineering delivery for a 100K+ institution data platform, and I build the AI agents and automated workflows that run on top of it.
Before that, as a Director and Senior Manager, I owned data governance, BI, and core business systems: platform vendor management, budget, release cycles, and a hands-on analyst team. Most of that was inside industrial and manufacturing environments (Johnson Controls/Clarios, IEWC, Navistar), including two years partnering directly with plant maintenance teams on the shop floor.
I also spent 24 years in the Army National Guard, including two combat deployments, and commanded 106 soldiers.
What's next: a company small enough that one leader can own the data, the systems, and the team, and turn them into results a CFO can see.
71% to 96%
Data reliability raised in 8 months
8–12 wks to 2 wks
Fastest AI data-foundation build
70%
Analyst research time cut by AI agent
5
Cloud, data & AI certifications since 2022
Built, run, and measured
Six things I have owned personally. Each pairs the scale I have worked at with the scale I actually operate at: the team, the budget, the days saved.
Owned hiring, coaching, and a $1.5M+ annual budget. Personally owned platform operations and vendor management for the BI platform (Qlik, cloud-hosted) and the product master data platform (Stibo STEP), including cost, patch and release cycles, and enhancement roadmaps. A 3-person analyst team under me served as the business's first line of technical support for BI and data issues, and I took help desk calls myself when needed.
- 7-person team
- $1.5M+ budget
- 2 platforms owned end to end
At IEWC, owned the master data and integration workstream (customer data plus the PIM product master) on a Salesforce CPQ implementation that cut quote turnaround from 3 days to 6 hours. At McKinsey, identified and led an agentic automation of a fully manual, Excel- and email-driven onboarding workflow supporting 145+ client communities: cut time to activation 38% (58 to 36 days) and triage effort 94% (90 to 5 minutes per request).
- 3 days to 6 hours
- 38% faster activation
- 94% less triage effort
For two years at Johnson Controls, owned indirect-materials master data governance and worked hand in hand with plant maintenance and PMO teams. Led the data migration into a new plant maintenance system with data quality controls built in at the point of entry. Replaced an informal, plant-to-plant phone network for locating spare equipment ("does plant A have this in stock?") with real-time, cross-plant inventory visibility, so plants could transfer high-cost spares instead of buying duplicates.
- 2 years on the shop floor
- Multi-plant inventory visibility
At a $6B+ energy company, decomposed data and AI requirements into a domain-driven framework that included the data products behind a near-real-time commodity pricing optimization model. The resulting strategy secured funding for a $300M+ project portfolio and cut data discovery time 62%.
- $300M+ portfolio funded
- 62% faster data discovery
Architecture lead for the semantic layer inside an AI research agent on Snowflake Intelligence (wrote the semantic model and SQL myself). Built an AI agent with Cursor, Claude Code, and MCP integrations that automated a manual data-verification workflow: each record is auto-classified as verified, an issue with a recommended fix, or low-confidence and routed to an analyst, cutting a multi-day review to a few hours. Human-in-the-loop review and governed data access are built in from day one.
- Multi-day review to a few hours
- Daily production use
Designed the governance operating model and target-state data organization, presented it to the COO and CFO, and it became the structure the firm adopted and hired against. Foundations first: this is the groundwork an early-stage data program needs before AI can be trusted.
- Operating model adopted and hired against
- Presented to COO and CFO
Where the work was done
Senior Data Strategy & AI Consultant (Data Platform, AI Enablement & Automation Lead)
McKinsey & Company (formerly Caserta Concepts)
Selected for McKinsey's Internal Data & AI Leadership Rotation to lead automation, AI enablement, and data governance for the firm's 100K+ institution client master data platform. Led an agentic automation of a fully manual onboarding workflow supporting 145+ client communities, cutting activation time 38% and triage effort 94%, and serve as architecture lead for the semantic layer inside an AI research agent now in daily production use. On the client-facing side, advised $3.5B to $30B enterprises across financial services, energy, mining, agriculture, and consumer goods on data and AI strategy, delivering results including an $8M revenue uplift, $6.5M in unlocked EBITDA, and a $7.6M productivity gain.
Director, Data Governance & Business Intelligence
IEWC (Industrial Electric Wire & Cable) · New Berlin, WI
Led a 7-person team spanning BI, marketing, e-commerce, and data governance, owning hiring, coaching, and a $1.5M+ annual budget, including vendor management for the company's Qlik BI and Stibo STEP PIM platforms. Directed marketing and e-commerce strategy end to end, growing digital revenue 12%, and improved the data governance framework to resolve long-standing product master data issues, saving $850K a year. Owned the master data and integration workstream on a redesigned SAP-to-Salesforce CPQ pipeline that cut quote generation from 3 days to 6 hours.
Senior Manager, Data Governance & Analytics (2018 to 2020); Manager, Master Data Management & BI (2014 to 2018)
Johnson Controls, Inc. / Clarios, LLC · Glendale, WI
Owned indirect-materials master data governance for two years, partnering directly with plant maintenance teams across multiple manufacturing facilities and leading the migration to a new plant maintenance system with data quality controls built in at the point of entry. Managed domain data stewards, master data analysts, and a Manager of MDM, and led the global implementation of SAP ERP Master Data Governance, standing up the organization's first data governance function and taking data quality from unmeasured to 98%. Also navigated a corporate divestiture while managing a $1.2M budget, cutting costs 18% without compromising quality or compliance.
Earlier Career
Navistar, AAIS, Metavante/FIS, Discover Financial, Sikich
Progressed from technology consulting in banking and payments (Metavante/FIS, Discover Financial, Sikich) into software engineering and business analysis, including four years as a Business Analyst and Team Lead at Navistar, a commercial truck manufacturer, and five years as a Senior Software Engineer and Team Lead at the American Association of Insurance Services.
Commander / Major
Army National Guard
24 years of progressive military leadership in the Army National Guard, including two combat deployments to Iraq and Afghanistan. Commanded a 106-soldier Cavalry Reconnaissance Troop and a 28-soldier mobile public affairs unit, and was awarded the Bronze Star Medal.
Platforms & tools
Snowflake, Databricks, Power BI, Qlik, AWS, AWS DMS, Redshift, Azure, SAP ERP, SAP MDG, Oracle, Oracle EBS, Salesforce, Stibo PIM, Oracle PIM, Cursor, Claude Code, OpenAI, Codex, Alation, Collibra, Castor, DataEdo
Certifications & Coursework
- AWS Certified Solutions Architect Associate (2022)
- SnowPro Core (2023)
- Databricks Foundations & Data Engineering (2025)
- Generative AI for Leaders, Vanderbilt University (2025)
- Responsible Generative AI Specialization, University of Michigan (2025)
Education
- MBA, Management Information Systems, University of Illinois Chicago
- BA, University of Wisconsin-Whitewater
Operating principles
These are the patterns behind the work above. They are what I would bring to a mid-market manufacturer early in its data and AI journey, with an ERP program in flight and a CFO who wants results, not a strategy deck.
- 01
Foundations before AI.
The first job at an early-stage data organization is data quality, master data, and a governed warehouse. AI that runs on bad data produces confident nonsense. I have built this foundation from zero twice (a $10B+ institution and Johnson Controls' first data governance function) and inside an ERP program (SAP MDG at Johnson Controls).
- 02
Automation starts with the workflow, not the tool.
The onboarding automation, the CPQ integration, and the verification agent all started the same way: stakeholder workflow discovery, then a written spec, then a build with human-in-the-loop exceptions. It is the same pattern for AR cash application, order processing, and headcount reporting.
- 03
Hands-on at the right altitude.
I write the SQL for a semantic layer, answer the help desk when it is needed, walk the plant floor with maintenance teams, and still present investment cases to a CFO. A smaller company needs one person who can do all four.
- 04
Working with vendors you don't control.
I owned the Qlik and Stibo STEP vendor relationships at IEWC and worked inside a bespoke industry platform at a financial services client whose roadmap did not always serve its customers. I get results inside constraints rather than around them.
- 05
Leading people through change.
Military command of 106 soldiers - two combat deployments, cross-functional groups of 10 to 15, and a focus on coaching and developing team members through 360 degree feedback. I plan for skeptical, tenured teams and earn trust by delivering.
Writing
Practical notes on data, automation, and leading teams. No buzzwords.
Beyond Work
What keeps me moving when I'm not solving data problems
Cycling
Road cycling and gravel riding keep me balanced. Covering miles under your own power clears the mind and builds resilience.
Sports Fishing
Time on the water is time well spent. Whether fly fishing a stream or chasing bass, it is where I recharge and find perspective.
Coaching Baseball
Helping young athletes develop their skills and love of the game. Leadership is not just in the plant or the boardroom; it is on the diamond too.
The best ideas come when you step away from the screen.
Get in Touch
If you run a manufacturer and need one leader to own the data, the systems, and the team, I would like to talk. Questions about automation, AI, or building a data function from scratch are welcome too.