Rick Young · Data & AI executive · rick@rickyoung.me · linkedin.com/in/rickyoungdataleader · rickyoung.me

Impact

Result first. Then the situation, and what I did.

Client names are withheld under confidentiality agreements. Descriptors and results are stated as agreed with each client; where a figure cannot be shared, I describe the decision or asset the work produced.

Client engagements

Large U.S. insurance provider

Insurance · Sikich

Agentic AILegacy modernizationBusiness caseOutcome-based

Funding AI modernization at a large U.S. insurer

$15M program funded, $5M in year onein year one: change failure rate and mean time to recovery down 30%, time to value against the feature backlog cut in half
Situation
Core legacy applications were slowing the business, and AI ambitions had no funded path to production.
What I did
Led a $150k assessment, strategy, and roadmap engagement that laid out the benefits of AI and tied every initiative to a business outcome. Defined a modernization approach built on AI-driven code refactoring and optimization, AI-enabled development-lifecycle practices, and agentic process redesign. Built the business case executives approved.
Result
The company approved a $5M first-year investment, a further $5M in year two, and a DevOps managed service after that: $15M over three years. In the first year, change failure rate and mean time to recovery fell 30% and time to value against the feature backlog was cut in half.

Five-plant discrete manufacturer

Manufacturing · Sikich

AI in productionAnalytics platformData integration

AI across five plants: reporting time down 93%, $12M a year saved

$12M a year saved; reporting time down 93%reporting cut from 15 hours to one a week; operational efficiency up 24%; capacity utilization up 18%
Situation
Five production facilities ran different MES, ERP, and quality systems, with inconsistent reporting and metrics across locations and decisions delayed across the network.
What I did
Led the team that built an AI-powered analytics platform unifying data across the five facilities: automated data integration, standardization, and cleansing, and real-time dashboards with predictive insights and alerts.
Result
Reporting time fell 93%, from 15 hours to one a week; operational efficiency rose 24% and capacity utilization 18%; the company saves $12M a year.

World's largest credit card and digital payments technology company

Payments · North Highland

Data & AI governanceData marketplaceAI-ready data

Governance that accelerates AI at the world's largest payments technology company

Governance adopted, marketplace livethree business units (authorization, fraud, and analytics), 300 certified data assets, time to value for new analytics products cut from weeks to days
Situation
Enterprise data was abundant but hard to find, trust, and reuse, which slowed AI innovation across a global business.
What I did
Led the enterprise Data & AI governance strategy and roadmap. Led development of an enterprise data marketplace (data catalog) to make data easier to find, trust, and reuse. Positioned governance as the enabler of faster, safer AI experimentation.
Result
The governance model was adopted across three key business units (authorization, fraud, and analytics), the marketplace holds 300 certified data assets, and time to value for new analytics products fell from weeks to days.

Clinical-stage biotechnology company

Life sciences · Sikich

Agentic AIOperating modelContext layerGovernance council

From strategy to a working agent at a clinical-stage biotech

Operating model, council, platform, and a production agentthe authoring agent removes 42 hours a week of manual data collection, preparation, and visualization across three project teams; data-quality agents in pilot
Situation
Leadership wanted AI to move faster than a science-driven organization's data foundations allowed.
What I did
Stood up an AI innovation operating model and a Data & AI governance council. Architected a single-source-of-truth data platform with a full data catalog as the context layer for agentic development. Built an authoring agent that automates data collection, preparation, and visualization for project status reporting; data-quality agents followed into pilot.
Result
One engagement delivered the operating model, the governance body, the platform architecture, and a production agent that removes 42 hours a week of manual data collection, preparation, and visualization across three project teams, with data-quality agents now in pilot.

Custom equipment manufacturer

Manufacturing · Sikich

AI in productionProcess redesignERP and MES integration

From engineering specifications to a production schedule in four hours, not 72

Planning from 72 hours to 4; $18M+ in added revenue95% on-time delivery; $18M+ in additional annual revenue
Situation
Custom engineering specifications were interpreted by hand, sales, engineering, and production communicated through a fragmented process, and long lead times meant missed delivery commitments.
What I did
Led the team that implemented an AI solution to interpret complex engineering specifications, synchronized it with the existing ERP and MES systems, and streamlined work-order creation and production scheduling.
Result
Planning time fell from 72 hours to 4, on-time delivery reached 95%, and the company added $18M+ in annual revenue.

Fortune 500 financial hardware, software, and services company

Financial technology · 3sage Consulting

Enterprise data strategyCDAO operating modelAnalytics CoE

Designing the Chief Data & Analytics Officer organization for a Fortune 500 company

$25M in realized valuethe company hired its first CDAO, stood up the matrixed organization, and funded the $15M program; the analytics center of excellence and single source of truth eliminated $10M a year of repetitive data preparation
Situation
The company needed a global enterprise data and analytics strategy, and an organization accountable for delivering it.
What I did
Served as engagement partner for the Data-Driven Transformation program. Worked with business-segment executives to identify top- and bottom-line growth from analytics. Created the enterprise data strategy (platform, an analytics center of excellence, master data, governance), designed the CDAO organization and operating model, took the strategy and organization design to the board, and established the enterprise data platform.
Result
The company hired its first Chief Data & Analytics Officer, stood up the matrixed organization, and funded the $15M program; the analytics center of excellence and the single source of truth delivered $25M in realized value, including $10M a year of repetitive data preparation eliminated.

Metals fabrication manufacturer with twelve facilities

Manufacturing · Sikich

AI opportunity assessmentUse-case prioritizationROI

$45M of AI value identified, and $2.1M of misallocated spend flagged

$45M in annual return across the top five AI opportunities$2.1M of misallocated resources identified by flagging three high-risk initiatives; leadership aligned on the AI strategy
Situation
Twelve facilities, diverse production lines, limited in-house AI expertise, and several stalled digital transformation initiatives left leadership unsure which AI investments to prioritize.
What I did
Led the AI opportunity assessment: analyzed operations and data infrastructure across all twelve facilities, evaluated data quality, prioritized AI use cases by impact, and built implementation roadmaps with ROI projections.
Result
The assessment defined $45M in annual return across the top five AI opportunities, identified $2.1M of misallocated resources by flagging three high-risk initiatives, and aligned leadership on the AI strategy and its ROI.

Regulated chemical manufacturer

Chemicals · Sikich

Responsible AIISO 42001Copilot guardrailsAI adoption

From restricting AI to deploying it safely at a regulated chemical manufacturer

Controlled AI deployment in place of a blanket restrictionan ISO 42001–aligned framework with guardrails and acceptable-use standards for Copilot and broader AI adoption
Situation
AI tools were broadly restricted over data security, regulatory, and intellectual-property risk, while Microsoft Copilot was being introduced enterprise-wide without a governance framework, leaving adoption inconsistent in a highly regulated chemical environment.
What I did
Led the development and implementation of an AI governance and risk management framework aligned to ISO 42001 and to the enterprise risk, cybersecurity, and regulatory requirements. Defined policies, guardrails, and acceptable-use standards for Copilot and broader AI adoption, and embedded risk-based controls, data protections, and monitoring.
Result
The company moved from restricting AI to deploying it under control: an ISO 42001–aligned framework with risk-based controls, data protections, monitoring, and clear guardrails for Copilot and broader AI adoption.

Am Law 100 law firm

Legal · Sikich

Enterprise Data & AI strategyMicrosoft FabricPower BIAI models

An Am Law 100 law firm’s first enterprise data platform, and AI for its lawyers

Strategy, platform, and AI models for practicing lawyersthe firm’s first enterprise data platform, on Microsoft Fabric, with new Power BI analytics and AI models for its subrogation practice
Situation
The firm had no enterprise data platform on which to build analytics or AI.
What I did
Led the team that developed the firm’s enterprise Data & AI strategy, then architected and built its first enterprise data platform on Microsoft Fabric (Azure), created new advanced analytics in Power BI, and developed new AI models for the lawyers in its subrogation practice.
Result
The firm has its first enterprise data platform, on Microsoft Fabric, with new advanced analytics in Power BI and AI models built for the lawyers in its subrogation practice.

Nation's largest cooperative bank

Financial services · North Highland

Entity resolutionMaster dataMachine learningData governance

Machine-learning entity resolution at the nation's largest cooperative bank

A single source of truth for customer information1M customer and 10M contact records unified across four systems; 90% auto-match rate; manual stewardship effort down 45%
Situation
Customer information was fragmented across Salesforce and three core lending and leasing platforms, with no single source of truth.
What I did
Led the MDM and data governance strategy. Architected and delivered a commercial MDM solution integrating the core systems. Introduced machine learning models to automate data quality, matching, and hierarchy management.
Result
1M customer and 10M contact records unified across Salesforce and three core lending and leasing platforms, with a 90% auto-match rate and manual stewardship effort down 45%.

Leading manufacturer and distributor of maintenance consumables and automotive aftermarket products

Manufacturing · Sikich

Master data managementData governanceManufacturing

One customer master across four ERPs at a leading manufacturer and distributor

Roadmap funded; governance operating model livethe customer data governance operating model went live in 2026; consolidation of the four ERPs onto the single customer master is under way
Situation
Customer data lived in four legacy ERPs, with no single view of the customer for pricing, risk analysis, or analytics.
What I did
Created the customer master data management strategy and implementation roadmap: one customer master integrating the four ERPs, and a customer data governance operating model to keep it trusted.
Result
The roadmap was funded, the customer data governance operating model went live in 2026, and consolidation of the four ERPs onto the single customer master is under way.

Top global commercial maltster

Manufacturing · North Highland

Enterprise data strategyDemand forecastingSupply chain

Demand forecasting that cut grain waste 25% at a global maltster

Grain waste down 25%, rail car overages down 20%after demand forecasting and the supply chain insights product went live
Situation
The company wanted a data-driven culture and had no enterprise data strategy to build it on; waste in raw material and rail logistics was a standing cost.
What I did
Developed the enterprise data strategy and ran the Insights Framework to identify the analytics that would move operations. Developed predictive models for demand forecasting and supply-chain optimization and released a supply chain insights product.
Result
Raw material (grain) waste fell 25% and rail car overages fell 20% after demand forecasting and the supply chain insights product went live.

Nation's largest home title insurance company

Insurance · ThreeBridge Solutions

Enterprise data strategySnowflakeMaster data management

A Snowflake platform in six months for the nation's largest home title insurer

Snowflake platform live in six months; MDM live in ninereplacing three warehouses and dozens of spreadmarts; customer create-and-maintain centralized across four core platforms
Situation
Three separate data warehouses and dozens of spreadmarts, with customer records created and maintained in four core platforms.
What I did
Led the enterprise data transformation: enterprise data strategy and roadmap, data governance strategy, MDM strategy with vendor evaluation and selection, and the architecture of a new Snowflake enterprise data platform.
Result
The Snowflake platform went live in six months, replacing three separate data warehouses and dozens of spreadmarts; the MDM platform went live in nine, centralizing customer creation and maintenance across four core platforms.

Fortune 100 health insurance payer

Healthcare · 3sage Consulting

Data governancePII and PHIData catalog

Governing a Fortune 100 health payer's first data lake

A fully governed data lakePII and PHI governance across about 20 source systems; the Collibra catalog adopted by roughly 100 analysts
Situation
The payer was building an enterprise data lake that would hold highly private information (PII, PHI) under regulatory scrutiny, and engaged us to govern it as a core part of its big-data strategy.
What I did
Led the governance strategy and its execution with the client's architects and compliance officers; developed the data cataloging architecture and led the tool selection.
Result
A fully governed enterprise data lake, with PII and PHI governance across about 20 source systems and a Collibra data catalog adopted by roughly 100 analysts.

Large credit bureau

Information services · ThreeBridge Solutions

Talent developmentAI engineeringGoogle Cloud

Building the AI talent pipeline at a large credit bureau

Twelve engineers and scientists placed within twelve monthstwo cohorts of six, feeding large-scale AI development programs on Google Cloud Platform
Situation
Demand for AI analysts and engineers was outrunning the client's ability to hire and onboard them for large-scale AI programs on Google Cloud Platform.
What I did
Created and led a future-leader development program aligning junior talent to the growing AI demand. Created the talent pipeline and training program for onboarding data engineers and data scientists.
Result
Two cohorts of six; twelve data engineers and data scientists placed into large-scale AI development programs on Google Cloud Platform within twelve months.

Internet automotive classified solutions provider

Digital marketplaces · 3sage Consulting

Master data managementBusiness caseIdentity resolution

350% ROI from a customer master at an automotive classifieds provider

350% ROI after year twoa single, transactional customer master for the dealer base
Situation
Leadership had no consistent, holistic view of its customers, the automotive dealers, across the business.
What I did
Introduced master data management as the approach, built the business case, ran vendor assessment and selection, and implemented a fully transactional customer MDM solution with identity resolution, data quality rules, and governance processes.
Result
A single, transactional customer master for the dealer base, returning 350% on the investment after year two.

Practice building

Two things I built from zero.

Sikich, 2023–present

Practice buildingOfferingsGo-to-marketTalent

Building a Data & AI practice from zero at a national firm

$3M in the second full year, on track for $5M+built from a standing start, with a team of nearly twenty and Fortune 1000 accounts in manufacturing, insurance, and financial services
Situation
Sikich had no data practice when I joined in September 2023.
What I did
I founded it: hired the team from two consultants to nearly twenty, built eight named offerings from Data & AI Strategy to Agentic Process Redesign (most fixed-fee, one priced on the outcome), stood up the AI Solutions Studio inside the practice, set the go-to-market by vertical (manufacturing, insurance, financial services), and wrote the delivery frameworks. Delivery is platform-agnostic (Microsoft Fabric and Azure, Databricks, Snowflake), inside a top-1% Microsoft Inner Circle partner where Dynamics 365 Finance & Supply Chain Management is the largest platform we work with; we choose the platform that fits each client. I personally originated $7M+ of the work and led the Fortune 1000 programs that followed.
Result
A $3M practice in its second full year, on track for $5M+ in its third, with a team of nearly twenty and Fortune 1000 accounts across manufacturing, insurance, and financial services.

3sage Consulting, 2009–2018

FounderP&LAcquisition

Founding, growing, and selling a data consultancy

Acquired by ThreeBridge Solutionswhich bought the firm to enter Atlanta and to add data, analytics, and AI consulting to its portfolio; I then led the combined practice as Partner
Situation
Enterprise data management was mostly technology projects: strategy missing, governance bolted on, platforms business leaders could not use.
What I did
I founded 3sage Consulting in Atlanta to do it the way I thought it should be done: strategy first, governance built in, platforms business leaders could actually use. For nine years I owned the P&L, the client relationships, and the delivery, growing the firm to 24 consultants, $8–10M in revenue, and eight enterprise clients, most of them Fortune 1000.
Result
Acquired by ThreeBridge Solutions, which bought the firm to enter Atlanta and to add data, analytics, and AI consulting to its portfolio; I then led the combined practice as Partner.