Founder-led & venture-backed
Companies turning product and data promise into repeatable growth, stronger commercial systems and operating scale.
Operator-led advisory & embedded implementation
Operating judgment for
consequential decisions.
Based in New York and working globally, Working Theory is a boutique, principal-led firm providing white-glove advisory and embedded implementation to CEOs, executive teams, boards and investors. Drawing on 20+ years of operating experience across enterprise technology, data and AI, media and advertising, and semiconductors, it helps data, research, intelligence, software and AI businesses, including media and advertising platforms, turn complex technology and proprietary data into stronger products, customer experiences, commercial models and operating performance, with trusted AI, governance, privacy and compliance built into the work where needed.
How clients engage ↓
EvidenceJudgmentResults
01 / The ethos
Data creates value when it changes a decision, improves an experience or opens a commercial channel. Insight, products, distribution, monetization and governance move together.
Working Theory brings direct COO and President-level operating experience to help CEOs and leadership teams turn strategy into stronger products, go-to-market execution, revenue growth, and operating performance. Drawing on experience across software, data, AI, and technology businesses, the firm works across product, commercial strategy, partnerships, and operations—staying engaged from the key decision through execution.
02 / Who we work with
Data, research, intelligence, software and AI businesses, including media, advertising and consumer platforms.
Companies whose proprietary data and technology can power better insight, stronger products and measurable growth.
Growth-equity backed
Businesses expanding product usage, monetization, distribution and operating leverage for the next stage of durable growth.
Private-equity backed
Companies translating a data, software or AI value-creation thesis into operating performance, cash flow and enterprise value.
Enterprise platforms
Global businesses navigating major product, portfolio, commercial, AI or operating-model shifts.
Working Theory also works directly with boards and investors on value-creation priorities, operating diligence, data rights and execution.
03 / Operator-led advisory
One business.
Five connected domains.
The advisory domains
Clients may enter through one domain. The work connects across the business when the mandate requires it.
Growth, performance & value creation
The company has product, market or customer potential, but its commercial engine and organization are not yet converting that opportunity into repeatable, scalable growth.
Clarify the offer, buyer and buying situation, then build and evolve product marketing, demand generation, sales, RevOps, customer success and lifecycle functions around a shared growth motion. Establish the segmentation, coverage, pipeline, funnel, pricing, expansion, leadership and measurement systems required to scale beyond founder-led or opportunistic demand, using AI and automation where they improve capacity, quality and speed.
Typical mandates
Value-creation diagnostic · Offer, ICP and GTM design · Product marketing and demand generation · Sales capacity, productivity and ramp · Commercial leadership and team design · RevOps, forecasting and attribution · Customer success, retention and expansion · Pricing, packaging and capital allocation
Performance leversPipeline quality and conversion · Win rate and sales cycle · Rep productivity and ramp · New-business acquisition · Retention and expansion · Revenue per seller · Marketing contribution to pipeline · Cost-to-serve · Organizational capacity and execution
Data architecture & products
The company’s data is fragmented or not yet translated into differentiated products and actionable insight.
Advise on connecting first-party, partner and proprietary sources through data architecture, identity, graphs, taxonomy and lineage, then translating those foundations into differentiated products, stronger customer experiences, deeper consumer and audience insight, trusted decisions, new monetization and distribution models, and operating leverage. Applications include marketing and advertising performance, brand and sponsorship effectiveness, and live-event monetization.
Typical mandates
Data architecture and graph strategy · Identity, taxonomy and lineage · Audience and customer intelligence products · Measurement and insight design · Product and portfolio strategy
Performance leversData quality, coverage and match rates · Time-to-insight · Product adoption and repeat use · Audience yield · Campaign, sponsorship and event performance
Data distribution, APIs, monetization & licensing
Valuable data products are not reaching customers and platforms in ways that capture their commercial value.
Design how data is packaged, priced and distributed through products, APIs, partners and LLM integrations. Define rights for access, derivative data, attribution, resale and model training, then connect licensing and usage to metering and revenue.
Typical mandates
API and LLM distribution · Partner and embedded channels · Packaging, pricing and consumption · Data licensing and usage rights · Metering and revenue design
Performance leversDurable ARR and revenue growth · API and consumption revenue · License yield and expansion · Distribution CAC · Gross margin and unit economics
Trusted AI, agentic systems & governance
The company sees the potential of AI and agents but has not yet made them trusted, governable and economically useful.
Apply AI and agentic systems to proprietary data and workflows where they advance customer value, product adoption or operating leverage. Set retrieval, authorization, evaluation, provenance and human-review controls so outputs are reliable, permitted, traceable and accountable.
Typical mandates
AI and agentic product strategy · Governed workflows and integrations · Retrieval, authorization and provenance · Evaluation and observability · Human review · Privacy, compliance and risk controls
Performance leversAdoption and time-to-value · Accuracy and exception rates · Workflow cycle time · Human-review capacity · Control and audit coverage · Cost-to-serve
NIST AI RMF · ISO/IEC 42001 · EU AI Act · AIUC-1 · GDPR · CCPA
Operating model, organization & leadership
The company’s strategy, functions and accountability are not aligned to deliver its next model of growth.
Align Product, Data, Engineering, Revenue, Marketing, Partnerships, Customer Success and Operations around a shared value-creation agenda. Redesign roles, workflows, decision rights, leadership cadence and investment priorities so the organization can deliver new products, commercial models and governed AI capabilities at scale.
Typical mandates
Operating-model redesign · Executive-team and organization design · Product and GTM alignment · Customer and service model · AI-enabled workflows · Cadence, accountability and implementation
Performance leversRep productivity and ramp · Pipeline velocity · Cycle time and handoffs · Capacity and cost-to-serve · SLA and quality · Retention, EBITDA and operating leverage
Applied where the mandate requires it
International expansion
Support market entry and cross-border growth for data, software, AI and media businesses, connecting commercial sequencing, regional infrastructure, privacy, tax, FX, partnerships and operating capacity across the US, UK, EMEA, MENA, APAC and LATAM.
M&A, diligence & integration
Support diligence and post-deal value creation across revenue quality, data and technology assets, product and platform fit, operating synergies, integration and carve-outs.
Two ways to engage
Advisory leads. Embed carries the work into results.
Every relationship is principal-led. The level of involvement expands only when the problem requires it.
04 / How we work
Evidence becomes judgment.
Judgment becomes results.
Every mandate connects operating and financial reality to a clear value-creation agenda. Embedded implementation is activated when the client wants help carrying the decision into execution.
01
Diagnose
Analyze usage, customer behavior, retention, pipeline, pricing, capacity, cycle time, unit economics, data rights and financial performance to quantify where value is created, lost or unrealized.
02
Value-creation thesis
Connect the diagnosis across growth, product, data, customers, operations, technology and capital, then identify the few levers that matter.
03
Decision & sequence
Make the choices and tradeoffs explicit, define the economics, establish rights and governance, assign accountability and sequence the work.
04
Implementation & value
When required, embed alongside client teams to implement the work and measure adoption, revenue, retention, efficiency, margin, cash and enterprise value.
05 / Operator's advantage
Strategy shaped
by operating reality.
Working Theory is led by Misha Williams, a former COO and President who has carried the P&L, led global teams and grown businesses across software, data, media and AI. He has taken data products from architecture and pilot to market, developed their distribution and commercial models, and linked AI and operating changes to customer, revenue and margin outcomes.
What operators say
“I was on Misha’s team during his time at GWI when he took on ownership of marketing, product and the commercial teams as COO. … He deeply understands both PLG and SLG motions…and how they should work together. During his time there, it was really the first time in years where our innovation engine started cranking again.”
“Misha was one of the most effective commercial leaders I’ve worked with. He did something most companies talk about and few manage: he got Product, Marketing and Sales working as one team. He built the shared rhythms, language and accountability that aligned what we built, how we positioned it and how we sold it. You could see it in AgentSpark: one story, one set of priorities and a shared plan for winning.”
“Misha built the Project Brokers US team from scratch and has grown it from just a handful of people to a national team. … Misha’s strong work ethic coupled with his personable can-do attitude and results have led to this solid growth.”
“Within his first 90 days, he recruited an outstanding leadership team—CRO, CPO and CMO—who became instrumental drivers of growth. His most impactful achievement was breaking down long-standing silos between Sales, Marketing and Product… Misha is the kind of operator who can create alignment in chaos, and clarity in confusion.”
“Misha brings discipline to complexity without slowing people down. When Spark had struggled to find its footing, he became its champion, created a focused six-week sprint and aligned Product, Sales, Marketing and Customer Success behind a successful delivery and real go-to-market motion across sales-led and product-led growth. At the same time, he pushed us beyond adding AI features, reframing how customers could access, use and derive value from GWI’s data. That thinking shaped AgentSpark and the broader move toward an AI-native business.”
“Misha perfectly blends a deep understanding of enterprise-grade analytics with exceptional client-facing delivery. As part of the Wave Analytics Cloud go-to-market team, he developed a footing in Brazil for the product and successfully formulated a new use case in intelligent marketing analytics.”
“He drives to results, thinking strategically, utilizing data-based analysis, making key decisions and then executing on them, all while being a true professional with a calm demeanor and the ability to get things done.”
“Misha combines deep analytics and strategy with a clear understanding of how technology can help businesses achieve their growth and sales targets. We worked together on business-facing machine learning and advanced analytics across behavioral analysis, clustering and market segmentation, neural-network recommender systems, and BI dashboards that connected the models to business opportunities.”
“The platform team at FreeWheel was one of the best teams I’d worked on in my career. We achieved incredible results, and no doubt Misha had a lot to do with that as the leader.”
Misha Williams in the media
06 / Founder
Misha Williams builds and scales data, AI and technology businesses, turning complex and fragmented data into trusted products, revenue and durable growth. His experience spans audience and consumer intelligence, enterprise software, advertising platforms, connected systems and applied AI across global enterprises, private equity and growth equity-backed companies, venture-backed businesses and his own startup.
His operating career began with eight years in the US Navy, serving aboard USS Dwight D. Eisenhower and at NAS Pensacola on JMCIS, the fleet command-and-control system that fused sensor, intelligence and position data into a common operating picture.
Across more than 20 years, he has led Product, Engineering, Revenue, Marketing, Customer Success, Partnerships and Operations across the US, Europe, LATAM, MENA and APAC, working with growth equity and private equity boards.
At GWI, backed by Permira and Stripes, Misha led the AI transformation of a global consumer research and audience-data business serving WPP, the NBA, adidas, Amazon, Pinterest, TikTok and Uber Ads. He launched Agent Spark, GWI’s AI-powered human insights analyst, and integrated its agentic capabilities into ChatGPT, Claude, Gemini and Copilot through Spark MCP. He rebuilt data licensing and commercial distribution, moved the business toward consumption and API models, took it upmarket and led a World Cup fan audience program.
At Pipeline360, backed by Audax Private Equity, he built the value-creation plan and board investment case from quality-of-earnings and churn analysis. He redesigned customer success and quote-to-cash, developed AgentOS for governed agentic operations, and reshaped the organization and systems to support future add-on growth and integration.
Across four mandates at FreeWheel, he rose to run a global TV and streaming business supporting Apple, Amazon, NBCUniversal, Paramount, Fox and Sky. He brought identity-based audience data and premium video advertising capabilities to market, monetized live sports from the Super Bowl through Apple’s MLS and MLB games on Apple TV+, consolidated its product portfolio into platform P&Ls and led diligence and integration of the Beeswax DSP acquisition.
At Salesforce, he led product and go-to-market across AI, IoT, Analytics and Sales Cloud. He launched Einstein predictive scoring and Next Best Action, brought mobile analytics and pipeline actions to market through Sales Wave, and connected real-time vehicle and industrial data with CRM to support proactive service, engagement and new revenue models. He led Salesforce’s LATAM entry and served Toyota, PayPal, State Farm, AB InBev and Burberry.
At Ceres Media A.I., he founded and led an advertising and media AI platform built on a proprietary Customer Data Graph. Machine learning predicted each customer’s optimal price, timing and channel, powering real-time advertising and streaming-content recommendations through a metered, multi-tenant Data-as-a-Service model.
At Texas Instruments, he rose from software engineer to applications engineering manager and senior program manager, building the technical foundation for the operating career that followed.
Through Working Theory Advisory, Misha is an equity advisor and operating partner to Cotera, a Y Combinator and Avenir-backed agentic AI platform. He brings that operating experience to CEOs, executive teams, boards and investors, advising on growth, data architecture, product and commercial strategy, monetization and distribution, trusted AI and operating models, and embedding with client teams when recommendations need to move into implementation.
Begin with the consequential problem.
Let’s develop a
working theory.
Operator-led advisory and embedded implementation for data, software, media and AI businesses.