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Net Good Business helps private and PE-backed mid-market B2B companies convert AI, workforce, and capital investments into durable enterprise value. Founder Bill Dunnington works as a fractional executive, strategic advisor, and executive coach — helping leadership teams build the operating discipline required to make AI and workforce transformation produce measurable financial results.

Bill Dunnington is the founder of Net Good Business (also known as Dunnington Consulting), based in Madison, Wisconsin. He has 30+ years of experience as a senior people and transformation executive, former Accenture and Booz consultant, and CEO advisor. He works with CEOs, CFOs, CHROs, and boards of private, mid-market B2B companies to turn AI and workforce investment into enterprise value. Read Bill's full background →

Primarily private and PE-backed mid-market B2B companies, typically $5M–$100M in revenue, whose CEOs, COOs, CFOs, or CHROs need to convert AI and workforce investment into measurable business results — without adding permanent full-time executive headcount. Most clients are in knowledge-workforce industries: professional services, technology, healthcare, biotech, and manufacturing.

Selected client results include: 27% enterprise value increase in 14 months (medical device company), 48% recurring revenue growth from new consulting services (accounting firm), and four acquisitions completed in 11 months (biotech company). Most engagements produce measurable productivity improvement and adoption gains within the first 90 days.

A senior executive embedded inside a company part-time — typically 1–2 days per week — to lead AI adoption and workforce transformation as a member of the leadership team. Unlike a consultant who delivers recommendations and leaves, this role drives execution and is accountable for measurable outcomes. Engagements typically run 6–12 months and report to the CEO, COO, or CHRO. Full details →

A consultant delivers advice, frameworks, and recommendations — then leaves execution to the client. A fractional executive is embedded on the leadership team: attending leadership meetings, owning deliverables, managing cross-functional teams, and accountable for results. The distinction matters because most AI transformation failures are execution failures, not strategy failures.

Pricing depends on structure. A day rate runs $2,250–$3,500. A monthly retainer for 1 day per week is $9,000–$14,000/month. Two days per week is $16,000–$26,000/month. A full 6–12 month engagement runs $75,000–$180,000 total. Many engagements include an optional performance bonus of $25,000–$75,000 tied to adoption milestones or financial outcomes. See full pricing →

Most engagements run 6–12 months across three phases: Diagnose & Align (weeks 1–6), Build & Embed (weeks 7–20), and Scale & Sustain (weeks 21–48). The goal is to build self-sustaining capability inside the organization — so the engagement ends with lasting results, not ongoing dependency.

This role is right for CEOs, COOs, and CHROs who have made AI investments — or are planning to — but don't have a dedicated senior leader driving adoption, workforce readiness, and execution. It's especially effective for PE-backed companies preparing for growth, transition, or acquisition, where AI and workforce capability directly impact enterprise value.

The most common reasons: AI pilots without adoption, productivity gains that don't reach the bottom line, managers overwhelmed by change, workforce capability lagging strategy, fragmented tools with unclear ownership, and governance uncertainty. The constraint is rarely the technology — it is leadership, operating model, and workforce capability. That is the gap this work is designed to close.

A 6-week diagnostic that identifies where AI can create measurable ROI in your specific company, where it shouldn't be deployed yet, and what governance and implementation plan is required. Most companies invest in AI without this clarity — which leads to wasted resources and failed pilots. The assessment produces an opportunity map, risk and readiness analysis, implementation roadmap, and governance framework. Learn more →

For a mid-market company, AI governance means clear answers to: Who owns AI decisions? What tools are approved? How is risk assessed and managed? How are employees trained and protected? What data can AI access? Without governance, companies face regulatory risk, inconsistent results, and board-level liability. Good governance doesn't slow AI adoption — it makes adoption sustainable and defensible.

The Capital Efficiency Index (CEI) is an executive diagnostic that measures whether a company's operating system is converting AI, workforce, and capital investments into durable enterprise value. It produces a 0–100 score across six domains: Strategic Capital Discipline, Operating Model Efficiency, Workforce Foresight, Human–AI Leverage, Risk & Governance Maturity, and Value Realization Discipline. Learn more about the Future-Fit Enterprise System →

Readiness depends less on technology and more on leadership alignment, workforce capability, and operating model clarity. Key signals: leadership agrees on what AI should accomplish, there is clear ownership of AI initiatives, the workforce has basic digital fluency, and the company has the governance appetite to manage risk. If any of these are missing, the AI Assessment is the right starting point — it produces a readiness analysis alongside the opportunity map.

A focused pilot used to build a new operating capability — AI adoption, workforce redesign, or a new service line — before scaling it across the organization. Rather than betting the whole company on a large transformation, Lighthouse Projects create a proof point, build internal confidence, and identify execution risks at small scale. Learn more →

It requires four things: a clear picture of which roles and skills the AI strategy actually requires, an honest assessment of where current capability falls short, a development and redesign plan that closes the gap, and leadership that drives adoption and behavior change. Most companies have the AI strategy but skip the workforce alignment work — which is why AI investments stall at the pilot stage.

People First is the operating philosophy at the core of Net Good Business: that competitive advantage comes from building a workforce that is genuinely hard to copy — in capability, culture, and commitment. For AI transformation, it matters because AI tools are available to everyone. The differentiator is whether your people can use them better, faster, and more consistently than your competitors. Technology advantage is temporary. People advantage compounds.

A focused 90-day engagement designed to align strategy, workforce, and AI so growth plans aren't constrained by capability gaps or execution risk. It produces a workforce capability map, a role and skills redesign plan, and an implementation roadmap tied directly to the company's growth objectives. Learn more →

The best starting point is a free 30-minute conversation. Bill will ask about your current AI initiatives, your biggest execution challenges, and what measurable outcomes matter most. From that conversation, it's usually clear whether and how Net Good Business can help — and which engagement type fits best. Book a free call →

Most clients start with either the AI Assessment (if they need clarity on where to invest) or a Fractional VP engagement (if they already know AI is a priority and need execution leadership). A smaller number start with the Capital Efficiency Index diagnostic or a Lighthouse Project. The free 30-minute call is the fastest way to identify the right entry point for your specific situation.

Engagement length varies by service. A Fractional VP engagement typically runs 6–12 months. An AI Assessment runs 6 weeks. A 90-Day Strategic Workforce Development engagement runs approximately 3 months. Executive coaching engagements are ongoing. Most clients begin with one focused engagement and expand the relationship as results build.

Yes. While Bill is based in Madison, Wisconsin and has deep relationships across the Midwest, most engagements are structured to work effectively with distributed or remote leadership teams. The embedded fractional model works well in person for key leadership sessions and remotely for ongoing execution support.