Origin

The best time to build is right now.

Building something used to take an army and a fortune. Now all it takes is an idea and the belief to chase it. AI does the heavy lifting. The rest is up to your imagination. So whether you're starting from zero, growing what's working, or rebuilding what you've outgrown, this is your moment! I partner with you to make it real, most recently taking a business from $0 to $12M+ a year in two years, right through the company going public. Let's build yours.

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The Proof
$0→$12M+
A year in revenue, reached within two years of launch and carried through the company going public
$100M/yrcustomer that found the company through an online search
+328%more customer accounts in a year, driving 80% of online orders
400+branches selling through one website
Three Ways I Work
When you need traction

Growth Strategy

The difference between an idea that catches and one that gets politely ignored. Positioning, market entry, and the hard sequencing calls, made with your data in one hand and your customers' actual words in the other.

When the business goes digital

Digital Channel Development

Taking the business online for real: sign-up, credit, payments, and the system that turns one sale into a customer who keeps coming back. The unglamorous plumbing that quietly brings in the money.

When AI has to deliver

Applied AI

Machine learning that clocks in and does a job. An AI tool that grew an online catalog from 5,000 items to 100,000. A model that spots a machine about to break before it breaks. Real systems that run the business, not a slick sales demo.

How I Think

Nothing exists yet? That's my favorite brief.

The moment right before something becomes real, when everyone agrees on the problem and no system exists to solve it, is where I've spent twenty years on purpose. Building from nothing isn't a chapter of my career. It's the whole spine of it.

Software should bend to the business. Finally, it can.

For twenty years companies twisted themselves to fit their software: renaming their own steps to match a vendor's menu, hiring people whose whole job was working around the system. We did it because custom software cost years and millions of dollars. That math just broke. AI makes software built for one specific business genuinely affordable, and I think one-size-fits-all software is living on borrowed time. The businesses that see it first won't just save money. They'll pull ahead.

Pain points first. Lean before code.

Every build I've shipped started at a pain point, not a feature list. Map the workflow, cut the waste, then point technology at what's left. Skip that order and you just get a faster mess. (I've met the faster mess. It is not cheaper.)

The point was never the software. It's the people it frees.

Every hour I've taken out of a workflow, ten minutes of quoting down to three, a credit process cut in half, went back to a human with better things to do. AI makes that dividend enormous, and it's the part I refuse to be cynical about: good tools hand people their focus and their afternoons back. That's the real unlock. The revenue just follows it home.

The Case
A business taken from nothing to $12M+ a year across 400+ branches. A $100M customer who started with a single online search. One playbook, run all the way through.
Shannon Owens hello@shannonowens.com LinkedIn
Engagements

What I Do

Three ways I partner with you, each a build rather than a binder. Bring me in for one, or all three. Either way, I'm in it with you, not handing over a plan and walking away.

When you need traction

Growth Strategy

You've got a product, a goal, or a market opening up, and no clear path from here to revenue. Finding that path is the job. I start in the data (what's happening) and then in real conversations with your customers (why it's happening), because a spreadsheet has never once told anyone the whole truth. From there come the calls that decide whether an idea catches on or gets ignored: how to position it, where to compete, what to build first, and in what order.

I've made those calls at the scale of an $8B pension fund's overhaul and at the scale of getting a single product to market.

You walk away withA clear plan for how to position it and roll it out, grounded in your data and your customers' own words, sharp enough to start building on Monday.

When the business has to go digital

Digital Channel Development

Your revenue still runs on phone calls and good relationships, and everyone quietly knows that ceiling is real. I take businesses online for the first time, and I don't stop at the storefront: sign-up, credit and payments, insurance paperwork, and the behind-the-scenes connections that make a real sale possible. Then the part most launches skip: watch where customers get stuck, clear the way, improve it, until the experience is genuinely good.

That's how I built the online rental business at a Nasdaq-listed construction technology company: from a January 2024 launch to $12M+ a year across 400+ branches within two years, through the company going public, with customer accounts up 328% and driving 80% of online orders.

You walk away withA working online business, the systems behind it, and a customer list you actually own.

When AI has to deliver

Applied AI

You know AI should be doing real work in your business, and so far everything you've been shown is a demo with great lighting. I drive machine learning that launches and keeps working, same discipline as everything else: fix the process first, point AI at what's left, then keep improving it against real use until it holds up when real people lean on it.

At the same company: an image-recognition system (built on Amazon Rekognition, trained on 1 to 2 million photos) that grew an online catalog from 5,000 items to 100,000, and a model that read live data off the machines to flag one about to break down before it did.

The future I build toward: AI makes it affordable to create software shaped to how a business actually works, instead of bending the business to fit some off-the-shelf product.

You walk away withA real, working system measured in results, not a demo that dies in a slide deck.

All Three, One Build
The construction tech build used all three at once: strategy found the opening, the online business brought in the revenue, and AI handled what people couldn't. $0 to $12M+ a year, in two years.
The Method
01

Find the pain

Sit with the actual work until the real problem shows itself. It's usually upstream of where it hurts.

02

Lean the process

Streamline before you automate. Technology applied to a broken process only makes the mess move faster.

03

Build something people use

Launch the version people actually use, watch where they get stuck, and make it smoother with every update. Measure it in revenue, and leave behind something that runs without you.

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Case Study

Building a Digital Channel From Zero

The whole story behind the $12M+ two years: what didn't exist, what I built, and the $100M deal that walked in through the front door.

No. 01The Problem

A Nasdaq-listed construction technology company had 400+ branches and no digital rental channel. Every rental request ran through a phone call or a branch visit. No online path from browse to book, no data on what customers wanted before they called, and not a single identified customer email anywhere in the business. Revenue from digital was $0.

No. 02The Build

I owned the whole thing end to end: not just the storefront, but everything underneath it. That meant designing the sign-up flow from scratch, building the credit and insurance-paperwork steps customers had never been able to finish online before, and connecting the outside systems that make a real sale possible. It went live in January 2024.

Signing customers up, tied to renting, sign-up, and credit, turned the business into something that fed itself. Past a point it stopped needing a push: 4,562 new accounts in a year (up 328%) reached critical mass and came to drive 80% of online orders, and the sign-up system built the company's first real customer list from nothing.

New customer accounts, up 328% in a year

The AI work was mine to direct, from the idea to the technical design to the testing: an image-recognition system (on Amazon Rekognition, trained on 1 to 2 million photos) that grew the used-equipment catalog from 5,000 items to 100,000, and a model that read live data off the machines to flag one drifting out of its normal range before it broke down. All of it was built and grown while the company was going public: new systems, built at the speed and under the scrutiny that going public demands.

No. 03The Result
$0→$12M+
A year in revenue, within two years of launch, growing 36 to 40% a year across 400+ branches

Critical mass. Past the tipping point, the channel stopped needing a push and grew itself.

No. 04How Customers Found Us

A website only sells to the people who find it, so I owned that too. I ran the company's whole online presence end to end: how it showed up in search, the content behind it, and a $150K a year search-ad budget alongside, building the kind of visibility a company needs heading into going public. AI did real work here too, helping grow the traffic and what we understood about it.

Search traffic doubled in ten months (June 2023 to April 2024). The top local pages grew tenfold in six. Visitors read about seven pages a visit, roughly double the biggest competitor. Those results were verified in the independent case study that profiled the work.

No. 05The Deal That Proved It

In 2024, a Fortune 500 energy company that had never heard of the business found it through that online presence and the experience behind it. That first contact became a $100M a year customer. No cold call, no chasing a bid: the website made the introduction, and the experience earned the trust.

No. 06Why It Matters Beyond the Number

This is the pattern I repeat: find the thing that doesn't exist yet, build the version people actually use (not just launch it), push it to critical mass, and leave behind something that runs without me in the room. It's the same instinct that shaped my work on Missouri's pension governance and insurance modernization: take something fragile or nonexistent and make it durable.

Also on the Record

Governing an $8B Pension Fund

MOSERS · Board Chair & Trustee · 2015 to 2018 $8B

Elected chair of Missouri's state employee pension fund during a major reform and a crisis year. This is the same build-from-nothing work in a different arena: I built the systems the board needed to actually dig into the fund's investments and risks, instead of just receiving reports. The job was turning a board that took reports at face value into one that could question them.

Taking a Court System Paperless

Missouri Courts · Statewide Program Lead · 2012 to 2016 115 counties

Directed the statewide eFiling rollout that moved Missouri's courts from paper to digital across all 115 counties, leading 49 county implementations directly while managing a six-project portfolio. Statewide adoption is won county by county: each one had its own clerks, judges, and workflows, and each one had to come along willingly.

Modernizing a Workers' Comp Insurer

Missouri Employers Mutual · Technical Program Manager · 2018 to 2021 10 min → 3

Led the full replacement of the customer and agent websites with a 40-person team. Lean process work cut the main quote process from ten minutes to three, and a rebuilt claims system brought the same care to the moment policyholders need the company most.

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Perspectives

Writing & Speaking

What twenty years of building inside heavily regulated industries taught me about software, and where AI takes it next. Strong opinions, all of them earned the hard way.

The Essay

The End of One-Size-Fits-All

AI has broken the economics that made businesses bend to their software. The companies that notice first will pull ahead.

Every enterprise software deal ends the same way. The vendor demos a product built for a thousand companies. The buyer signs. Then, quietly, the business starts bending: renaming its processes to match the vendor's vocabulary, adding steps because the workflow demands them, hiring people whose whole job is working around the system.

I've watched it for twenty years, up close. In state government, where teams reshaped how they worked around whatever their systems could handle. In insurance, where quoting a policy took ten minutes because ten minutes was what the platform allowed; it took Lean process work and a rebuilt portal to get it to three. In construction technology, where the workflows that actually made money (credit, insurance, logistics) lived outside the software entirely, in phone calls and PDFs. The software never quite fit, and the business always paid the difference.

We accepted this because the economics gave us no choice. Custom software was a luxury. Building something shaped to one company's actual workflow took years and millions, so we bought the closest thing off the shelf and absorbed the friction. One-size-fits-all was never a design philosophy. It was a cost constraint.

That constraint is collapsing.

AI has changed what a small team can build. The systems I drove to production in the last few years, an image-recognition tool that grew an equipment catalog twentyfold and a model that read live data off the machines to predict breakdowns, were software shaped to one company's equipment, one company's data, one company's day-to-day reality. None of it existed on a vendor's price list. All of it went live.

A caution, learned the Lean way: technology applied to a broken process just makes the mess move faster. The order still matters. Map the workflow. Take out the waste. Then build to what remains. AI lowers the cost of building. It does not lower the cost of building the wrong thing.

But when the process is sound, the old tradeoff is gone. You no longer choose between software that fits and software you can afford. The companies that see this early will stop contorting themselves around their vendors and start compounding: every workflow a little more their own, every system a little closer to how the work actually happens.

One-size-fits-all software had a good run. It was the sensible answer to a world where software was expensive to build. That world is ending.

The fit is the product now.

Speaking

I speak from the builder's side of the table: what actually happened, what it cost, and what held up once real people used it. Current topics:

For podcast and panel invitations, write to hello@shannonowens.com.

Coming Next

The $100M Search ResultUpcoming

Launch, Watch, Fix: Letting the Sticking Points Draw the RoadmapUpcoming

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The Through-Line

About

Shannon Owens

I've spent twenty years taking things that don't exist yet and making them work.

That's meant different things at different points: leading tech strategy inside Missouri state government, chairing the board of an $8B public pension fund through a major reform and a crisis year, modernizing the technology at an insurance company, and, most recently, building the online rental business at a Nasdaq-listed construction technology company from the ground up: the design, the sign-up, the credit and insurance steps, and all the behind-the-scenes connections underneath it, grown to $12M+ a year across 400+ branches as the company went public.

2012

Missouri Courts

Missouri's courts ran on paper. Four years later, all 115 counties filed electronically; 49 of those implementations I led directly, clerk by clerk, courthouse by courthouse.

2015

MOSERS Board

An $8B pension fund had a board that just received reports. As trustee, then elected chair, I built the systems that let it actually question them, through a major reform and a crisis year.

2016

State of Missouri

The state had no single source of record for the roughly 20,000 businesses it regulated. Its first enterprise master-data implementation changed that: 1,400 employees, a $12M budget, 14 projects running at once.

2018

Missouri Employers Mutual

Quoting a workers' comp policy took ten minutes. A 40-person portal replacement and Lean process work cut it to three, and claims intake was rebuilt around the moment policyholders need the company most.

2021

Construction tech

A construction technology company (on the Nasdaq) had no way to connect insurance to its equipment data. I led that build from scratch and rolled it out across the business, alongside early AI work: predicting breakdowns and recognizing equipment from photos.

2024

The rental channel launches

In January, online revenue was $0 and not one customer email existed anywhere in the business. Two years later: $12M+ a year across 400+ branches, a real customer list built from nothing, and momentum the company carried into going public.

2026

Origin

The pattern becomes the practice: growth strategy, digital channels, and applied AI, concept to market. Every build starts at the origin.

The through-line isn't the industry. It's the moment right before something becomes real, when there's a problem everyone agrees on but no system yet to solve it. That's where I do my best work, and the work I love most: translating ambiguity into architecture, and architecture into adoption.

The method underneath is Lean: find the pain point, simplify the process, then bring technology to what's left. And the belief on top is that AI is ending the era of one-size-fits-all software. It's finally affordable to build products shaped to how a business actually works, instead of bending the business to fit some off-the-shelf product.

The construction tech years were startup years, and they gave me range. I looked after the company's whole online reputation, built the kind of search visibility a company needs heading into going public, and used AI to grow both the traffic and what we understood about it. Through all of it I stayed data-driven without being data-only: the numbers showed me where customers got stuck, and the conversations told me why. Clear the way, improve it, repeat until it's excellent.

I've owned the revenue and the budget, led the AI work, run a federal-compliance project, and governed a public pension board: the same challenge at four different heights. And none of it was solo work. I led an in-house web team and an eight-person outside engineering firm, ran a $1.2M a year budget, and coordinated credit, marketing, fleet, billing, and insurance to deliver one seamless experience.

And I stay hands-on with the technical work, not above it. The image-recognition system that grew an online catalog from 5,000 items to 100,000 was mine to conceive, direct, and test into production.

MBA PMP Advanced CSM Lean Six Sigma Green Belt

I take on a small number of consulting partnerships at a time, in growth strategy, digital channels, and applied AI, and I'm open to the right Director or VP product role. I work alongside your team, in the room and in the weeds, not from a slide deck. If you're building something that doesn't exist yet, that's exactly my kind of problem.

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Let's Talk

Let's build something that doesn't exist yet.

Growth strategy, digital channels, applied AI, advisory, or the right Director/VP product role. If you're starting from nothing, I'm in.

hello@shannonowens.com LinkedIn →

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