Your gut built the business. Evidence scales it.
Somewhere in your invoices, schedules, and customer records sits the answer to the question you've been debating for months. We extract it — and when the answer isn't in your data, we go ask your market directly.
Folklore is expensive at scale
Every business carries beliefs that were true once: which service makes the money, which customers are 'good,' what the market will pay, why people choose you. Decisions compound on those beliefs — pricing, hiring, expansion — long after the data quietly disagrees.
We run the evidence two ways. Inward: your own operational and financial data, cleaned and made to answer the question at hand. Outward: structured research in your actual Northwest Arkansas market — customer interviews, win/loss, demand tests — not national industry reports stretched to fit.
AI has made research faster and more dangerous at once. A 2026 Cornell SC Johnson study describes analysis that once took seven days now delivered in two — while warning that AI produces work that looks authoritative and is sometimes confidently wrong. The new skill isn't generating the chart; it's stress-testing it: asking the right question, and catching the hallucination before it becomes a pricing decision. We use AI to move faster, then apply the judgment that decides whether to trust it.
What changes
The standing debate settled with evidence; a scorecard of the numbers that actually predict your month; market beliefs tested before capital follows them.
How we track it
Decision made and documented; forecast accuracy against the new model; margin by segment after re-pricing; research findings acted on within the quarter.
Where it shows up
Capital pointed at what the evidence supports; prices set on willingness-to-pay instead of fear; the end of meetings that re-litigate opinions.
Evidence, two directions
The question first
We start from the decision you need to make, not the data you happen to have. Analysis without a decision attached is a hobby.
Inward: your data
Invoices, schedules, job costs, CRM exports — cleaned, joined, and interrogated. Most owners are sitting on answers they've never once queried.
Outward: your market
Customer and lost-prospect interviews, demand tests, competitor pricing sweeps — original research in this corridor, sized to SMB budgets.
The operating scorecard
The handful of numbers that predict your month, automated to land weekly — so the evidence habit outlives the engagement.
Every engagement runs the same way: conceptual agreement on objectives, measures, and value — then one proposal, three options, one fixed fee.
See how we engageAn illustrative engagement
Composite scenarios drawn from the kinds of situations we work on. Details altered; client identities not used.
- Objective
- Settle a year-long debate: which product lines and customers actually earn their keep, and what would happen to margin if the worst were re-priced or released.
- Measures
- Contribution margin by line and customer after true cost allocation; margin shift after re-pricing; revenue retention through the change.
- Value
- Two 'cornerstone' accounts turned out to be subsidized by everyone else — re-priced with evidence in hand, one stayed, one left, and margin improved either way.
Illustrative composites for explanation of method — not statements of past performance, and not a guarantee of results.
Grounded in peer-reviewed research
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U.S. Census-linked evidence that data-driven decision-making is associated with significantly higher productivity among adopting firms.
Brynjolfsson & McElheran (2016) — “The Rapid Adoption of Data-Driven Decision Making,” American Economic Review, 106(5). doi.org/10.1257/aer.p20161016
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Across 732 firms, structured management practices — monitoring, targets, incentives — correlate strongly with productivity, profitability, and survival.
Bloom & Van Reenen (2007) — “Measuring and Explaining Management Practices Across Firms and Countries,” The Quarterly Journal of Economics, 122(4). doi.org/10.1162/qjec.2007.122.4.1351
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A 2026 study finds AI compresses research timelines dramatically — days into hours — while making critical evaluation the scarce skill, since AI outputs are fast, plausible, and sometimes confidently wrong.
Doucette, Gaur, Dixit, Gao & Koo (2026) — “The Impact of Artificial Intelligence on MBA Hiring, Skills Expectations, and Business School Curriculum,” Cornell SC Johnson College of Business.
Research informs our methods. Findings describe study populations — not a promise of results for any engagement.
Stephen Velasquez
Founder-owner of ZipHealthy for ten years — profitable, with no outside capital — and a former technology-product executive at Amazon, Microsoft, Walmart, and the U.S. Department of the Treasury. The advice you get has been paid for with the advisor's own payroll, and stress-tested at Fortune 1 scale. Every engagement is led personally, start to finish.
Asked by owners, answered directly
It's the normal starting point. Messy-but-present beats clean-but-absent, and the first week of every engagement is cleanup. If something truly can't be answered from your records, we'll tell you — and design the cheapest way to start capturing it.
Almost never at SMB scale. Your existing systems' exports, joined competently, answer most questions. We'd rather hand you a scorecard you maintain in tools you already own than sell you a platform.
Industry reports describe the average of a national market; you operate in a specific one. Twelve structured interviews with your actual customers and lost prospects beat three hundred pages about the sector.
Faster answers, easier mistakes
96%
of firms report AI productivity gains — but 65% can't yet prove where.EY, 2025
88%
of businesses now use AI in at least one function — up from 55% in 2022.WEF, 2026
#1
AI is the top skill recruiters expect to need within five years.GMAC, 2025
Industry figures as compiled in Cornell SC Johnson's 2026 review; original sources attributed inline — not promises for any engagement.
Decide on evidence.
One conversation with the principal — a Cornell MBA who'll turn your own data into a decision and use AI to get there faster without trusting it blindly. We'll settle the question that matters and show you how we'd measure it. If we can't help, we'll say so.
Prefer the phone? (479) 259-1390 · 240 S Main St, Suite #270, Bentonville, AR 72712
Most of our clients come to us by referral from other Northwest Arkansas owners. If someone sent you here — tell us who, so we can thank them.