The value comes first
I build data work people use to make better decisions — that's the whole measure of success: not the dashboard, but the call someone makes differently because of it. Three ways I help: decide under uncertainty, build the machinery, and teach the judgment underneath.
Available for hire on Upwork→An honest note. Backporch is early — I'm an independent practitioner, not yet a formalized company. Everything here is offered on an
as-is, if-there's-interest basis: we scope something small, see how it goes, and put an agreement in place if and when it makes sense. The simplest first step is
a project on Upwork or just
an email.
millions
saved in cost & waste
kilotons
CO₂ avoided per year
1
senior partner — no pyramid
Outcomes from prior roles and engagements, framed honestly — see the case themes below.
What I do
Eleven services, three jobs. Open a bucket for the specifics — each line is something I've shipped and can ship again, sized to your need.
Decideframe the bet — the judgment call6›
Decision Mechanics — the algorithm under the decision
The part I care about most: building and explaining the algorithm that makes a decision, and knowing when each one applies. Optimization, spectral and matrix methods, simulation, and honest rules-of-thumb for which tool fits which problem — not black-box button-pushing.
Operations research & optimization
The classic OR toolkit, applied. Linear and integer programming, network flows, scheduling and routing, queueing, and dynamic programming — plus metaheuristics when a problem is too large to solve exactly. For allocation, capacity, and sequencing calls that must respect hard constraints, not just fit a trend.
Network & operations optimization
Where to make it, hold it, and move it. Sequencing, routing, and footprint decisions turned from intuition into a defensible, repeatable recommendation.
Pricing strategy for new products
Price launches and changes with evidence — elasticity, margin, and scenario math — instead of gut feel, so the number survives the room it's argued in.
Cost-driver scorecards — find it, rank it, prove the dollars
I rank what's actually driving your cost and waste — by how often it happens and by recoverable dollars — then hand off the fix with a number attached. The modeling stays under the hood; what you take to the floor is the ranked driver, the recoverable $, and the proof it moved.
The decision hub
For a cross-functional call, I become the single analytical point of truth — the person who holds the numbers, the assumptions, and the trade-offs so the room can decide.
Buildwire the pipes — embedded and shipped4›
Infrastructure optimization & refactor
Make the warehouse, pipelines, and reports you already paid for faster, cheaper, and trustworthy. Often the highest-ROI work — no new tools, just a system that finally holds steady.
Analytics that get used
Dashboards and analyses people actually open and act on — across sales, marketing, logistics, finance, ops, and engineering. Legible, fast, and tied to a decision, not a vanity metric.
Supply-chain & demand analytics
Forecasting, inventory, and cost-to-serve models that have moved real money — savings in the hundreds of thousands to millions, and kilotons of CO₂ avoided per year.
Higher education — governance & decisions
Move colleges from reporting → improving → proving: data governance and one source of truth, capturing tribal knowledge before it walks out the door, and building data + AI literacy. Hands-on, without the big-firm overhead.
Teachlearn with me — the judgment, not just the tool5›
Workforce training & AI literacy
Hands-on courses for your team or yourself — using AI and data well, and the thinking underneath the tools. Not tool-chasing: the concepts that make the tools safe to trust.
AI for your team, used well
What today's AI and LLMs can and can't do, how to prompt them, where they quietly fail, and how to govern them — so a team adopts them with eyes open.
Reading the numbers
Statistics for decision-makers: what an average, a p-value, a confidence interval, and a trend actually say — and the traps that make smart people wrong.
From spreadsheet to dashboard
Build and read analytics people actually act on — the difference between a chart and a decision.
Data thinking
The systems-of-thinking foundations: measurement, causality, and uncertainty — the concept space the tools sit on top of.
Why a person, not a pyramid
You work directly with the person who does the work — the same head that frames the bet wires the pipes that place it. No account manager, no junior hand-off, no pyramid billing for a name on a slide. One senior partner, sized to the need:
Decisions under uncertaintyEmbedded on your dataHonest modelerData engineerTranslator
The model is the cheap part now — everyone has the tokens. The judgment is scarce: which question to ask, what a number is allowed to mean, when the model is wrong, and what it costs to be wrong. Calibration doesn't come in a subscription — and it's exactly what I sell.
How it works — end to end, then I stay
The hardest lesson from a previous data consultancy: the value isn't in the hand-off — it's in adoption and the months after. So I cover the whole arc, and most engagements settle into a managed partnership where I keep the work current, trusted, and in your team's hands.
1Listen›2Scope›3Build›4Adopt›5Manage
Adoption is the metric: if your team isn't reaching for it, it isn't done. See how it works and what it costs →.
Where I've worked — case themes
Industries I've delivered in, framed as outcomes rather than logos. Each is a starting point for a conversation about yours.
High-tech & electronics
Supply-chain analytics and demand/supply forecasting for a global market leader — cost savings at scale, and a documented BI estate across logistics, supply chain, sales, finance, ops, and engineering.
Retail
Forecasting and reporting pipelines; savings from the hundreds of thousands to millions, with dozens of kilotons of CO₂ avoided annually.
Precision manufacturing
DMAIC and root-cause analytics across engineering and quality — cutting cost and waste and improving cycle times on the floor.
Insurance
Claim frequency and severity modeling (GLMs, elastic net, ridge) with feature engineering in SQL — findings presented to management.
Higher education / public sector
Chaired data governance and ran the PM during an ERP migration — one source of truth out of scattered spreadsheets, and decision dashboards in Power BI.
Research & academia
Statistical consulting for faculty research and a peer co-authored study — EDA, spatial/image analysis, and predictive models from raw data.
Learn & collaborate
Tutoring is a headline offering — mathematics and data science, one-on-one, for any student (future data scientists especially). The full picture, the method, and the data-science track live on its own page: Tutoring & collaboration →. Beyond paid work, I'm glad to collaborate on research across the sciences — especially anything about systems of thinking.
Research & notes
A quieter corner, kept apart from the client work on purpose — the slow processing the fast decisions rest on. The questions I keep turning over:
- Decision-making under uncertainty, end to end
- Topological data analysis & information theory
- Lean Six Sigma applied to data systems — Kaizen for information
- The philosophy of measurement: what a number is allowed to mean
- Making analytics calm, legible, and humane
For the research itself — collaboration, or comparing notes — research@backporch.studio.
Want to talk through your decision? work@backporch.studio