Build the system
I design the system around the decision it has to support. If you want, I build the first version myself.
Book an intro call
Always included
Architect-lead
Add when you want it
Hands-on build
You choose
Which parts
What I build
Four kinds of system
Dashboards
The numbers a team checks every week, built around a decision.
Data pipelines
ETL that moves data from where it lives to where it gets used.
Data platform
The warehouse, models and definitions everyone shares.
Forecasts and analysis
Forecast models and market analysis that support a plan.
How it works
Two tiers. Pick the one you need
Tier 1, always
Architect-lead
I design the system, set the definitions, and direct whoever builds it, your team or a vendor.
Scope and design for the parts you pick
Data definitions and success metrics
Review of what gets built
Tier 2, added on top
Architect-lead plus hands-on build
Everything in Tier 1, and I build the parts you choose myself. Costs more, because it is more of my time.
Working first versions, not only a design
You choose which parts I build
Hand-off so your team can run it
Hands-on build always comes with the architect-lead work. You can take the lead on its own.
Proof
What I have built
1
A dozen dashboards for a subscription business
Built in Tableau and with Claude on Vercel. A daily business-health tracker, a customer lookup for support, marketing spend and channel attribution, a target-CPA tool, a sales conversion monitor and follow-up queue, a lifecycle view of growth, habit and renewals, and cohort LTV.
2
A 3-year forecast for a product in development
Projects daily active users and revenue from conversion, retention by tier and country, organic and paid acquisition, installs and session length. Teams enter planned features with an expected lift and the model reruns. Assumptions are checked against real market comparables. Used for annual and long-range planning.
3
A portfolio data pipeline across many product teams
Built at multiple companies. Standard top-line KPIs so every product is judged the same way: what is working, what is failing, what needs help. When something looks off, drill into the next level of KPIs, with no custom analysis per team.
4
Market analysis
Tested the forecast’s assumptions and the market appetite for what was being built, using user research and other data.
Fit
Is this the right engagement
A good fit
You know what decision the data should support and need it designed well, with or without someone to build it.
Not the right fit
You want a generic dashboard tool set up with no decision behind it. If you are not sure what is wrong, start with the Bottleneck Diagnostic.
Questions