Data & Reporting Infrastructure

How We'd Run It

The same six steps, applied to this project

1. 1

   Diagnose

   We find the handful of recurring questions leadership asks in meetings, and the specific spreadsheets and systems today's answers come from.

2. 2

   Pilot

   We build a pipeline for the two or three highest-value data sources first, and put real numbers in front of the people who'll use them before touching anything else.

3. 3

   Review, Together

   We sit down with leadership and the team currently maintaining the spreadsheets, and confirm the pilot numbers match what they already trust — or figure out why they don't.

4. 4

   Build

   We build out the full pipeline and dashboard, with clear, documented definitions for every metric so a disagreement is a lookup, not a debate.

5. 5

   Launch, With a Human on Every Send

   We launch the dashboard as the source of truth for the questions it covers, with a human still spot-checking outputs against the old process during the transition.

6. 6

   Operate & Improve

   We monitor the pipeline for silent failures and definition drift after launch, and hand off clear ownership so accuracy doesn't quietly decay.

Typical Timeline

A rough phase-by-phase breakdown

A target shape for a project like this, not a narrated account of a specific past engagement — actual pacing depends on scope and how quickly decisions get made.

1. 1

   Diagnose

   Week 1

   Find the recurring questions leadership asks and the systems today's answers come from.

2. 2

   Pilot

   Early Week 2

   Build a pipeline for the two or three highest-value data sources and put real numbers in front of the people who'll use them.

3. 3

   Review Together

   Mid Week 2

   Confirm the pilot numbers match what leadership and the current spreadsheet owners already trust.

4. 4

   Build

   Weeks 2-3

   Build out the full pipeline and dashboard with documented definitions for every metric.

5. 5

   Launch

   Week 3

   Launch the dashboard as the source of truth, with a human still spot-checking outputs during the transition.

6. 6

   Operate

   Ongoing from Week 3

   Monitor the pipeline for silent failures and definition drift, and hand off clear long-term ownership.

What's Included

What an engagement like this covers

• Interviews with leadership to find the recurring questions the dashboard needs to answer

• A fixed-fee pilot pipeline for the two or three highest-value data sources first

• Documented, agreed-upon definitions for every metric so disagreements are a lookup, not a debate

• A full pipeline and dashboard build once the pilot numbers are trusted

• A monitored transition period with spot-checks against the old manual process

• Clear ownership and monitoring handed off so accuracy doesn't quietly decay after we're gone

Where Projects Like This Go Wrong

Common pitfalls, and how we handle them

• Building a beautiful dashboard on top of data nobody has verified, so leadership makes decisions off numbers that are quietly wrong

• Trying to unify every data source in the company on day one instead of proving the pipeline on the two or three sources that drive decisions

• No owner for the data once it's live, so definitions quietly drift — what counts as an "active customer" changes — and the dashboard slowly stops matching reality

Targets, Not Results

What we consider success

These are the targets we'd work toward on a project like this — not results we're claiming to have already achieved.

• Leadership can answer their recurring questions from the dashboard without asking someone to pull a fresh spreadsheet

• Every number on the dashboard can be traced back to its source and definition, so a disagreement about a metric is a five-minute conversation, not a week of reconciliation

• The pipeline keeps running and stays accurate without a person manually refreshing it