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