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Craft beerLooker StudioBigQueryPOS exportsWholesale ledger export

A craft brewery put its taprooms, wholesale, and events on one scorecard

Taproom sales, wholesale accounts, and festival events each lived in different tools; the founding team made brewing and staffing decisions on gut feel, and a bad festival season had been invisible until the cash balance said so.

CLIENT a craft brewery with three taprooms and a wholesale arm — FOCUS One scorecard, three columns

Looker Studio / Data Studio DashboardsAnalytics & CROLooker Studio / Data Studio DashboardsCraft beerRepresentative example
Client
a craft brewery with three taprooms and a wholesale arm
Industry
Craft beer
Engagement
4 weeks — growth pod — analytics specialist
Service
Analytics & CRO / Looker Studio / Data Studio Dashboards
Headline outcome
Founders reviewing taproom, wholesale, and events from one weekly phone view: Gut feel → one scorecard, read from Scorecard adoption

Representative examplesEvery case study in this library is an illustrative composite of the kind of engagement we deliver — written to show our method and standards, not to name clients.

Where they started

The brewery runs three taprooms and a wholesale arm from one small operation, with the founding team making brewing and staffing calls between tasks on their phones. Taproom sales live in point-of-sale systems, wholesale in a ledger the accountant keeps, and festival results in whatever spreadsheet the event lead assembles. The tooling is deliberately small — there is no budget for new platforms, and none was requested. A festival season that went badly had been invisible until the cash balance said so, which is the kind of instrument panel that works until precisely the moment it is needed.

What it was costing

Taproom sales, wholesale accounts, and festival events each lived in different tools; the founding team made brewing and staffing decisions on gut feel, and a bad festival season had been invisible until the cash balance said so.

What they could see

  • The founders compared taprooms, wholesale, and events from three tools, three logins, and mostly from memory.
  • A bad festival season showed up in the cash balance weeks after the decisions that caused it could have been changed.
  • Staffing and brewing plans were made on feel, and the honest basis for those feels was never written anywhere.
  • Seasonal swings read as trends — one warm weekend made a taproom look like it had turned a corner.

The constraints we worked inside

  • The brewery's stack is deliberately small — POS exports, a wholesale ledger, and a festival spreadsheet; no new tooling budget.
  • Founders read on phones between tasks; the scorecard must be legible in ninety seconds.
  • Seasonality dwarfs trends; every view must normalize for season to avoid celebrating weather.

What had been tried before

The POS system's built-in dashboard was adopted for a while as the daily view of taproom performance.
It sees one taproom at a time and knows nothing of wholesale or events, so the view that was easiest to open was structurally incapable of answering the founders' actual question.
The accountant produced a year-end review of all three revenue lines with commentary for the founders.
Annual reflection cannot steer September staffing; by the time the picture arrived, every decision it could have informed had already been made for the year.

What we proposed

We proposed one scorecard, built entirely on the brewery's existing exports: taproom, wholesale, and events as peer columns with per-liter and per-event normalization, so the founders compare revenue shapes rather than absolutes of different units. Every tile compares against the same week in prior years, because seasonality dwarfs every other signal in this business and a dashboard that celebrates sunshine is worse than none. The scorecard is designed phone-first — legible in ninety seconds between tasks — with detail one tap away. No new tooling, no new logins, nothing to maintain beyond the exports they already produce.

Just as important is what we ruled out, and why:

  • An all-in-one brewery management platformReal money on a subscription the founders explicitly have no budget for, plus a migration of the POS and ledger workflows that serve them fine — the constraint was stated up front.
  • A general BI tool with automated connectors to POS and accountingConnector fees plus setup complexity on three mismatched sources, and the result would be a desktop analytics product when the founders read on phones between tasks.

How the work ran

01One scorecard, three columns

Taproom, wholesale, and events appear as peer columns with per-liter and per-event normalization, so the founders compare revenue shapes, not absolutes.

02Seasonal baselines on every tile

Each tile compares against the same week in prior years, making real movement visible and sunshine invisible.

03Phone-first legibility

The scorecard is designed for a phone screen first, with the detail view one tap away.

Delivered by the growth pod — analytics specialist over 4 weeks, with working increments reviewed with the client every week.

The stack, and the reasoning

Looker Studio
The founders read on phones between tasks, not at desks; the scorecard had to open in one tap between a kettle check and a delivery, and free, browser-based tooling was the only budget shape that fit.
BigQuery
The free tier comfortably covers three taprooms' weekly exports, and it holds the seasonal baselines that make same-week comparisons possible without a spreadsheet.
POS exports
The taprooms' systems cannot be replaced on this budget, so their scheduled exports are the source — shaped once, on arrival, rather than fought at chart level.
Wholesale ledger export
The accountant's ledger is the wholesale truth and stays the accountant's tool; a scheduled export brings it into the scorecard without changing how she works.
Seasonal baseline queries
Same-week-prior-year comparisons are the whole defense against celebrating weather — built into the queries so the founders never have to remember to ask.

What went wrong

Obstacle

The festival spreadsheet's free-text fields — event names, city spellings, revenue notes — needed a cleanup layer nobody had budgeted, and agreeing its format took longer than building the queries.

Handled: We negotiated a light template with the event lead for future festivals, wrote a parsing layer for the historical free text, and accepted documented fuzziness on old events rather than inventing precision.

Obstacle

One taproom's POS ran a different software version with its own product naming, so the same beer appeared under two names and the per-liter comparisons silently split.

Handled: A product-mapping table fixed the naming at import, we validated the first month against the founders' own knowledge of what they actually sold, and the map is now part of the weekly checklist.

How we worked together

Cadence
Two short working sessions weekly with whichever founder owned the numbers that week; the accountant joined twice for the wholesale export; a phone demo of each scorecard iteration, not a deck.
Client side
One founder acted as product owner and supplied the context for every trade-off; the accountant owned the wholesale ledger export; the event lead owned the festival template's adoption.
Decisions
Normalization choices — per-liter, per-event — were settled with the founders in one tasting-room session; layout was iterated directly on their phones until ninety seconds held.
They provided
Scheduled access to the POS exports, the accountant's wholesale ledger, the festival spreadsheet's history, and honest founder attention in short bursts rather than meetings.

What changed

The headline: founders reviewing taproom, wholesale, and events from one weekly phone viewGut feel → one scorecard, read from Scorecard adoption. A second check: weekly revenue reviews needed to plan brewing and staffing at 3 → 1.

The founders' weekly check-in happens on one screen now, usually standing up, usually while the kettle is on — three revenue shapes side by side, each against its seasonal baseline, sunshine ignored by design. The next festival season was judged while it was still happening, and one underperforming event was dropped from the calendar on evidence instead of folklore. Brewing quantities still involve judgment, but the judgment now starts from the same numbers every founder sees, which ended the quiet disagreements about whose week was the real week.

The result was read from Scorecard adoption against the pre-engagement baseline over the stated window, with a guardrail check on weekly revenue reviews needed to plan brewing and staffing. Where platform-reported numbers and business outcomes differ, this record says which layer it is quoting.

What they own now

  • The phone-first scorecard with taproom, wholesale, and events as peer columns.
  • The seasonal baseline queries behind every tile, documented and editable.
  • The product-mapping table reconciling the two POS naming schemes, with its weekly checklist.
  • The negotiated festival template and the parsing rules for the historical free-text files.
  • The BigQuery setup on the brewery's existing account, with the export schedule written down.

What we would do differently

We would have negotiated the festival spreadsheet's format before building — its free-text fields needed a cleanup layer, and agreeing a template would have saved it.

Analytics & CROLooker Studio / Data Studio DashboardsCraft beerLooker Studio

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