Short answer: most brewery dashboards stop at the line chart and the Shewhart control chart — and those genuinely answer “is this batch in spec.” But brewing asks questions they show badly: does this batch match its brand profile, is a value slowly drifting, how does flavour evolve over weeks of ageing, and where do extract, water and energy go. Each has a better-suited, underused chart — radar profiles, CUSUM/EWMA, trajectories, Sankey. This series walks through them. The skill isn’t the chart library; it’s matching the visualization to the brewing question.
This opens a five-part series on brewing data visualization — specifically the charts most brewery dashboards never reach for. Your line charts and QC control charts are doing real work and aren’t going anywhere. This series is about the other questions — the ones those charts answer poorly — and the visualizations that answer them well: true-to-target brand tasting, drift-catching SPC, shelf-life trajectories and Sankey balances.
The default chart is a default, not an answer
When a brewery builds its first dashboard, almost everything becomes a line over time or a value against a spec limit. That’s a sensible start — most operational questions really are “what’s the trend” or “are we in spec.” But defaults harden into habits, and the habit hides the questions a line chart answers badly. A line of “bitterness over the last 20 batches” tells you bitterness is roughly steady; it does not tell you whether batch 18 still tastes like your flagship, whether a slow creep has begun that’s too small to see batch-to-batch, or where the 8% extract you lost actually went.
Start from the question, then pick the chart
The whole discipline of good brewing visualization is this inversion: name the question precisely, then choose the chart. Four questions recur in every brewery and each has a natural, underused answer:
- “Does this batch match its brand profile?” — not “is it in spec on each parameter” but “does the shape of its sensory and analytical profile match the target.” A radar/profile chart against a target band shows conformance as a shape you recognise at a glance. This is the flagship of the series — true-to-target tasting.
- “Is something slowly drifting?” — a creep too small to trip a control limit but real over twenty batches. CUSUM and EWMA charts are built precisely to surface slow drift early — the SPC the basic chart misses.
- “How does flavour change as it ages?” — a question about trajectories, not snapshots. Small multiples and trajectory plots show many batches’ staling paths together — shelf-life visualization.
- “Where do my extract, water and energy go?” — a question about flows and losses. A Sankey diagram makes the whole brewhouse balance visible in one picture — seeing the losses.
Why this matters more than chart polish
A chart that answers the wrong question beautifully is still the wrong chart. The brewer’s advantage here is the same one that runs through this whole blog: you know which question actually matters on the floor. Pairing that judgement with the right visualization is what turns a dashboard from decoration into a tool people use — the difference between a dashboard that lives and one that dies. The tools (Power BI, Tableau, a spreadsheet, occasionally a little Python) are rarely the constraint; knowing the chart exists is.
Where this breaks
The honest section. More chart types is not better dashboards — a radar here and a Sankey there can become novelty clutter; each chart in this series earns its place only against a specific question, and a plain line chart beats a fancy one whenever the question is genuinely “what’s the trend.” Some of these need the right data first — a true-to-target radar needs a defined target profile; a Sankey needs measured losses, not estimates; no chart conjures data you haven’t collected. Pretty can mislead — a radar’s shape exaggerates or hides depending on axis order and scaling, and a Sankey can imply precision you don’t have. And the audience matters — a CUSUM chart is powerful and unfamiliar; ship it with a one-line “what am I looking at” or the floor will distrust it, exactly like any unfamiliar instrument.
The bottom line
Brewing dashboards underuse visualization because they default to the line and the control chart, which answer “trend” and “in spec” and little else. Four recurring brewing questions — brand conformance, slow drift, ageing trajectory, and flows/losses — have natural, underused charts: radar, CUSUM/EWMA, trajectories and Sankey. The series takes each in turn, starting with the one you asked about: true-to-target tasting. Pick the chart for the question, ground it in real data, and label the unfamiliar ones — and your dashboard starts answering things the line chart never could.
Frequently asked questions
What data visualizations should a brewery use beyond control charts? Control and line charts answer “is this batch in spec”, but brewing has questions they can’t show well: “does this batch match its brand profile” (radar/profile charts), “is a value slowly drifting” (CUSUM and EWMA charts), “how does flavour change over weeks of ageing” (trajectory and small-multiple plots), and “where do my extract, water and energy go” (Sankey diagrams). Match the chart to the question, not the other way round.
How do I choose the right chart for brewing data? Start from the question, not the chart library. Comparison to a target profile wants a radar or deviation chart; slow drift wants CUSUM or EWMA; change over time across many batches wants small multiples or trajectories; flows and losses want a Sankey. A line chart is the right answer surprisingly often — but it’s the wrong default for these four questions.
Do brewers need special software for these visualizations? No. Most can be built in Power BI, Tableau or even a spreadsheet for radar and CUSUM; Sankey and some trajectory plots may need a specific visual or a little Python. The constraint is rarely the tool — it’s knowing the chart exists and which brewing question it answers, which is what this series is about.