📊 From Hive Journal to KPIs

About this simulation

Every inspection a beekeeper writes down — queen seen, brood pattern, stores, mite count, temperament — is a raw data point. On its own, a single note in a paper journal tells you little. Structured and aggregated across an apiary and a season, those same notes become key performance indicators (KPIs): honey yield, overwintering survival, mite load, inspection frequency. This scene shows that pipeline in 3D — a pile of journal cards on the left streaming through a processing hub into a live bar-chart dashboard on the right.

How it works

• KPI metric — choose which indicator drives the bar heights and colours.
• Hives tracked — how many colonies feed the dashboard; each gets its own bar and its own baseline performance.
• Record completeness — the share of inspections actually logged. Low completeness means fewer data particles flow through the hub, more red "missing record" cards in the pile, and noisier, less trustworthy bars — a KPI is only as good as the records behind it.
• Simulated week — scrubs through a 52-week season; honey builds toward a summer harvest, mite load climbs in late summer, and survival risk grows over winter. Press play to watch it unfold automatically.

Reading the bars

• Bar height is the current KPI value for that hive; colour shows whether it's on target (green), worth watching (amber), or needs action (red).
• Thresholds flip direction for metrics where lower is better, such as mite load.

Did you know?

Beekeeping associations that run structured recording schemes typically report far better early detection of disease and queen failure than beekeepers relying on memory alone — the value is almost entirely in consistent, comparable records, not in any single clever measurement.