How dashboards and widgets work
Where analytics data comes from, how widgets turn it into answers, and what dashboards are for.
Tooling Metrics collects data across the tool lifecycle automatically — every item movement, every cost posting, every runtime entry, every condition change. None of it requires separate data entry: by the time you open Analytics, the data is already there because the shopfloor documents that created it (pick lists, transfers, return lists, receipts) were validated as part of normal work. The Analytics module exists to make that data readable.
Widgets answer one question each
Section titled “Widgets answer one question each”A Widget is a configured data view with three parts:
- A source — the record type being read (Item, Tool, Cutting Edge, Machine, Storage Device, Warehouse, Purchase Order, Purchase Order Line, Usage Cost Line, or Tool Life)
- Columns — the fields read from that source, each with its own function: show the raw value, group by it, or aggregate it (sum, count, average, or — for a date field — group by day, week, month, quarter, or year)
- A Type — how the result is presented: Metric (field values from one Machine, Storage Device, or Warehouse, as cards), Chart, or Table
A widget is the unit of meaning: one widget answers one question, such as “how much usage cost did each machine post this month?” (Usage Cost Line, machine grouped, value summed, created date grouped by month.) If you find yourself wanting a widget to answer two questions, you want two widgets.
Because the source, columns, and Type are independent choices, the same underlying data can serve different jobs. Usage Cost Line grouped by machine tells the production manager which process is expensive; the same source grouped by item tells the purchaser which consumables dominate spend.
Dashboards answer a role’s questions together
Section titled “Dashboards answer a role’s questions together”A Dashboard solves a specific monitoring problem by putting several related widgets on one screen. Dashboards are designed around a job, not around a module: a production manager tracks daily shopfloor status; a purchaser manages replenishment cycles; an inventory controller does weekly stock checks. Each role needs different widgets because each asks different questions of the same data.
Whether you see someone else’s dashboard in the Dashboards list follows your organization’s Analytics permission role, not a setting you toggle per dashboard: Admin and Manager roles see every dashboard in the organization; a User role mainly sees the dashboards they created. This lets everyone experiment freely without cluttering the view for people who only need the dashboards built for their role.
Templates are starting points
Section titled “Templates are starting points”A dashboard can be marked as a Template by a site admin. Templates appear in the gallery you see when you start a new dashboard, alongside the option to start from a blank one. Picking a template duplicates it immediately into a dashboard you own — it’s a starting point, not a fixed report, so adjust its widgets freely once you’re in your own copy.
What widgets cannot do
Section titled “What widgets cannot do”Widgets summarize recorded data — they do not predict, and they do not alert in real time. A dashboard is something you review on a rhythm: daily before the morning meeting, weekly for the stock check. If you need proactive notification rather than periodic review, service thresholds on serialized items are the right tool — they trigger automatically the moment a usage threshold is crossed. See Track a serialized item.
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