Operations analytics overview

Operations analytics turns the data recorded in the shift log into numbers, charts and reports — with no one copying anything into Excel. What the shifts write down every day (readings, operating modes, events) shows up here: monthly availability, production trends, shift comparisons — and all of it as a PDF, by email, on a schedule.

The module is a separate, paid add-on. If you don’t see “Analytics” in the menu, the screen says so plainly: “The Analytics module is not enabled.” — your recorded data is kept either way, and once the module is enabled the history shows up immediately, retroactively.

Why it exists

Keeping the shift log asks for work from the shifts — every day, every shift. This module is where that work pays back: the other modules collect data, this one consumes it.

• Zero new process. Nobody needs training, and there is no waiting weeks for “enough data to accumulate”: the module computes over all past periods on the day it is enabled, because a metric is computed from the diary at display time — not from pre-stored numbers.
• One shared namespace. The module does not care where a number came from: diary element fields, meter-reading chain differences, events and classified operating modes are all the same kind of datapoint. Whatever has become a datapoint can go into a formula — you can analyse anything against anything, not just the built-in availability template.

What it consists of

Overview (dashboard)

A view built from tiles: a big number (KPI), trend, table, ranking, calendar, scatter. You can build a tile from any diary datapoint — the built-in availability view is just one template among many possibilities.

Calculated metrics

Ratios, specific values or differences derived from existing metrics (for example production / energy use). With a live preview, computed retroactively as well.

Recipes

Classifying operating modes into layers (mechanical · operational · external cause) — this is what produces layered availability (MA · OA · OSF).

Export

Any metric, any period, with selectable resolution and breakdown (shift, plant) — as CSV or Excel. A frequently used setup can be recalled as a saved export.

Scheduling

The selected view goes out as a PDF by email on its own — daily, weekly or monthly. The “Dispatch log” shows afterwards when, to whom, and exactly which PDF went out.

PDF view

What you see on screen becomes a document in one click: the same numbers, from the same source.

What it looks like

A tile is more than a number: the target, the change against the previous period and the small trend line (sparkline) together tell you whether you are on track:

A KPI tile: under the big number, the target bar (is it met?), the change against the previous period, and the layered availability rows.

The trend tile shows the same metric over time — the resolution follows the page’s period (year → monthly, month → daily):

Daily production trend for one month. “Open source” on every tile takes you to the diary rows behind the number.

Every number can be clicked back to its source

Every tile has an “Open source” link: it takes you to the diary rows behind the metric — day, shift, plant, value and who recorded it. No number “comes from somewhere”: you can always see what it was built from.

Who can do what

• Viewing analytics:view — opening views, numbers and the PDF.
• Managing analytics:manage — editing views, setting metrics and targets, scheduling, export.

Your admin assigns these permissions to roles; if a tab doesn’t appear for you, this is the most common reason.

Related

Why does the number differ from the old Excel report?Two ways of counting outages that span a period boundary — and why ours is the more accurate one.