Understanding Analytics

BayWise Scheduler analytics gives you a factual view of how the workshop is performing. This guide explains what the numbers mean in workshop terms and how to use them to make better operational decisions.

Who can access analytics: Member, Location Manager, Org Admin, Account Owner.

What analytics is for

The numbers in analytics are most useful when you ask “what should I do differently?” rather than just reading them as a report.

A utilisation figure of 62% on a Tuesday is not just a number — it tells you the workshop had capacity available that day that was not filled.
A technician efficiency of 55% on heavy jobs but 92% on light jobs suggests a skill mismatch, not a performance problem.
A promise accuracy of 71% means roughly 3 in 10 customers experienced a late delivery last month.

The goal of analytics is to catch these patterns early, before they become persistent problems.

Accessing analytics

Click the Analytics tab in the main navigation (left sidebar or bottom tab bar).

Analytics is organised into six sections, each accessible from the Analytics landing page:

Overview — daily completions and financial summary
Bays — bay-level utilisation and trends
Techs — per-technician productivity and revenue
Efficiency — estimation accuracy analysis
Delays — promise adherence and late delivery tracking
Services — service frequency and category distribution

All sections support time period filtering: DAY, WEEK, MONTH, or CUSTOM date range.

A summary row at the top of each section displays aggregate metrics for the selected period: total jobs, completed jobs, total revenue, total cost, gross profit, and average cycle time.

Overview

The Overview section is the starting point for performance review. It shows:

Daily completions trend — a sparkline chart showing the number of jobs completed per day across the selected period. Use this to spot volume patterns (busy days, slow days, week-over-week trends).
Financial summary — total revenue, total cost, gross profit, and average cycle time for the period. These are the headline numbers for any operational review or management report.

How to use it: Open Overview at the end of each day or the start of the next morning to get an immediate read on throughput and financial performance. Compare the current period to the previous equivalent period to identify trends.

Bays

The Bays section breaks down utilisation at the individual bay level.

Average bay utilisation by bay — a bar chart showing each bay’s utilisation percentage for the period. Quickly identify which bays are consistently busy and which have spare capacity.
Utilisation trend — a line chart showing how overall bay utilisation has changed across the period. Useful for spotting declining or improving capacity usage.
Peak bay identification — highlights the bay with the highest utilisation. This bay is most likely to experience schedule pressure and overrun risk.
Idle bays detection — flags bays that had no active jobs for significant portions of the period. These represent unused capacity.

How to use it: If one bay consistently shows low utilisation, investigate whether it has equipment limitations, is assigned to a low-demand service category, or is being overlooked during scheduling.

Techs

The Techs section provides per-technician performance metrics.

Productivity ranking — hours worked per technician, ranked from most to least. Shows who is carrying the heaviest workload.
Revenue per technician — how much revenue each technician generated during the period.
Profit per technician — revenue minus the cost of that technician’s time, with an efficiency percentage showing how productively their time was used.

How to use it: Compare revenue and profit figures alongside hours worked. A technician with high hours but low revenue may be assigned to low-value work or working slower than estimated. A technician with moderate hours but high revenue is being deployed effectively.

A technician who shows low efficiency on complex bodywork but high efficiency on mechanical jobs is not performing poorly overall — they may be assigned to work that does not match their skill level. Check their skill profile and compare to their assignment history.

Efficiency

The Efficiency section analyses how accurate your service duration estimates are compared to actual job times.

Overall estimation accuracy — the ratio of actual time to planned time across all completed jobs. A figure of 100% means estimates matched reality perfectly. Below 100% means work was completed faster than estimated. Above 100% means work took longer.
Accuracy trend — a line chart showing how estimation accuracy has changed over the period. Improving accuracy means your catalog durations are becoming better calibrated.
Per-service accuracy divergence — a breakdown by service type showing which services are consistently overestimated or underestimated. This is the most actionable metric in the section — it tells you exactly which catalog durations need adjustment.

How to use it: If a specific service type consistently shows actual times 30% longer than estimated, update the catalog duration for that service. Accurate estimates improve scheduling density, promise accuracy, and technician trust in the system.

Delays

The Delays section tracks whether the workshop is meeting its customer commitments.

Promise adherence rate — the percentage of delivered jobs that were completed on or before the promised time. This is the single most important customer experience metric.
Late deliveries — a list of jobs delivered after their promise time, showing the delay in hours for each. Use this to identify patterns — are late deliveries concentrated on a specific day, service type, or technician?
Currently overdue steps — steps that are past their expected completion time right now. This is a live action list for the current day.

How to use it: If promise adherence drops below 80%, investigate root causes systematically. The most common are underestimated durations, scheduling overcommitment, and parts delays. Cross-reference with the Efficiency section to determine whether estimation accuracy is a contributing factor.

Services

The Services section shows the mix of work flowing through the workshop.

Service frequency bar chart — how many times each service type was performed during the period. Identifies your most common and least common services.
Category distribution (pie chart) — the proportion of total jobs by service category (e.g., Maintenance, Repair, Body Work, Diagnostic). Shows the overall job mix at a glance.
Job category mix — a detailed breakdown of job volume by category, useful for capacity planning and staffing decisions.

How to use it: If one service category dominates and another is underrepresented relative to demand, consider whether scheduling or technician skill profiles are creating a bottleneck. Use this data when planning staffing levels, bay configurations, and service menu pricing.

Filtering by period

Use the period selector at the top of any analytics section to adjust the reporting window:

DAY — single day view (today, yesterday, or a specific date)
WEEK — rolling seven-day window
MONTH — rolling thirty-day window or calendar month
CUSTOM — pick any start and end date

→ See Filter Analytics by Period for step-by-step instructions.

Common questions

Utilisation shows 0% even though jobs were running. Check that technicians clocked in during the period. Utilisation is calculated against bay-time with active assigned technicians. If clock-in was not recorded, the calculation may be affected.

A technician is missing from the Techs section. Only technicians who had at least one active job step during the selected period appear. Technicians who were scheduled but had no active steps will not appear.

Can I export analytics data? Export functionality is on the product roadmap. Currently, analytics is view-only within the app.