Welcome to the FV Metrics Dashboard
What Is This?
The FV Metrics Dashboard is an automated reporting system for Fairview Vehicles. It takes the booking data from the Daily Hire spreadsheet on SharePoint, analyses it, and presents it as a live, interactive web dashboard at metrics.fvapp.co.
You don't need to do anything to keep it running — the system downloads the latest data automatically throughout the day and updates the dashboard. It also sends a daily email summary with an Excel attachment at 11 PM each evening.
Where Does the Data Come From?
All data on this dashboard comes from a single source: the Daily Hire.xlsx spreadsheet stored on SharePoint. This is the same spreadsheet the team uses day-to-day. The system downloads a fresh copy at each scheduled refresh, processes all bookings, and updates every section of the dashboard.
How Often Is It Updated?
The dashboard refreshes five times a day:
| Time | What Happens |
|---|---|
| 8:00 AM | First refresh of the day — dashboard updated with latest spreadsheet data |
| 12:00 PM | Midday refresh — captures any morning bookings |
| 3:00 PM | Afternoon refresh |
| 6:00 PM | Evening refresh |
| 11:00 PM | Full daily run — dashboard update plus email report with Excel attachment |
Between refreshes, the data shown is a snapshot from the last update. The header bar shows when the dashboard was last updated.
The Eleven Dashboard Sections
The dashboard is organised into eleven sections spread across four tabs. Use the sidebar on the left to learn about each one in detail.
| Tab | Section | In a Nutshell |
|---|---|---|
| Today | Daily Snapshot | Today's headline numbers — bookings, revenue, vehicles on hire, deposits |
| Forward Activity | What's happening tomorrow — pickups, returns, and upcoming unpaid bookings | |
| Alerts & Unpaid | Conditional panels — only visible when overbookings or unpaid items exist | |
| Performance | MTD by Branch | This month's performance by branch, compared to last month and the same month last year |
| YTD by Branch | Year-to-date performance by branch, compared to the same period last year | |
| Revenue Trend | Charts showing daily and weekly revenue patterns over time | |
| Forward | Forward Bookings | The pipeline — bookings confirmed for the next 7, 30, and 90 days |
| Forward Utilisation | Day-by-day heatmap showing how fully booked each vehicle group is over the next 28 days | |
| Booking Buildup | For each month's hire days, when were they booked? Shows how far ahead bookings are placed | |
| Breakdown | Revenue Composition | Where the money comes from — broken down by the 8 revenue streams |
| Booking Channels | How bookings are coming in — RC, MP, Other Broker, or Direct | |
| Fleet Utilisation | How well the fleet is being used — busiest and idlest vehicles |
Reading the Dashboard
Before diving into the individual sections, here's how to navigate the dashboard and interpret the visual cues used throughout.
Tabs and Sections
The dashboard is organised into four tabs shown as a pill-shaped bar near the top of the page:
| Tab | What's Inside |
|---|---|
| Today | Today's snapshot, tomorrow's activity, pipeline, alerts, and unpaid bookings |
| Performance | MTD by branch, YTD summary, revenue trend charts |
| Forward | Forward bookings, utilisation heatmap, booking buildup |
| Breakdown | Revenue composition, vehicle groups, booking channels, fleet utilisation |
Tap any tab to switch groups. The KPI cards and pace indicator at the top of the page are always visible regardless of which tab you're on.
Expanding and Collapsing Sections
Within each tab, individual sections are shown as collapsible panels. Tap the section header to expand or collapse it. A small chevron (▼) on the right indicates whether the section is open or closed.
Use the "Expand all" and "Collapse all" links above the sections to open or close every panel in the current tab at once. This is useful when you want to quickly scan all data or focus on just one section.
Arrows and Colour Coding
Whenever the dashboard compares a number to a previous period, it uses coloured arrows to show the direction of change:
The μ Symbol (Averages)
Throughout the dashboard, you'll see the Greek letter μ (pronounced "mew"). This simply means average. For example:
| Label | What It Means |
|---|---|
| μ£/Booking | Average revenue per booking |
| μ£/Day | Average revenue per day |
| μ£/Paid Day | Average revenue per paid rental day |
| μ Days/Booking | Average hire duration (in days) per booking |
| μ Vehicles OH | Average number of vehicles on hire at any given time |
Currency and Number Formatting
All monetary values are shown in pounds sterling (£) with two decimal places (e.g., £4,250.00). Whole numbers such as booking counts use commas for thousands (e.g., 1,250). Percentages always show one decimal place with a sign: +12.5% or −3.2%.
Comparison Periods
The dashboard uses two main comparison methods:
| Abbreviation | Meaning | Example |
|---|---|---|
| MoM | Month-on-Month | February 2026 compared to January 2026 |
| YoY | Year-on-Year | February 2026 compared to February 2025 |
The MTD section shows both MoM and YoY comparisons. The YTD section shows only YoY (current year vs. the same period last year).
Revenue Attribution
Stale Data Warning
If the dashboard data is more than 6 hours old, you'll see an amber banner at the top of the page warning that the data may be stale. This can happen if the scheduled refresh failed. Contact your administrator if this persists.
Daily Snapshot
The Snapshot is the first thing you see on the dashboard. It gives you an immediate overview of today's activity and the current state of the fleet.
Headline Cards
Four cards appear at the top of the dashboard:
| Card | What It Shows | Data Source |
|---|---|---|
| Vehicles On Hire | How many unique vehicles are currently out with customers (pick-up date has passed, drop-off date hasn't yet) | Pick-up and drop-off dates in the spreadsheet |
| Today's Revenue | Total revenue from bookings created today, plus the number of new bookings | Booking date (Column A) = today; revenue from "Paid to Us" (Column AF) |
| Avg Booking | Average value and average duration of today's new bookings | Calculated from today's bookings |
| Outstanding Deposits | Number of bookings where the vehicle has been returned but the deposit hasn't been given back yet | Drop-off date has passed, "Deposit Returned" (Column AG) is blank, and a deposit was collected (Column AC > 0) |
Pace Indicator
The Pace Indicator answers the question: "How is today shaping up compared to the monthly average?"
It takes today's revenue from bookings that are picking up today and compares it to the average daily pick-up revenue so far this month. If the pace is positive (green), today's pickups are generating more revenue than the monthly daily average. If negative (red), it's a quieter day.
Today by Branch
A branch-by-branch breakdown of how many bookings were created today and their total revenue. This tells you which branches had the busiest booking activity for the day.
Alerts
The Alerts panel flags data quality issues in the spreadsheet. Common alerts include:
- Blank pick-up location — A booking doesn't have a pick-up location entered, so it can't be assigned to a branch
- Unknown branch — The pick-up location didn't match any known branch, so it was classified as "Unknown"
- On-hire mismatch — The number of active bookings doesn't match the number of unique vehicles, suggesting duplicate or unclosed bookings
- Blank booking date — A row in the spreadsheet is missing its booking date
Alerts are informational — they help the team keep the spreadsheet clean. Fixing the underlying data will clear the alert at the next refresh.
Forward Activity
This section looks ahead to help you prepare for tomorrow and flag any upcoming issues.
Tomorrow's Activity
A branch-by-branch table showing:
| Column | Meaning |
|---|---|
| Pickups | Number of vehicles being collected by customers tomorrow |
| Returns | Number of vehicles being returned tomorrow |
| Net | Pickups minus Returns — a positive number means the branch will have more vehicles out; a negative number means more are coming back |
This is useful for staffing and vehicle preparation — a branch expecting five pickups tomorrow needs vehicles cleaned, checked, and ready.
Revenue Pipeline — Tomorrow
Shows how much revenue is attached to tomorrow's pickups, broken down by branch. It also flags which of those bookings are unpaid, so the team can chase payment before the vehicle goes out.
Unpaid Bookings — Next 7 Days
This appears only when there are unpaid bookings with a pick-up date within the next seven days. It shows the count and total rental days by branch, giving the team a clear list of bookings that need payment attention before the vehicles leave.
MTD by Branch
MTD stands for Month-to-Date — it covers everything from the 1st of the current month up to the report date.
What It Shows
A table of every branch with their performance for the current month so far. The key columns are:
| Column | Meaning |
|---|---|
| Bookings | Number of bookings with a pick-up date in this month |
| Revenue | Total "Paid to Us" revenue for those bookings |
| Paid Days | Total rental days for paid bookings (from the spreadsheet's Rental Days column) |
| Total Days | Total rental days calculated from pick-up to drop-off for all bookings (including unpaid) |
| μ£/Booking | Average revenue per booking |
Comparisons
Each metric is compared against two benchmarks, shown as coloured percentage changes:
- vs Prior Month — How this month compares to the same point in last month (MoM)
- vs Same Month Last Year — How this month compares to the same month a year ago (YoY)
MTD Summary
Above the branch table, you'll see headline MTD figures for the whole business — total bookings, total revenue, and key averages — with their MoM and YoY change indicators.
YTD by Branch
YTD stands for Year-to-Date — it covers everything from 1 January of the current year up to the report date.
What It Shows
The same branch-level breakdown as MTD, but over the entire year. Additional columns include:
| Column | Meaning |
|---|---|
| μ Vehicles OH | Average number of vehicles on hire across the year — gives a sense of each branch's typical fleet usage |
| μ£/Paid Day | Average revenue earned per paid rental day — a measure of how much each hire day is worth |
Comparison
YTD figures are compared Year-on-Year only — this year vs. the same period last year. This gives a clear picture of whether the business is growing, and which branches are driving that growth.
Revenue Trend
This section uses charts to show how revenue has moved over time, making it easy to spot patterns, peaks, and dips.
MTD Daily Line Chart
A line chart showing daily revenue for the current month. It plots four lines:
- This month (solid line) — Day-by-day revenue so far
- Prior month (dashed) — Last month's daily revenue for comparison
- Same month last year (dotted) — The same month a year ago
- Average line — The daily average for the current month, shown as a flat reference line
This makes it easy to see whether the current month is running ahead of or behind recent benchmarks.
YTD Weekly Bar Chart
A bar chart showing weekly revenue totals for the year. Two series are shown side by side:
- This year — Weekly totals for the current year
- Last year — The same weeks last year
This is useful for spotting seasonal trends and understanding whether weekly performance is improving over time.
Key Performance Indicators
Alongside the charts, you'll see highlighted KPIs including the best day (highest single-day revenue this month), the worst day, and the current streak (consecutive days above or below the daily average).
Forward Bookings
The pipeline view — showing confirmed bookings that haven't happened yet.
What It Shows
Three time horizons, each broken down by vehicle group:
| Window | Meaning |
|---|---|
| Next 7 days | Bookings with a pick-up date in the coming week — these are almost certain to happen |
| Next 30 days | The next month's pipeline — useful for medium-term fleet planning |
| Next 90 days | The longer-term forward book — shows future demand and helps with strategic decisions |
For each window, you'll see the number of bookings and their total expected revenue, broken down by vehicle group (e.g., SWB, LWB, Luton, Tipper).
Combined Sources: DH + Surprice
The forward bookings numbers combine data from two sources: the Daily Hire (DH) system and the Surprice franchise. Both systems share the same vehicle group codes, so their bookings are merged into a single view.
When Surprice data is present, you can hover over any number to see a tooltip showing the breakdown — how many bookings come from Daily Hire and how many from Surprice. The headline figure is always the combined total.
Why It Matters
Forward bookings tell you what's coming. A strong forward book means the fleet is likely to stay busy. A thin pipeline may signal a need for more marketing or pricing adjustments. Comparing the 7-day and 30-day windows over time shows whether bookings are building or softening.
Forward Bookings Utilisation
The utilisation heatmap gives you a visual, day-by-day picture of how fully booked each vehicle group is over the next 28 days.
How to Read the Grid
The grid has one row per vehicle group and one column per day. Each cell shows two numbers separated by a pipe: booked | available. For example, "3 | 5" means 3 vehicles are booked out of 5 available in that group on that day.
The cells are colour-coded by utilisation percentage:
| Colour | Utilisation | Meaning |
|---|---|---|
| Green shades | 0–49% | Good availability — plenty of vehicles free |
| Yellow/Amber | 50–79% | Moderate — availability is tightening |
| Red shades | 80–99% | High utilisation — very limited availability |
| Dark Red (pulsing) | 100%+ | Overbooked — more bookings than available vehicles |
Weekend & Bank Holiday Shading
The column headers use visual cues to distinguish different types of days:
| Header Style | Meaning |
|---|---|
| Sat 22 | Weekend — Saturday or Sunday, shown with a grey header and thicker column borders |
| Mon 05 | Bank Holiday — English bank holiday, shown with an amber/gold header and thicker column borders |
This makes it easy to spot patterns — for example, whether weekends are under- or over-utilised compared to weekdays, or whether a bank holiday is causing a demand spike.
Combined Sources
Like the Forward Bookings section, the utilisation grid combines Daily Hire and Surprice bookings. When Surprice data is present, hovering over a cell shows the split between DH and Surprice bookings for that group and day.
Where Does "Available" Come From?
The "available" number comes from the Vehicle Counts sheet in the source spreadsheet. This records the total number of vehicles in each group. If the Vehicle Counts sheet is missing or incomplete, the utilisation section won't appear — it requires fleet counts to calculate percentages.
Booking Buildup
This heatmap answers a simple but powerful question: for each month's hire days, when were they booked? It reveals how far in advance bookings are being placed and how each future month's utilisation is building up over time.
How It Works
Each booking's hire days are split across the calendar months they actually fall in. A 10-day booking starting 28 January contributes 4 days to January and 6 days to February. Each portion is then attributed to whichever month the booking was originally created.
This means the grid shows hire days, not booking counts — giving a more accurate picture of how much capacity is committed for each month.
How to Read the Grid
The grid has one row per future usage month (12-month forward view from the current month) and one column per booking month. Each cell shows how many hire days falling in that usage month were booked during that booking month.
Cells are colour-coded by intensity — darker blue means more hire days. Greyed-out cells in the upper-right triangle are impossible combinations (you can't book in a month that hasn't happened yet).
| Element | Meaning |
|---|---|
| Row labels (left) | Usage month — the month the hire days fall in |
| Column headers (top) | Booking month — the month the booking was created |
| Cell value | Number of hire days for that usage month booked in that booking month |
| Total column (right) | Total hire days committed for that usage month across all booking months |
| 12+ mo | Hire days from bookings placed more than 12 months before the usage month — grouped into a single bucket |
Interacting with Cells
On desktop, hovering over a cell highlights it and shows a tooltip bar with the full context (booking month, usage month, and hire day count). On mobile, tap a cell to select it — tap again or tap elsewhere to dismiss.
What to Look For
- Diagonal pattern: Most bookings naturally cluster near the diagonal (booked close to the usage month). A healthy spread along the row suggests good forward planning.
- Thin rows: A future month with very few total hire days may need attention — it could signal a gap in the pipeline.
- Heavy current-month column: If most days are booked in the same month they're used, bookings are arriving last-minute rather than building steadily.
Revenue Composition
This section breaks total revenue down into its eight component streams, showing where the money actually comes from.
The Eight Revenue Streams
| Stream | What It Covers |
|---|---|
| Hire Charge (incl VAT) | The core vehicle hire fee — the base cost of renting the vehicle |
| Insurance | Insurance charges collected from the customer |
| Additional Hours/Days | Charges for overruns — when a customer keeps the vehicle longer than booked |
| Additional Rental | Extra rental charges collected at the Fairview branch |
| Additional Driver | Fees for adding extra named drivers to the booking |
| CDW / Standard / Premium | Collision Damage Waiver — optional damage protection collected at the branch |
| Damage Charges | Charges levied when a vehicle is returned with damage |
| Additional Charges | Any other miscellaneous charges |
Charts and Tables
You'll see two doughnut charts — one for MTD, one for YTD — showing the proportion each stream contributes. Below each chart is a detailed table with the exact figures.
The total of all eight streams should equal the "Paid to Us" figure. If there's a small discrepancy, the dashboard will display a note explaining the difference.
Booking Channels
This section shows how bookings reach Fairview — whether through broker platforms or direct customers.
The Four Channels
| Channel | How It's Identified |
|---|---|
| RC | Bookings that have an RC broker reference number in the spreadsheet |
| MP | Bookings that have an MP broker reference number |
| Other Broker | Bookings with a different broker reference (not RC or MP) |
| Direct | No broker reference at all — the customer booked directly with Fairview |
The system checks the reference fields in order: RC first, then MP, then Other Broker. If none are filled in, it's classified as Direct.
What You'll See
For each channel, both MTD and YTD:
- Bookings — Number of bookings through that channel
- Revenue — Total revenue from those bookings
- μ£/Booking — Average booking value per channel
This helps identify which channels are generating the most valuable bookings. A channel with fewer bookings but a higher average value may be more profitable than a high-volume, low-value channel.
Fleet Utilisation
This section answers the question: "How well are we using our vehicles?"
Key Metrics
| Metric | Meaning |
|---|---|
| Unique Vehicles | Total number of distinct vehicles that have been hired out this year (identified by registration plate) |
| Paid Days | Total number of paid rental days across the fleet |
| Total Days | Total calculated rental days (including unpaid bookings) |
| μ Days/Vehicle | Average number of hire days per vehicle — higher is better, as it means vehicles are spending more time earning revenue |
Top 10 Vehicles
A ranking of the 10 busiest vehicles by total rental days. This shows which vehicles are the workhorses of the fleet.
Idle Vehicles
A list of vehicles that have been hired out at some point this year but are not currently on hire. These are vehicles that could be generating revenue but aren't. This doesn't necessarily mean they're sitting unused — they may be in for maintenance, between hires, or awaiting reassignment — but the list is a useful starting point for fleet managers to investigate.
Glossary of Terms
A quick reference for the terminology used throughout the dashboard.
| Term | Definition |
|---|---|
| Booking Date | The date a booking was created in the spreadsheet (Column A). Used only for the "new bookings today" count in the Snapshot. |
| Pick-up Date | The date the customer collects the vehicle. This is the primary date used for revenue attribution — all MTD, YTD, and other analytics count revenue on this date. |
| Drop-off Date | The date the vehicle is returned (or scheduled to be returned). |
| Branch | The Fairview branch responsible for the booking, determined by the pick-up location. Current branches include Bray, Battersea, Barking, Kensington, Heathrow, Egham, Milton Keynes, Final Rentals Heathrow, and Final Rentals Battersea. |
| Paid to Us | The total revenue collected for a booking (Column AF in the spreadsheet). This is the sum of all 8 revenue streams. |
| Paid Days | Rental days as recorded in the spreadsheet (Column V). Only populated for paid bookings. Used for revenue-per-day calculations. |
| Total Days (Calc) | Rental days calculated automatically as the number of days between pick-up and drop-off. Computed for every booking, including unpaid ones. Same-day hires count as 1 day. |
| MTD | Month-to-Date — from the 1st of the current month to the report date. |
| YTD | Year-to-Date — from 1 January of the current year to the report date. |
| MoM | Month-on-Month — comparing the current month to the previous month. |
| YoY | Year-on-Year — comparing the current period to the same period one year ago. |
| μ (Mu) | Average. Appears as a prefix throughout the dashboard (e.g., μ£/Booking = average revenue per booking). |
| Pace | Today's pick-up revenue compared to the month's average daily pick-up revenue. A positive pace means today is outperforming the monthly average. |
| On Hire | A vehicle is "on hire" if its pick-up date has passed and its drop-off date hasn't yet arrived. The count uses unique registration plates. |
| Forward Book / Pipeline | Confirmed bookings with a pick-up date in the future. Shown in 7-day, 30-day, and 90-day windows. |
| Revenue Streams | The 8 categories of income: Hire Charge, Insurance, Additional Hours/Days, Additional Rental, Additional Driver, CDW, Damage Charges, and Additional Charges. |
| Channels | The source of a booking: RC (broker), MP (broker), Other Broker, or Direct. |
| CDW | Collision Damage Waiver — optional damage protection the customer can purchase at the branch. |
| Vehicle Group | The type of vehicle: SWB (Short Wheelbase), LWB (Long Wheelbase), XLWB (Extra Long), Luton, Tipper, Dropside, etc. Identified by FV group codes (e.g., DGAV, EDAV) shared across both DH and Surprice systems. |
| Vehicle Counts | A sheet in the source spreadsheet recording the total number of vehicles available per group. Used to calculate utilisation percentages in the Forward Bookings Utilisation heatmap. |
| Utilisation % | The percentage of a vehicle group's fleet that is booked on a given day: (booked ÷ available) × 100. Shown in the Forward Bookings Utilisation heatmap with colour coding. |
| Overbooking | When the number of active bookings for a vehicle group exceeds the number of available vehicles on a given day. Shown with a pulsing red indicator on the heatmap. May resolve through cancellations or reassignments. |
| Surprice | A franchise operation that uses the same vehicle fleet. Surprice bookings are merged into the Forward Bookings and Utilisation sections, with tooltips showing the DH/Surprice breakdown. |
| DH (Daily Hire) | The primary booking system. When the dashboard shows "DH + Surprice" in tooltips, DH refers to bookings from the Daily Hire spreadsheet (as distinct from Surprice franchise bookings). |
| Idle Vehicle | A vehicle that has booking history this year but no active hire covering today. It may be available, in maintenance, or awaiting redeployment. |
| Outstanding Deposit | A booking where the vehicle has been returned but the customer's deposit has not yet been refunded. |
| Alert | A data quality flag — not an error, but something the team should review (e.g., missing location, duplicate vehicles on hire). |
Frequently Asked Questions
Why don't the dashboard numbers match what I see in the spreadsheet?
The most common reasons are timing and attribution. The dashboard uses pick-up date to attribute revenue, while you might be filtering the spreadsheet by booking date. Also, the dashboard only shows data as of the last refresh — if bookings were added after the most recent refresh, they won't appear until the next one.
When does the data refresh?
Five times a day: 8 AM, 12 PM, 3 PM, 6 PM, and 11 PM. The exact time of the last refresh is shown in the dashboard header. Admin users can trigger an immediate refresh using the button in the header.
Why is a booking showing as "Unknown" branch?
The system assigns branches based on the pick-up location field. If the location text doesn't match any known branch pattern (e.g., a typo or an unusual format), the booking gets classified as "Unknown". Correcting the pick-up location in the spreadsheet will fix this at the next refresh.
What does "On-hire mismatch" mean?
This alert appears when the number of active booking records doesn't match the number of unique vehicle registration plates currently on hire. This usually means either: (a) a vehicle appears in two overlapping bookings, or (b) a booking wasn't closed properly when the vehicle was returned. It's worth checking the drop-off dates for the flagged vehicles.
Why is the Pace Indicator blank early in the month?
On the 1st of the month, there's no prior data to calculate a monthly average against. The Pace Indicator needs at least one full day of data from the current month before it can show a meaningful comparison.
Can I see historical data from previous months?
The dashboard always shows current MTD and YTD data. It doesn't store or display past months' dashboards. However, the Revenue Trend section includes comparison lines for the prior month and same month last year. For historical analysis, the daily email's Excel attachment is archived and can be found on SharePoint.
What happens if the spreadsheet is open when the dashboard refreshes?
The system downloads a copy of the spreadsheet from SharePoint — it doesn't interfere with anyone editing the file. There may occasionally be a brief moment where a half-saved entry is captured, but the next refresh will correct this.
Who can access the dashboard?
Anyone with login credentials created by an admin. There are two roles: standard users (can view the dashboard and this guide) and admin users (can also manage users, trigger refreshes, and access the technical Code Wiki).
I've spotted an error — how do I report it?
First, check whether the issue is in the source spreadsheet (incorrect data entry) or in the dashboard's processing. If the spreadsheet data is correct but the dashboard shows something different, contact your system administrator. Fixing data in the spreadsheet will automatically correct the dashboard at the next refresh.