I used to rely on gut feeling to decide whether my clients were about to hit a cash squeeze. Over the years I realised that the most reliable early‑warning signals live in the accounting data we already have — invoices, bank feeds, payroll and supplier bills. The trick is turning that raw data into a simple, repeatable management dashboard that highlights cashflow risks before they become urgent.
Why a simple dashboard matters
Complex BI tools are great, but for most micro‑businesses and small teams I work with, a compact dashboard with a handful of actionable metrics is far more useful. It gives you a quick, honest view of cashflow health, supports better decisions (like delaying discretionary spend or chasing overdue invoices) and reduces the stress of month‑end surprises.
My aim when building dashboards for clients is always the same: make the dashboard quick to update, easy to understand, and tightly focused on the few indicators that predict short‑term cash problems.
What to include — the essential KPIs
These are the metrics I include in every cashflow dashboard. They’re simple to extract from common accounting systems (Xero, QuickBooks, FreeAgent) or spreadsheets.
- Current cash balance — actual bank balance(s) across your trading accounts.
- Net cash movement (last 30 days) — money in minus money out to show momentum.
- Cash forecast (next 30 days) — expected inflows and outflows from invoices, bills, payroll and recurring expenses.
- Outstanding receivables (Aged receivables) — grouped into 0–30, 31–60, 61+ days.
- Upcoming bills and scheduled payments — supplier bills and known direct debits in the next 30 days.
- Days cash runway — how many days you can cover average daily cash outflow with current balances.
- High‑risk customers or invoices — large invoices overdue or customers with repeated late payments.
Where to get the data
If you use a cloud accounting package, most of these numbers are accessible through built‑in reports or the API. I regularly pull data from:
- Xero — great for bank feeds, aged receivables and payment schedules.
- QuickBooks Online — easy cash and sales reports.
- FreeAgent — useful for freelancers and contractors.
- Bank CSV exports — if you don’t have bank feeds.
- Payroll reports — for upcoming wages and PAYE liabilities.
If you prefer spreadsheets, you can export bank statements and aged receivables, then use simple formulas to build the metrics. For teams with more time or data volume, connecting to Google Sheets via the accounting tool’s export, or using an ETL connector into Power BI / Looker Studio, is helpful.
How I build the dashboard (step‑by‑step)
Here’s the practical workflow I use when I create a simple dashboard for a client. You can replicate this in Excel, Google Sheets or a lightweight BI tool.
- Step 1: Pull current balances — snapshot bank balances from the accounting system or bank CSV.
- Step 2: Calculate net cash movement — sum receipts and payments for the last 30 days.
- Step 3: Build a 30‑day cash forecast — list expected receipts (invoices due, forecasted sales) and scheduled payments (bills, payroll, tax). Use conservative timing for receipts (assume a few days delay).
- Step 4: Age receivables automatically — group invoices into 0–30, 31–60, 61+ day buckets and flag invoices overdue more than 30 days.
- Step 5: Compute days cash runway — divide current balance by average daily cash outflow (typically last 90 days outflow / 90).
- Step 6: Add risk flags — large upcoming payments exceeding a % of balance, customers with repeat lateness, or a forecast negative balance within 30 days.
- Step 7: Create visual cues — traffic lights, trend arrows, and a small table of the top 5 overdue invoices and next 5 bills.
Example: a compact dashboard layout
Keep the layout to a single screen or printable sheet. I like a three‑column approach: cash at a glance, short‑term forecast, and actions.
| Left (At a glance) | Middle (Forecast & trends) | Right (Actions & risks) |
|---|---|---|
| Current cash: £12,450 Last 30 days net: +£2,300 Days cash runway: 28 | 30‑day forecast: Opening balance £12,450 Receivables: 0–30: £4,200 | 31–60: £1,800 | 61+: £3,400 | Top actions:
|
Useful formulas and quick tricks
Here are a few simple formulas I use in Google Sheets / Excel:
- Days runway = Current cash balance / (Average monthly cash outflow / 30)
- Projected balance = Current cash + Expected inflows (30 days) − Expected outflows (30 days)
- Use VLOOKUP / INDEX‑MATCH or the invoice status export to build aged receivables automatically.
Quick tricks:
- Apply conditional formatting to the projected balance — red if it goes negative within 30 days, amber if runway is less than 14 days.
- Keep the aging buckets broad (0–30 / 31–60 / 61+) — too many buckets make the dashboard noisy.
- Build one tab for raw data and one tab for the dashboard. That way you can refresh the raw data without breaking the layout.
How often to update and who should see it
For most businesses, a weekly refresh is ideal — it’s frequent enough to catch issues but not so frequent it becomes noise. If you run tight margins or seasonal cash cycles, update daily or connect the dashboard to live feeds in Xero / QuickBooks.
Share the dashboard with your bookkeeper and the business owner. If you have a small team, make a short weekly meeting (15 minutes) around the dashboard to agree immediate actions — chase invoices, delay spend or apply for short‑term finance.
Examples of actions the dashboard prompts
- Initiate a payment plan with a large overdue customer instead of writing off revenue.
- Postpone a discretionary purchase until the forecasted negative day passes.
- Contact your bank early if runway falls below a critical threshold — you’ll get better options if you give yourself time.
- Switch suppliers or negotiate better payment terms based on predictable outflows.
If you’d like, I can create a reusable Google Sheets template based on this structure or show you how to connect Xero/QuickBooks to Looker Studio for a live dashboard. I’ve built both lightweight spreadsheet dashboards and simple Looker Studio reports for clients — the right approach depends on how hands‑on you want to be and whether you need live data.