Property Management Dashboard — Portfolio Truth From the Rent Roll You Already Keep

What is a property management dashboard?

A property management dashboard is a single view across the portfolio of the numbers that determine whether the management business — and each landlord's investment — is performing: occupancy rate and void days, rent collected versus rent due, arrears and their ageing, maintenance cost per property, and yield. For an agency managing on behalf of landlords, it is also the raw material for the thing clients judge you on: the periodic report that proves their asset is being looked after.

The data already exists in your property management software — Arthur, Re-Leased, Propertyfile, Jupix, or the long-serving Excel rent roll — and every one of those systems exports CSV or Excel. What the software mostly does not do is analysis. It will tell you the arrears total; it will not tell you that nine tenancies generate 71% of it, or that void periods have been lengthening for two quarters, or that one block's maintenance spend is running far beyond the portfolio norm. Those are analytical questions, and they go unanswered because answering them by hand takes hours per month.

The questions compound as portfolios grow. At thirty units, an experienced manager holds the picture in their head. At three hundred, intuition fails quietly: the slow drift in void days costs real money before anyone perceives it, arrears patterns hide inside an acceptable-looking total, and the landlord whose two properties are both quietly underperforming finds out from their own bank statement — which is how management contracts get lost.

DataHub Pro turns the monthly exports into that missing analysis layer. Upload the rent roll, arrears ledger and maintenance log, and the platform computes occupancy and void trends, runs Pareto analysis on arrears, flags maintenance cost anomalies by property and block, and tracks rent collected against due. Auto Report then generates landlord statements and portfolio reviews as editable Word documents — on schedule, per client, with every figure traceable to the export. For sales-side and investment analytics, see our companion page for real estate.

The reporting problems property managers recognise

Letting agents, block managers and portfolio landlords all hit versions of these:

• Landlord reporting is a monthly production line. Each client wants their statement and commentary. Assembling rent, arrears, voids and maintenance per landlord by hand turns month-end into a multi-day ritual that scales linearly with clients.
• Arrears are managed by total, not by pattern. A stable arrears total can hide churn underneath — old debts written off while new ones form. Without concentration and ageing analysis, chasing effort lands on the wrong tenancies.
• Void periods lengthen invisibly. The occupancy rate looks fine while average void days drift from 18 to 31. Nobody notices a slow trend without a trend line — and void days are pure lost income.
• Maintenance spend has no benchmark. Is £840 per unit per year reasonable? Without per-property comparison and anomaly detection, the block with a failing roof or an overcharging contractor hides inside the total.
• Portfolio questions take a day to answer. "Which of my properties performed worst this year?" from a key landlord means a day in spreadsheets — for an answer the data could surface in minutes.
• Rent-roll analysis happens never. Yield by property, rent versus market drift, renewal timing — classic portfolio analysis that the management workload permanently postpones.

DataHub Pro features mapped to property work

From the platform's 50 analysis tools, these do the heavy lifting for property managers:

Worked example: from rent-roll.csv to three portfolio actions

You upload rent-roll.csv — 280 tenancies with rent due and received, tenancy dates, property and block — plus the maintenance ledger. Three findings come back in minutes:

Auto Report turns the same analysis into each landlord's monthly statement, generated on schedule with every figure traceable to the rent roll. The portfolio review that used to take a weekend now takes a review-and-send.

How it works — three steps, no implementation project

There is no onboarding call, no integration scoping and nothing for IT to install. The workflow is the same whether you are testing on one file or running scheduled reporting across a team:

• 1. Bring your data. Upload an Excel or CSV export from the systems you already use, or connect Google Sheets, SharePoint or Shopify for sources that should stay live. DataHub Pro auto-detects your columns — no template to conform to.
• 2. Run the analysis. The KPI dashboard builds itself on upload. From there, pick from 50 analysis tools — Pareto, cohort, RFM, anomaly detection, variance, what-if, Holt-Winters forecasting — or ask questions in plain English with Ask Your Data, where every answer shows the operations behind it.
• 3. Ship the report. Auto Report turns the analysis into an editable Word or PowerPoint document with charts and AI-written commentary. Schedule it, and the recurring version arrives without you — same method, fresh data, every time.

Plans that scale from a single file to a whole team

• Free — $0, forever. One user, 3 uploads a month, 8 core analysis tools and watermarked PDF export. No AI features, no credit card — but a genuine way to test the workflow on your real data before paying anything.
• Pro — $14.99/mo, or $9.99/mo billed annually. All 50 analysis tools, Ask Your Data auditable AI, Auto Report DOCX/PPTX export, scheduled reports and team roles. This is the plan most teams on this page run.
• Enterprise — custom pricing. Everything in Pro, plus white-label reporting, SSO, unlimited usage, multi-client workspaces and organisation-level audit-log governance.

Every plan runs on UK/EU infrastructure under GDPR, and uploaded data is never used to train AI models — on any tier.

Frequently asked questions