Project Management Dashboard — Milestones, Budgets and Utilisation From the Trackers You Already Keep
Project managers lose Friday afternoons to status decks. DataHub Pro turns project tracker exports into a live dashboard — milestone health, budget vs actual, resource utilisation — and generates the weekly status report as an editable Word or PowerPoint document, automatically, on schedule.
Updated 10 June 2026
What is a project management dashboard?
A project management dashboard is a single view of the three things every sponsor asks about: are we on schedule (milestones), are we on budget (planned versus actual cost), and are the right people on the right work (resource utilisation)? A good one shows status across the whole portfolio at a glance, lets you drill into any project that has gone amber, and produces the steering-committee pack without a copy-paste marathon.
The frustrating part is that the data almost always exists. It sits in a project tracker spreadsheet — like the one in our project tracker in Excel guide — or in exports from Jira, Asana, Monday or Microsoft Project, plus a finance extract for the cost side. What is missing is the layer that joins these exports together, computes the health metrics consistently, and presents them in a format a steering committee will actually read.
Most PMs solve this manually: every Friday, export the data, update the RAG statuses, rebuild the burn-down chart, paste it into PowerPoint, and write the commentary. It works, but it costs half a day a week, the methodology drifts from one report to the next, and by Monday morning the numbers are already stale. BI tools could automate it, but the BI team has a backlog of its own — and a six-week wait for a dashboard defeats the point.
DataHub Pro takes the middle path. Upload the tracker export (or connect the SharePoint library where project files live), and the platform builds the dashboard, runs variance analysis on budgets, flags slipping milestones with anomaly detection, and writes the status narrative with auditable AI. The output is an editable document, not a locked dashboard — because every status report still needs a PM's judgement before it goes to the sponsor.
The reporting problems PMs and PMOs know too well
If any of these sound like your week, you are the audience for this page:
- The Friday status-deck ritual. Exporting, reformatting, rebuilding the same charts and rewriting near-identical commentary every week. Multiply by the number of active projects and reporting becomes a part-time job in itself.
- Budget burn is invisible until it is an overrun. Cost actuals live in a finance system; the plan lives in your tracker. By the time someone joins the two, the project is 20% over and the conversation has become an escalation.
- Overallocation is discovered through burnout. Without a utilisation view across projects, the same two specialists end up at 115% allocation — and you find out when delivery slips or someone resigns.
- Five tools, no portfolio view. One team is in Jira, another in spreadsheets, a third in Monday. Each tool reports on itself; nobody can see the whole portfolio without manual assembly.
- Steering packs take a day to build. Milestone tables, RAG summaries, finance slides, risk registers — assembled by hand, every cycle, in PowerPoint.
- Every PM calculates status differently. One PM's amber is another's green. Without consistent, data-derived health metrics, portfolio reporting is opinion with formatting.
DataHub Pro features mapped to project work
From the platform's 50 analysis tools, these are the ones project managers lean on:
Budget vs actual variance
Upload planned and actual cost per project or workstream and get instant variance analysis — the automated version of our budget vs actual in Excel guide. Drifting cost lines are flagged before they become overruns.
Anomaly detection on slippage
Statistical anomaly detection flags milestones and tasks whose dates or durations are drifting abnormally versus baseline — so the slipping workstream surfaces itself instead of hiding in row 214 of the tracker.
What-if resource scenarios
Model the effect of moving people between projects or delaying a phase. The what-if tool recalculates utilisation and cost impact instantly, before you commit to the change.
Ask Your Data — auditable AI
"Which projects are over 80% budget but under 60% complete?" Plain-English questions, answers with a visible audit trail of the operations performed — defensible in a steering committee.
Auto Report steering packs
Generate the steering-committee pack as an editable PowerPoint or Word document: milestone status, budget variance, utilisation and AI-written commentary, ready for your judgement and edits.
Scheduled reports + SharePoint connector
Connect the SharePoint library where project files live. DataHub Pro re-reads on schedule and delivers the weekly status report automatically — Friday afternoons return to delivery work.
Worked example: from portfolio.csv to three findings
Suppose you upload portfolio.csv — one row per workstream across 14 active projects, with milestone dates (planned and actual), budget, cost to date, percent complete and allocated hours per person. Three findings come back within minutes:
Three projects in the danger zone
Variance analysis flags three projects that have consumed more than 80% of budget at less than 60% completion. Projected at current burn, the worst lands 31% over — a number you now know in week 7, not week 12.
Two engineers at 115% allocation
The utilisation view shows two named engineers allocated across four projects simultaneously, at 110–115% of capacity, while overall portfolio utilisation sits at 78%. The rebalancing conversation now has data.
One workstream causes 64% of slippage
A Pareto analysis of milestone delays shows a single integration workstream accounts for 64% of total slip days across the portfolio — turning fourteen separate status conversations into one focused intervention.
Auto Report turns the same analysis into the steering pack, with each figure auditable back to the tracker export. If you are still building your tracker, start with our project tracker template and Gantt chart in Excel guide — DataHub Pro reads those files as-is.
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.
What DataHub Pro is not
It is not a task manager and does not replace Jira, Asana, Monday or Microsoft Project — your team keeps working where they work. It also does not draw interactive Gantt charts; for plan visualisation, see our Gantt chart in Excel guide. DataHub Pro is the reporting and analysis layer that sits on top of the exports those tools already produce.
Frequently asked questions
Does DataHub Pro replace Jira, Asana or Microsoft Project?
No — and it is not meant to. Your team keeps managing tasks wherever they already work. DataHub Pro is the reporting layer: export the data (CSV/Excel from any of these tools), upload or sync it, and get portfolio dashboards, variance analysis and automated status reports.
Can it produce a Gantt chart?
DataHub Pro focuses on analytical reporting — milestone health, budget variance, utilisation — rather than interactive plan visualisation. For building a Gantt view of your plan, see our free guide to Gantt charts in Excel; DataHub Pro then analyses that same file.
How does budget vs actual tracking work?
Upload a file with planned and actual cost per project, workstream or period. The variance tool computes absolute and percentage variance per line, flags items beyond your threshold, and the AI writes commentary on what is driving the gap. Most PMs run it weekly from the same export.
Can it read project files stored in SharePoint?
Yes. SharePoint is a live connector — point DataHub Pro at the document library where tracker exports are saved and it re-reads them on schedule. Excel/CSV upload and Google Sheets are also supported.
Can the weekly status report be automated?
Yes. Scheduled reports re-run your analysis at the cadence you set and generate an editable Word or PowerPoint via Auto Report, with AI-written commentary. You review, adjust the narrative, and send — typically minutes instead of a half-day.
Does it handle a portfolio of many projects?
Yes. Upload one consolidated file or several per-project files; the dashboard aggregates to portfolio level with drill-down per project. Pareto analysis identifies which projects drive most of the delay or overspend.
Can it analyse RAID logs and risk registers?
If the data is in a spreadsheet, yes — risk counts by severity, ageing of open items, anomaly flags on items whose status has not moved. It will not invent risk judgements; it makes the register you already keep measurable.
What does it cost for a PMO team?
Free tier: 1 user, 3 uploads/month, 8 core tools — enough to pilot on one project. Pro is $14.99/mo per user ($9.99/mo annual) for all 50 tools, AI and scheduled reports. Enterprise adds SSO, team roles at scale and audit-log governance for larger PMOs.
Is project data secure?
Data is hosted in UK/EU regions under GDPR and never used to train AI models. Team roles restrict who sees which workspaces, and the audit log records every access and analysis — useful when project data includes commercially sensitive budgets.
Get Friday afternoons back.
Upload a tracker export. Get milestone health, budget variance and utilisation in minutes — and a status report that drafts itself every week.
See also: Project tracker in Excel · Gantt chart in Excel · Budget vs actual in Excel · For finance teams · Pivot tables in Excel · Home