Most Australian finance teams build in one spreadsheet platform or the other, and the Excel versus Google Sheets debate usually starts with a feature list and ends in stalemate. The more useful question is narrower: what kind of modelling work are you doing, who else needs to work in the file, and how much scrutiny will the finished model face?

This guide compares the two platforms across the things that actually matter for financial modelling: real-time collaboration, formula depth, auditability, version control, integration, data capacity, and cost. It is written for SME finance teams, accountants in practice, and advisors who need a defensible reason to standardise on one platform, not a tribal allegiance to either.

The Core Question: Same Tool, Different Workflows

Excel and Google Sheets are both spreadsheet engines. Both calculate, both chart, both pivot, and both can produce a perfectly serviceable three-way forecast. The choice between them is not about whether spreadsheets work, but about how models get built, audited, and shared in your specific workflow.

The differences show up in the details. Excel is a desktop application with a cloud layer bolted on; Sheets is a cloud application with offline support bolted on. That sounds trivial, but it shapes everything downstream: where files live, how versions are controlled, how review comments travel, and what happens when a lender or auditor asks for the working file.

A financial model is rarely a solo artefact: built by one person, reviewed by another, challenged by a lender or board, and updated monthly for years. The platform that supports that lifecycle is the one to use, and the two platforms support it differently.

Real-Time Collaboration: Where Sheets Leads

If five people need to work in the same file at once, Google Sheets is the better tool, and there is no serious argument against it. Simultaneous editing is the default: no save button, no checkout, no risk of two people editing different copies. Comments thread with @mentions, cell-level edit history shows who changed what, and a contributor with a free Google account can work without any licence.

Excel has closed most of the gap. Microsoft 365 supports real-time co-authoring in both the desktop app and Excel for the web, provided the file lives in OneDrive or SharePoint and AutoSave is on. For teams that host their workbooks in the cloud, the collaborative experience is genuinely good.

The problem is that file-based sharing still dominates in Australian advisory and SME practice. Emailing "the latest version" around, with filenames like forecast_final_v3_FINAL.xlsx, disables co-authoring entirely and creates exactly the version chaos collaboration tools are supposed to prevent. If your team or your client still works that way, Excel's collaboration features never switch on.

The practical read: if the file is a shared working document that several people update, Sheets wins on friction alone. If the file is a model one person owns and others review, Excel's workflow is perfectly adequate; the bottleneck is review discipline, not the tool.

Formula and Function Depth: Excel's Long Tail

This is where Excel pulls ahead, and the gap is wider than most people realise. Modern Excel has a genuinely deep function stack:

• Dynamic arrays (FILTER, SORT, UNIQUE, SEQUENCE, VSTACK, HSTACK, DROP, TAKE, CHOOSECOLS) that spill results across cells without array-entry gymnastics
• LET for readable intermediate calculations, and LAMBDA for defining reusable custom functions inside the workbook
• XLOOKUP, mature enough that nobody should be writing new VLOOKUPs
• Power Query for repeatable data transformation
• Power Pivot with DAX for in-memory data models, plus cube functions (CUBEVALUE, CUBEMEMBER) that report against those models
• The long legacy tail: database functions (DSUM, DGET), engineering functions, and the full financial function family (XIRR, MIRR, CUMPRINC, IPMT, PPMT)

A LET pattern for readable, auditable multi-step calculations:

=LET(rate, $C$5,
     months, SEQUENCE(12,,0,1),
     base, $C$4,
     base * (1 + rate) ^ months)

Sheets has real equivalents, but fewer. ARRAYFORMULA and QUERY cover a lot of ground, and QUERY is excellent for lightweight SQL-style reporting. FILTER, SORT, and UNIQUE exist, and LAMBDA, named functions, and XLOOKUP arrived in 2022, so the modern formula set is closer than it used to be. A typical Sheets aggregation:

=QUERY(Transactions!A:G,
       "select A, sum(G) where B = 'July' group by A
        order by sum(G) desc label sum(G) 'Total'", 1)

What Sheets lacks is the machinery layer. There is no Power Query, no DAX, no cube functions, and no equivalent to the data model. Apps Script can automate, but it is JavaScript programming, not a transformation engine. For a monthly consolidation model, that missing machinery layer is the difference between a refresh and a rebuild.

Modelling Best Practice: Audit Trails and Precedent Tracing

Professional modelling is as much about review as calculation. A model that cannot be checked is a liability, no matter how clever the formulas are. Here the platforms diverge clearly.

Excel's formula auditing toolbar is the standard for audit-grade work: trace precedents and dependents, evaluate formula step by step, and the watch window for monitoring key cells. Combined with named ranges, defined names with scoped visibility, sheet protection, and conditional-formatting error checks, Excel gives a reviewer the tools to interrogate a model properly. The workbook is also self-contained: it travels as a single xlsx file, which matters when a lender, auditor, or board member wants the working file, not a summary.

Sheets offers the basics: trace precedents and dependents, named ranges, protected ranges, and data validation. For a lighter internal model, that is genuinely enough. But there is no evaluate-formula tool, the auditing features are thinner, and a cloud model is only as accessible to an external reviewer as the sharing settings allow.

The honest summary: Excel is the stronger platform for audit-grade models that will withstand external scrutiny, and Sheets is acceptable for lighter models where the audience is the team itself. Build the model a bank or board will challenge in Excel; build the planning sheet an operations manager updates weekly in Sheets.

Version History and Recovery

Both platforms keep history, but they do it differently, and the difference matters more than most teams realise.

Google Sheets automatically records a version at every edit, lets you name versions (for example, "FY27 board pack v2"), and restores any point in time. Cell-level edit history shows who changed what, and you can revert individual edits without losing the rest of the sheet. It is granular, discoverable, and needs no discipline to maintain.

Excel's version history works through AutoSave versions in OneDrive or SharePoint: you can open the version list and restore earlier saves, including the classic "I saved over the wrong file" recovery. None of this helps if the file never makes it to the cloud. For locally saved files, version control is whatever your backup software provides, and the email-attachment workflow has none at all.

That last point is a process problem rather than a software problem, but it is the one that bites. Teams that host Excel files in SharePoint get solid versioning; teams that email files around get none. Sheets removes the decision by making history automatic and unavoidable.

Integration and Ecosystem

Platform choice is often settled by the ecosystem around it, not the spreadsheet itself.

Google Sheets connects natively to Google Workspace: Drive, Gmail, Calendar, and Google Forms feed straight in. IMPORTRANGE pulls data between sheets, IMPORTHTML and IMPORTXML pull from the web, and Apps Script automates with JavaScript. For teams already living in Workspace, and for small businesses on Google Forms, the integration is frictionless. Looker Studio (formerly Data Studio) gives free dashboarding against Sheets data.

Excel connects to the Power Platform: Power Automate for workflow, Power Apps for lightweight applications, and Power BI for serious reporting. It talks to SQL Server and ODBC data sources natively, runs Python in Excel, and carries VBA for desktop automation. Crucially, xlsx remains the interchange format that banks, lenders, auditors, and government template providers expect, making Excel the safer default when a file must leave your organisation.

For Australian SME finance teams the practical question is often what the rest of the ecosystem runs on: a practice on Xero and Microsoft 365 will find Excel fits naturally, and a team standardised on Google Workspace will find Sheets fits naturally. The spreadsheet is rarely the reason to switch ecosystems, but it is the reason to stop juggling both.

Data Handling and Dataset Size

Excel handles larger datasets and more sophisticated data transformation, full stop.

The Excel grid holds 1,048,576 rows by 16,384 columns, and Power Pivot extends the practical ceiling far beyond that, compressing millions of rows of transactional data into an in-memory model. Power Query turns multi-file consolidations into repeatable, refreshable queries, which is the standard answer for monthly reporting on top of system exports.

Google Sheets is capped at 10 million cells per spreadsheet, and in practice it becomes sluggish well before that when formulas are heavy. QUERY is fine on a few hundred thousand rows, but it is not a substitute for Power Query, and there is no in-memory model. For monthly consolidations of transactional data across multiple systems, Excel plus Power Query and Power Pivot is the right answer.

Cost and Accessibility for Small Business

For a small business, cost is a real consideration, and Sheets is meaningfully cheaper.

Google Workspace Business Starter is roughly AUD $9 per user per month at typical Australian pricing, and a free Google account gives you Sheets with most core features for small-team use. Collaboration costs nothing extra, and there is no licence decision when a contractor or advisor needs access.

Microsoft 365 Business Standard is roughly AUD $20 per user per month, with cheaper Basic plans and a one-time Office Home and Business licence around $250 if you prefer no subscription. The free Excel web app covers basic use, but the desktop app is where the real modelling power lives, and that is what the licence buys.

For a two-person team with modest modelling needs, paying for Excel is hard to justify. For a finance function where the model is a core asset, the per-user cost is trivial next to the value of Power Query, Power Pivot, and audit tooling. Cost should be a tiebreaker, not the deciding factor.

Excel vs Google Sheets: The Comparison Table

Decision Framework: Which Platform for Which Job

The decision framework below is the practical version of everything above. Match the scenario to the platform; when unsure, the default is Excel.

The realistic answer for most teams is not "one platform, everywhere". It is a deliberate split: Excel for models that are reviewed, audited, or handed to external parties, and Sheets for shared working files where collaboration is the point. The risk is not choosing the wrong tool; it is not choosing at all.

Conclusion

The Excel versus Google Sheets question is really a question about model lifecycle. Sheets is the better collaboration surface: cheaper, easier, and purpose-built for several people working in one file at once. Excel is the better modelling engine: deeper formulas, real data transformation, bigger data capacity, and review tooling that holds up when a lender or a board asks hard questions. The two strengths barely overlap, which is why the debate never resolves.

A finance function that matches platform to job, keeps version control explicit, and documents assumptions will out-build one that picks sides. Excel remains the default for audit-grade work and data-heavy consolidation, and Sheets earns its place for anything where the team is the audience. Choose deliberately, and the tool stops being the argument.

Related reading

• Excel VBA vs Custom SaaS: Choosing the Right Tool
• Comparing AI Tools for Excel Work: ChatGPT vs Copilot vs Gemini
• Excel Automation with Power Query