Excel vs EPM: When Your Spreadsheets Stop Serving You

Your Excel model is probably fine. It was built by someone clever, it does what you need, and your team knows how to use it. So why does every consultant who walks through your door act like it’s a ticking time bomb?

The excel vs epm debate gets framed as a binary choice: primitive spreadsheets versus sophisticated platforms. That framing serves vendors and consultants. It doesn’t serve you. The real question isn’t whether EPM is better than Excel. It’s whether the pain you’re experiencing justifies the cost, disruption, and risk of changing.

Let’s talk about when it does. And when it doesn’t.

The Signs That Actually Matter

Most “you’ve outgrown Excel” articles list symptoms like “you have multiple spreadsheets” or “your data is in different places.” These aren’t problems. They’re descriptions of every finance function that’s ever existed.

Here are the signs that actually indicate you’ve hit a wall:

Your month-end takes more than a week, and you can’t figure out why. Not because the work is complex, but because people are waiting on other people. Someone needs numbers from another team before they can run their section. That team needs the sales data, which comes from a system that updates overnight. The cascade of dependencies means your close isn’t limited by processing power or analytical complexity. It’s limited by coordination.

You’ve had a near-miss that kept you up at night. A formula that referenced the wrong row. A copy-paste that overwrote actuals with forecasts. A version control issue that meant the board saw numbers that were two days stale. You caught it. But you know you got lucky.

Your best analyst spends 60% of their time on data handling. Not analysis. Not insight. Just getting numbers from one place to another, checking that they match, and reformatting for different audiences. You hired them for their brain, and you’re using them as a human ETL process.

A single change takes days to propagate. You restructure one cost centre. Now someone has to update the budget model, the forecast model, the management reporting pack, the board deck, and the investor model. They’re all slightly different. They all need manual adjustment.

The COO at a Lloyd’s syndicate we worked with had seen this pattern before. He’d watched previous organisations accumulate what he called “technical debt” in their spreadsheets. Models that worked, sort of, but that nobody fully understood and everyone was afraid to change. He made a deliberate choice to implement a modelling platform from day one rather than wait for the pain to become unbearable. You can read more about that implementation in our Lime SMA case study.

That’s unusual. Most companies wait until the pain is acute.

What Excel Does Better Than Any Platform

This is the part most consultants skip. Excel has genuine advantages that EPM platforms haven’t replicated.

Speed of prototyping. You can build a quick model in Excel in an hour. The same model in Anaplan or Pigment takes days, minimum. When you’re exploring a new idea, testing a hypothesis, or responding to an urgent board question, Excel wins.

Transparency of logic. Click on a cell, see the formula. Trace precedents, trace dependents. The logic is visible in a way that platform calculations often aren’t. When something looks wrong, you can figure out why.

Universal literacy. Everyone in finance can use Excel. Not everyone can use Anaplan. This matters more than vendors admit. The analyst who builds your model might leave. The person who replaces them needs to understand what they inherited.

Low switching cost for small changes. Need to add a new line item? Add a row. Need a new calculation? Write a formula. In platforms, even small changes often require someone with builder permissions, and sometimes a change request process.

“Your Excel model works. Your team is talented. That’s not the problem. The problem is that the model doesn’t scale the way your business does.”

The honest answer to excel vs epm isn’t that one is better. It’s that they’re better at different things. The question is which set of trade-offs matches your situation.

The Real Cost of Switching (That Nobody Talks About)

Let’s say you’ve decided Excel isn’t working anymore. You’ve seen the demos, you’ve talked to the vendors, you’ve got budget approval. Here’s what the next 18 months actually looks like.

Month 1-3: Discovery and design. Someone needs to document how your current models work. This is harder than it sounds. The person who built the original model left two years ago. The person who maintains it has made undocumented changes. There are formulas that reference cells that no longer exist, kept alive by legacy data that nobody remembers creating.

Month 4-8: Build and test. The implementation partner builds your new model. You test it. The numbers don’t match your Excel model. Sometimes that’s because the platform is doing something wrong. Sometimes it’s because your Excel model was doing something wrong and you never noticed. Figuring out which is which takes longer than the build itself.

Month 9-12: Parallel running. You run both systems simultaneously. Your team’s workload roughly doubles. They’re maintaining the old process while learning the new one. Morale dips. The people who were sceptical from the start feel vindicated.

Month 13-18: Stabilisation. You’ve switched over, but you’re still finding edge cases. The model handles 95% of scenarios correctly. The other 5% require workarounds, escalations, or manual adjustments. Slowly, these get fixed. Slowly, the new system becomes the system.

This timeline assumes things go well. We’ve seen implementations where the 12-week project took 18 months. We’ve seen companies abandon implementations entirely, writing off six-figure investments because the platform never delivered what was promised.

The vendors won’t tell you this. The implementation partners might hint at it, but they’re incentivised to be optimistic. You need to go in with realistic expectations.

When EPM Actually Delivers Value

Despite everything I’ve just said, there are situations where EPM platforms genuinely transform how finance operates. Here’s what those situations have in common.

Multiple stakeholders need to contribute to the same plan. Not just view it. Contribute. If your budget process involves 15 cost centre managers submitting their numbers, then someone consolidating in a master spreadsheet, then sending back for revisions, then reconsolidating, you’re doing manually what platforms do automatically. The time savings are real.

You need scenario analysis that goes beyond “base, upside, downside.” What happens if we acquire that company AND lose that customer AND interest rates rise 50 basis points? In Excel, each scenario is a separate model or a separate tab. In platforms like Pigment, scenarios are dimensions. You can create and compare them without duplicating your entire model.

Your reporting requirements are multiplying. Board pack. Investor update. Regulatory submission. Management accounts. Departmental dashboards. If these all need slightly different cuts of the same underlying data, you’re either maintaining multiple outputs manually or you’re compromising on what each audience receives. Platforms let you build once and report many ways.

Your business structure changes frequently. Acquisitions, disposals, reorganisations, new product lines. Each change ripples through your models. In Excel, that’s manual work across multiple files. In platforms, a single change to the hierarchy adjusts everything downstream.

The systems like Anaplan or Pigment have genuine ability to automate regular tasks: data flows, data cleansing, calculations, updating of reporting suites. With built-in integrations that run on schedule, manual processes become a thing of the past. A single change to the hierarchy can adjust the entire model and reporting in an instant.

But here’s the thing: these benefits only materialise if you implement correctly. And correct implementation requires clarity about what you’re trying to achieve, realistic timelines, and genuine executive sponsorship. Without those, you’re just trading one set of problems for another.

The Middle Path Nobody Mentions

The excel vs epm framing suggests you have to choose. All in on platforms, or stuck in spreadsheet purgatory.

There’s a middle path.

Keep Excel for what it does well: ad-hoc analysis, quick prototyping, one-off models that don’t need to be maintained. Use platforms for what they do well: recurring processes, multi-user collaboration, integrated reporting.

Some of the most effective finance functions we’ve seen use both. The platform handles the core planning cycle: budgets, forecasts, monthly reporting. Excel handles everything else. The analyst who wants to test a new pricing model doesn’t need to wait for a platform build. They spin up a spreadsheet, do their analysis, and if it proves valuable, then it gets productionised in the platform.

This hybrid approach requires discipline. You need clear boundaries about what lives where. You need governance to prevent spreadsheet sprawl from recreating the problems you were trying to solve. But it’s more realistic than pretending you’ll never need Excel again.

Making the Decision

If you’re genuinely wrestling with this choice, here’s how to think about it.

Calculate your actual cost of current state. Not the theoretical cost. The actual cost. How many hours per month do your team spend on data handling versus analysis? What’s the fully-loaded cost of those hours? What decisions have you delayed or avoided because you couldn’t get the analysis done in time?

Be honest about your implementation capacity. Do you have someone who can own this project for 12-18 months? Not just sponsor it. Own it. Show up to weekly meetings, make decisions, resolve conflicts, push back on scope creep. If that person doesn’t exist, your implementation will struggle regardless of which platform you choose.

Talk to companies who’ve done it, not just vendors. Vendors will give you references. Those references will be their happiest customers. Ask to speak to customers who had difficult implementations. Ask what they’d do differently. Ask what they wish they’d known.

Consider the cost of waiting. This cuts both ways. If you implement too early, you’ll spend money and political capital on a problem that wasn’t urgent. If you wait too long, you’ll implement under pressure, which almost guarantees a worse outcome.

The right answer isn’t always “implement now.” Sometimes it’s “implement in 18 months, after the acquisition closes.” Sometimes it’s “never, because our Excel models are genuinely fit for purpose.” Sometimes it’s “yesterday, because we should have done this three years ago.”

What matters is making the decision deliberately, with clear eyes about the trade-offs, rather than being pushed into it by a compelling demo or a vendor’s end-of-quarter discount.

Your spreadsheets got you here. They might get you further than you think. But if they can’t, you should know before you’re in crisis mode.

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