Picture a typical morning in treasury.
You open your laptop with a simple goal: answer one question confidently. But before you can, you’re already juggling multiple banks, multiple accounts, multiple entities — and a few versions of “the same” forecast. Someone has updated a spreadsheet. Someone else has not. A number looks familiar, but you can’t tell if it’s up to date. And then the CFO asks the question you expected: “Where will we be on cash in four weeks — and what could break the plan?” You know the business. You know the drivers. The frustrating part is that your best insights are often spent explaining why the process is messy rather than what the numbers actually mean.
That’s the tension at the heart of forecasting in 2026: forecasting remains one of the most critical processes in finance, and still one of the most painful. Forecasts don’t fail because teams don’t understand the business. They struggle because the process is still built on foundations that weren’t designed for today’s complexity.
Why your forecast is always wrong - and why that’s okay
Every forecast is wrong by definition. That’s simply what forecasting is: you’re describing a future shaped by events no spreadsheet can predict — market shifts, customer behaviour, supplier disruptions, policy changes.
So the goal was never perfect accuracy. The real purpose is to be:
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Directionally reliable enough to make decisions
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Early enough to avoid liquidity surprises
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Clear enough that leaders can act without hesitation
Many teams still approach forecasting like a precision exercise. Then reality changes, and the forecast gets treated like a failure instead of what it is: a decision tool.
What actually breaks forecasting in most organisations
Back to that morning in our story. The reason it feels harder than it should isn’t a lack of skill. It’s the environment the forecast is forced to live in.
- Fragmented system landscapes
Multiple ERPs (often after acquisitions). Multiple banks. Local tools that each hold a piece of the truth. When cash, payments, and drivers don’t come together in one place, Excel becomes the default integration layer. It’s the quickest way to connect what was never properly connected in the first place. - Cross-border and organisational complexity
Global operations add friction that compounds fast: different currencies, reporting standards, timelines, and assumptions. Local teams are closest to the business, but they often work with different inputs and rhythms. Central treasury depends on submissions it can’t fully validate. - Culture, communication, and ownership gaps
Forecasting is human work wrapped around financial data. And the human parts fail in predictable ways: late inputs, incomplete submissions, unclear accountability, and “someone else owns that number”. Finance ends up policing data instead of operating as the strategic partner it’s meant to be.
The hidden cost: Maintenance crowds out analysis
If you’ve ever felt like you spend most of your time preparing data rather thanusing it, you’re not imagining things.
In many organisations, forecast effort is swallowed by:
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Data collection
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Reconciliation
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Version control
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Spreadsheet upkeep
That leaves only a small fraction of time for the work that actually moves the business: understanding risk, testing scenarios, and advising leadership with confidence.
And that’s where the story gets painful. The CFO’s questions are usually simple. The answers become slow, qualified, and cautious because the data doesn’t feel trustworthy.
What changes when forecasting becomes automated
Now imagine the same morning, but different.
You open the forecast and it’s already updated from banking and ERP data. Baseline, best-case, worst-case scenarios are there. The mechanics are handled in the background: ingestion, reconciliation, pattern detection. Your job shifts fromproducing the forecast to interpreting it:
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What assumptions matter most
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Where the liquidity buffer should be
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What financing options need to be prepared
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Which decisions should be accelerated or delayed
Automation is not designed to remove people. It clarifies roles. Sales owns revenue assumptions, procurement owns payment timing, HR owns payroll, and finance orchestrates the narrative and the governance. Humans focus on judgement, not copying numbers between files.
The“real-time” promise - and what most teams actually need
“Real time” is oftentreated like the finish line. But what drives stress day to day is rarely the speed of loading times alone.
It’s uncertainty:
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Which number is current
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What changed
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Whether a decision is safe
For many organisations, near-time updates and strong data foundations will beat “real-time” dashboards every day. Real-time signals become truly valuable when external shocks hit — but only when systems are connected, and the organisation is ready to interpret impact and act.
Without Excel from day one: What that really means
Forecasting works best when the process runs in a dedicated system and your team uses spreadsheets foranalysis and decision-making.
If you startforecasting in Excel, you often build habits that become hard to unwind:
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Fragmented inputs
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Manual consolidation
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Uncontrolled versions
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“Shadow processes” that are hard to audit or scale
Modern forecasting needs structure. Defined ownership, consistent logic, clean integrations, and a workflow that scales as the business grows. That’s difficult to establish when the forecast is built on a file that can be copied, changed, and re-shared endlessly.
In practice, “no Excel from day one” means starting with a workflow that treats forecasting as an operating model -not as a spreadsheet exercise. And when technology is part of the solution, it should support that operating model by connecting source data, standardising inputs, and reducing manual handling, so finance can spend time on decisions rather than gathering information.
Forecasting excellence is clarity, not perfection
A good forecast doesn’t predict the future. It makes the future less risky to navigate. When the mechanics of data gathering and consolidation are handled reliably, finance gets its actual job back: helping leaders make better decisions with fewer surprises — even in uncertain conditions.
And the next time the CFO asks the question, your first answer doesn’t have to be an explanation of why the process is broken. It can be what it should have been all along: a confident view of what’s coming, what could change, and what to do next.
