From Treasury Masterminds
Treasury Masterminds has hosted plenty of webinars over the years. Usually educational, sometimes technical, occasionally even entertaining. But now and then, it is healthy to take a sacred topic in treasury and simply put it on trial.
That was exactly the idea behind the webinar “Cash Flow Forecasting on Trial.” Instead of another session explaining why forecasting is important, we decided to question it. Does it really deliver value? Is the effort justified? Or is it one of those treasury processes everyone maintains because… well, treasury has always done it.
To explore this properly, we invited three different perspectives:
- The Skeptic: Maggie Wong, Group Treasurer at Alberts
- The Optimist: Alexander (Clearbox Consulting, and a Treasury Masterminds board member)
- The Technologist: Joergen from Nomentia
And the audience? They played the jury.
What followed was a refreshingly honest debate about a topic every treasurer claims to master and quietly struggles with at the same time.
The Opening Question: Is Cash Flow Forecasting Actually Useful?
Before the debate started, the audience was asked a simple question:
How useful is your current cash flow forecast?
The answers were telling. Most participants landed in the “very useful” or “somewhat useful” categories. No one rushed to publicly declare their forecast useless. Treasurers tend to have a reputation to maintain.
Still, the conversation quickly revealed a familiar tension. Everyone agrees that forecasting is important. But many treasurers secretly wonder whether the effort required to produce a “perfect” forecast actually delivers the value promised.
The Sceptic’s Case: The Effort vs. Value Problem
Maggie Wong opened the trial from the sceptical side. Not anti-forecasting, but definitely realistic about its limitations.
Her main argument was simple and painfully familiar to most treasury teams:
A good cash flow forecast requires a huge amount of effort.
- Collecting data from multiple departments.
- Chasing business units.
- Reconciling assumptions.
- Updating models constantly.
And even after all that work, the forecast can still be wrong.
In her early treasury career, she spent significant time producing very short-term forecasts. The experience led to an uncomfortable realisation: the amount of work required sometimes outweighed the practical value of the output.
For some companies, especially those with stable liquidity positions, obsessing over extremely detailed short-term forecasts may simply not be the best use of treasury resources.
Uncomfortable truth number one.
The Optimist’s Argument: Companies Don’t Go Bankrupt Because of Bad Excel
Alexander took the opposite stance. His argument was blunt and hard to disagree with:
Companies go bankrupt because they run out of cash.
Not forecasting liquidity is basically flying blind.
Even if the process isn’t perfect, treasurers still need a forward view of cash inflows and outflows to answer fundamental questions:
- Can we meet payroll?
- Can we pay suppliers?
- Are we approaching a liquidity gap?
- Do we need funding?
Forecasting doesn’t have to be perfect to be useful. It just needs to be good enough to support decision making.
This is where many treasury teams get stuck. They aim for unrealistic precision instead of focusing on directional insight.
The Technology Angle: Automation Is Changing the Game
Joergen brought the technology perspective. And thankfully not in the usual “AI will solve everything” tone.
His point was more practical.
Many forecasting challenges come from data collection and manual processes, not from the forecasting concept itself.
Technology can help by:
- Automating data collection from ERP systems and banks
- Standardising forecasting templates across business units
- Improving data quality and consistency
- Reducing manual effort
The goal is simple: spend less time building the forecast and more time interpreting it.
Because a forecast nobody trusts or understands is just another spreadsheet quietly aging in a shared drive.
The Real Problem: Forecasting Isn’t the Issue
One theme kept resurfacing during the discussion.
The real issue often isn’t forecasting itself. It is a process discipline and organisational behaviour.
Forecasts break down when:
- Business units do not provide reliable inputs
- Data sources are fragmented
- Treasury lacks visibility into operational cash drivers
- Processes rely heavily on manual updates
Technology can help, but governance and collaboration matter just as much.
Treasury forecasting is not just a model. It is an organisational process.
What the Jury Learned
By the end of the session, the question was not whether cash flow forecasting should exist. That debate is already settled. Instead, the real question became:
Are we doing it in a way that actually delivers value?
Some key takeaways from the discussion:
- Perfection is unrealistic. Forecasts should support decisions, not predict the future with mathematical certainty.
- Effort must match purpose. A short term liquidity forecast for operational cash management is different from a strategic long term forecast.
- Technology can reduce friction. Automation helps eliminate manual work and improve data reliability.
- Treasury cannot do it alone. Forecast accuracy depends heavily on cross department cooperation.
- Focus on insights, not spreadsheets. The value of forecasting lies in interpretation and action.
Final Verdict
Cash flow forecasting survived the trial. Barely.
Not because it is perfect, but because treasury simply cannot operate without some forward view of liquidity.
The real takeaway is this: the traditional approach to forecasting is evolving. AI might be there to solve it. But that might just be the next one on Trial.
- Less manual effort.
- Better data integration.
- More realistic expectations.
And maybe, just maybe, fewer spreadsheets that nobody fully trusts. Treasurers everywhere would appreciate that outcome. Even if they will not admit it publicly.
Listen or watch the recording on Spotify HERE and on YouTube HERE
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