Sales orders
Sales orders, expected fulfilment dates and invoice schedules.
Oracle NetSuite Partner · Cash Flow Forecasting · UK-wide
Cash flow forecasting software built on your NetSuite data
Cash flow forecasting software estimates the cash a business may hold over the weeks and months ahead. NetSuite already contains sales, purchases, invoices and payment dates. A forecast built from that source can be refreshed more often than a spreadsheet that depends on manual exports. The result still relies on accurate data and sensible assumptions.
- Since 2003 working with NetSuite
- Accountancy-led CA & CGMA directors
- Built on live data not manual exports
Who builds the forecast?
Cofficient is an Oracle-authorised NetSuite partner. Our directors include qualified accountants, so the forecast is designed around the decisions a finance team needs to make.
Why manual forecasts drift
A spreadsheet forecast often starts with an export from several systems. The finance team updates formulas, adds assumptions and circulates a copy. Transactions continue after the file is produced, so the forecast begins to age immediately.
Common problems include:
- Updates depend on one person and a set of formulas that other users may not understand.
- Late payments and changed order dates are not reflected until someone edits the file.
- Different versions circulate, which makes review and approval harder.
- Scenario work takes time because each change must be modelled by hand.
The issue is the gap between the operational data and the forecast. Bringing the forecast closer to the source reduces that gap.
The data NetSuite already holds
A cash forecast can draw on information already recorded in NetSuite, including:
Customer invoices
Customer invoices, due dates and recorded payment history.
Supplier bills
Supplier bills, payment terms and planned payment runs.
Recurring costs
Recurring costs and other commitments held in the system.
The relevant records and fields vary by account. Discovery work should confirm which data is complete enough to use and where additional inputs are needed.
How AI can support a forecast
AI may help with pattern review and scenario analysis. For example, a model can compare due dates with recorded payment behaviour or show how a delayed order changes the expected cash position. The selected tool must be tested against known outcomes before the finance team relies on it.
Useful applications may include:
- Adjusting expected receipt dates where a clear payment pattern exists.
- Refreshing the forecast after transactions or order dates change.
- Running defined scenarios without rebuilding a spreadsheet model.
- Flagging data gaps or unusual movements for a person to review.
The finance team remains responsible for assumptions, review and approval. The model supports the process; it does not remove uncertainty.
What the forecast can tell you
What it can do
A well-designed forecast can show the expected cash position by week, identify a potential shortfall and compare the effect of agreed scenarios. It can also make the assumptions more visible, which helps the finance team explain the result to other decision-makers.
What it cannot do
It cannot predict an event that is missing from the data. It also cannot correct poor coding, incomplete orders or unrealistic assumptions. These issues need to be addressed in the source process.
How Cofficient builds the forecast
The work begins with the current forecast and the decisions it supports. Cofficient then reviews the NetSuite records, the update process and the controls used by the finance team.
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1
Agree the forecast horizon, reporting frequency and owners.
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2
Map the NetSuite data used in each part of the forecast.
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3
Record the assumptions and identify missing or unreliable fields.
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4
Build and test the forecast against previous periods and known scenarios.
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5
Train users, document the review process and monitor the result after launch.
A rolling thirteen-week cash view is common, but the final horizon should match the business cycle and the decisions being made.
Who you are working with
Cofficient is employee-owned. The team includes NetSuite specialists and directors with CA and CGMA qualifications.
Oracle NetSuite Partner
Authorised UK NetSuite partner
Since 2003
20+ years of NetSuite delivery
Employee-owned
Led by chartered, CA & CGMA-qualified directors
UK-wide
Glasgow HQ, clients across the UK & internationally
Our Google reviews
Questions about cash flow forecasting in NetSuite
Can NetSuite produce a cash flow forecast?
NetSuite contains reporting and planning capabilities, and it holds much of the transaction data used in a forecast. The final setup depends on the modules, records and reporting tools in the account. Cofficient can assess the current setup and identify any gaps.
Do we need separate cash flow forecasting software?
Not in every case. If the required data already sits in NetSuite, it may be possible to build the forecast around that source. A connected product should only be introduced where it adds a clear function that the current setup cannot provide.
How far ahead should we forecast?
The horizon should match the decisions being made. Many finance teams use a detailed thirteen-week cash forecast and a longer planning view. The level of confidence usually falls as the horizon extends.
How is financial data handled?
The data flow, permissions, hosting and retention rules depend on the tools used. These requirements should be documented before any forecast is built. Access should follow the organisation's existing finance and security policies.
Will an AI forecast be more accurate?
It may update more often and use recent transaction data, which can reduce the delay found in a manual process. Accuracy depends on the source data, assumptions and model design. Performance should be measured against previous forecasts before wider use.
Review your cash flow forecasting setup
Cofficient will review how the forecast is produced, which NetSuite data is used and where the process loses time or accuracy. You will receive a clear view of what can be improved within the current system and whether an additional tool is justified.