How to Improve Sales Forecast Accuracy
One of the hardest questions any Sales Director or Managing Director gets asked is:
“What are we going to sell next month?”
Unfortunately, the answer is often little more than an educated guess.
Sales forecasts are built from spreadsheets.
Managers make adjustments.
Someone changes a few numbers before the board meeting.
Then everyone hopes they’re close.
The problem isn’t a lack of data.
It’s that most businesses aren’t using the data they already have.
Your Sales History Can Predict More Than You Think
Whether you use Sage 50, Sage 200, Microsoft Dynamics 365 Business Central, Exchequer, Pegasus Opera, Dynamics NAV, SAP Business One, Xero, Access Dimensions, Kerridge, Intact, Brightpearl, Oracle NetSuite or another ERP system, you already have years of valuable sales history.
That information can help answer questions such as:
- Which customers are likely to reorder soon?
- Which products are seasonal?
- Which customers are increasing their spending?
- Which products are declining in popularity?
- How does this month compare with previous years?
- Are we on track to hit our sales target?
- What is our likely month-end position based on current trading?
- Which sales teams or regions are ahead or behind forecast?
With the right reporting, forecasting becomes evidence-based instead of instinct-based.
The Spreadsheet Forecast
We’ve worked with businesses where the monthly sales forecast was one of the most important spreadsheets in the company.
Every week someone would:
- Export sales from the ERP.
- Update Excel.
- Copy figures between worksheets.
- Adjust forecasts manually.
- Compare against budget.
- Produce graphs.
- Email a revised version to management.
The process worked.
But it also consumed hours every week.
And because it relied on manual updates, forecasts were often out of date almost as soon as they were finished.
One Sales Director told us:
“We spent more time updating the forecast than actually using it.”
A Real Customer Story
A wholesale supplier approached Illuminis Insight Software because management lacked confidence in their sales forecasts.
The finance team exported data from Sage 200 into Excel every week, where forecasts were manually updated based on experience and recent trading.
Some months they were very accurate.
Others were significantly out.
We started by understanding how the business currently forecast sales.
What factors mattered?
How did customers buy?
Were there seasonal trends?
Did different product groups behave differently?
We then built an automated forecasting solution in Octelas that combined historical sales trends, current performance and management targets into a live forecasting dashboard.
The sales team could instantly see:
- Expected month-end sales.
- Sales against target.
- Year-on-year comparisons.
- Product trends.
- Customer trends.
- Regional performance.
- Sales by account manager.
- Forecast accuracy over time.
The Sales Director later told us:
“Our forecasting meetings became discussions about strategy instead of arguments about spreadsheets.”
Better Forecasts Improved More Than Sales
Another customer originally wanted better forecasting for the sales team.
What they didn’t expect was the impact across the rest of the business.
Because forecasts became more accurate:
- Purchasing could order stock with greater confidence.
- Finance improved cash flow forecasting.
- Operations planned staffing more effectively.
- Production scheduled work earlier.
- Management made investment decisions sooner.
The Managing Director commented:
“Improving sales forecasting improved the whole business.”
Forecasting Shouldn’t Depend on One Spreadsheet
Many SMEs have one person who understands the forecasting workbook.
Everyone relies on them.
If they’re on holiday…
The forecast waits.
If they leave the business…
Nobody wants to touch it.
We’ve seen forecasting spreadsheets evolve over ten years, becoming so complex that even small changes feel risky.
At Illuminis Insight Software, we believe forecasting should belong to the business—not to a spreadsheet.
We Build Around the Way You Forecast
Every business forecasts differently.
Some forecast by customer.
Others by product.
Some by sales representative.
Others by territory, branch, product group or division.
Some work weekly.
Others monthly or quarterly.
That’s why we never provide off-the-shelf forecasting reports.
We spend time understanding how your business works.
We review your existing Excel models.
We understand your assumptions.
Then we recreate and improve the process inside Octelas, removing the repetitive manual work while keeping the reporting familiar.
More Than Software
Software alone won’t improve forecasting.
You need people who understand reporting.
People who understand ERP data.
People who understand business.
That’s where Illuminis Insight Software is different.
We don’t simply install software.
We become your long-term reporting and data partner.
We automate data extraction.
We eliminate repetitive reporting tasks.
We maintain your reports.
We improve them over time.
As your business changes, your reporting changes too.
Our customers don’t need an in-house reporting specialist because they already have one.
Make Better Decisions With Better Forecasts
A good forecast doesn’t eliminate uncertainty.
It gives you the information to respond to it sooner.
Octelas, developed by Illuminis Insight Software, automatically analyses data from Sage, Microsoft Dynamics, Exchequer, Pegasus Opera, SAP Business One, Xero, Brightpearl, Oracle NetSuite and many other ERP systems to produce accurate, automated sales forecasting tailored to the way your business operates.
Instead of manually updating Excel spreadsheets every week, your sales and management teams receive live forecasts, trend analysis and performance reporting that help improve planning, increase confidence and support better business decisions.
That’s why businesses across manufacturing, wholesale, distribution, engineering and many other sectors choose Illuminis Insight Software as their trusted reporting and data partner—helping them spend less time building forecasts and more time achieving them.