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Every forecast has a certain error band around it, and would say that forecasts are accurate as long as the actuals come in within that range.

Common problems associated with forecasting include the following:

  • Dynamic business environment: Annual forecasting and budgeting cannot keep pace with today’s ever changing business environment because the information produced is often out-of-date and irrelevant. Additionally, end-to-end processes of manual forecasting takes two to five weeks to finalise, which also eat into resources and increased costs.
  • Accuracy and version control: Despite technological advances, many organisations still rely on manual spreadsheet models to complete their forecasting and budgeting processes, with multiple versions and revisions throughout the process.
  • Building the forecast around the target instead of reality: pressure to meet targets often result in the tailoring of forecasts to meet these expectations, not considering the extremely unpredictable market which can lead to high risk decision making.
  • Unbalanced view between risk and reward: If you believe that the risk is lower than it really is, you could make poor risk/reward decisions.
  • Historical Budget Comparison: many companies create their upcoming forecasting based on the previous years’ findings. This leads to huge errors due to out of date data  and changing market wants.
  • Static Annual Forecast: often planners and forecasters create one budget for the year and leave it on the shelf until next year. Annual budgets should be adjusted monthly in preparation for board meetings to provide an updated forecast for the fiscal year, however with many organisations working off spreadsheets, this proves a lengthy and timely task.

Forecasting examples

Infor business intelligence BI - forecasting

Infor d/EPM

Birst forecasting