Business Planning Baseline Generation
Business Planning Baseline generation is used to create a starting point for planning based on
historical ledger data. The generated baseline can either serve as a reference point for planned
values but can also be incorporated directly into the plan as a manual planning transaction.
Analyzing Historical Data
Before generating the baseline, users can analyze historical balances of combinations of
planning dimensions. This analysis is performed in Business Planning Baseline Page and helps determine which
combinations are most suitable for creating an accurate baseline.
Generating a Baseline
A baseline can be generated from either:
- Planning Unit page – Select one or multiple planning transaction(s) and
access the baseline command.
- Planning Units page – Select one or multiple planning unit(s) and access the
baseline command.
- Business Plan Baseline page - Select one or multiple row(s) and access the baseline
command.
When the Generate Baseline assistant completes, historical balances from the selected ledger
and business plan are sent to The Forecasting Service to produce the baseline.
Forecast Models
The Forecasting Service supports seven model variants for calculating the baseline:
- Adaptive exponential smoothing with level
- Bayesian
- Brown’s smoothing with level and trend
- Exponential smoothing with level
- Exponential smoothing with level and trend
- Naive
- Regression line – Least squares
For each planning dimension combination, the forecast service evaluates which model best fits the data. The
evaluation compares how well each model forecasts the last 12 periods of available ledger data,
using MAE (Mean Absolute Error) as the accuracy metric.
The winning model is then used to generate the baseline for the selected output periods.
Results are displayed as a separate planning transaction with source Business Planning Baseline. Alongside
generated balances, the system also presents:
- The selected model
- The WMAPE (Weighted Mean Absolute Percentage Error) score. The WMAPE metric measures how
well the selected model forecasted the last 12 periods of available data. Unlike MAE, which was used for
selecting the winning model, WMAPE allows for comparing forecasting quality across different time series, not
just within a single series.
Best Practices and Limitations
- Use at least 24 periods of input data (preferably more) to ensure realistic accuracy.
- Forecasts are only reliable if historical data reflects future developments.
- If known changes (e.g., trend shifts, volume jumps) will occur, users must manually adjust
the forecast.
- For multi-company scenarios, the currency balance setting must be configured consistently
across all included companies: it must either be enabled for all companies or disabled
for all companies. If it is enabled, the same code part must be used across all
included companies.
Multi-Company Planning
For multi-company plans:
- All companies must use the same accounting calendar.
- Companies must be connected to a planning entity in the plan-holding company.
High-Level Planning
Users can plan at a higher aggregation level by setting selected code parts as “not
used” in the planning unit. In this case, ledger balances for unused code parts are
aggregated before being sent to the forecast service.
In addition, it is possible to generate baseline on node level in an accounting structure. In such scenarios one
account will represent all other accounts connected to the same node or below in a selected accounting
structure.
Baseline Processing and Cost
- Baseline is processed in batches of 200 combinations of planning dimensions.
- Each batch of 200 combinations incurs a fixed cost.