Nexala uses a variety of techniques that identify patterns and trends in the previous history of events or activities and then calculates/forecasts the potential of that event or a similar event re-occurring at some point in the future. For example a potential peak in stock demands; the likely time of part failures, and assisting with revenue forecasting.

The forecasting Application supports a number of different statistical algorithms, including linear regression, exponential smoothing and moving averages. Event models can provide adjustments to the forecast for special events like promotions or seasonality, or other irregular occurrences. It is also possible to adjust for events of several different types within one forecast model.

Multiple level models allow for the aggregation of data into groups that can be reconciled using a top-down or bottom-up approach to produce consistent forecasts at all levels of aggregation.