How it works

Chart showing leading indicators.

Leverage a data-driven methodology

We've built an econometric model (VAR) to identify leading indicators. Vector autoregression is a workhorse model in macroeconomics that defines each indicator as a function of other indicators. This way, instead of treating each indicator’s impact separately, the model captures interactions between them and their influence on your sales.

By using a lasso penalty through cross-validation, we ensure that only the relevant indicators are represented, delivering the most accurate results.

Improve planning agility through
scenario analysis

Forecasting and planning based on historical data and assumptions are no longer sufficient
to help your organization meet the challenges that come with volatility.

By conducting a scenario testing, you put sensitivity bounds on your forecast's range,
giving you a clear picture of how extraneous macroeconomic factors and
future assumptions may affect the organization's forecasts.

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What-if series

Exploring the what-ifs

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Conducting a scenario analysis in practice

Identify relevant variables

You've got your baseline numbers calculated for each variable. Identify specific volatile variables that you suspect could have an impact on your forecast.

Make adjustments

Tweak not just one or two. You have the option to adjust multiple variables simultaneously at each given time range.

By leaving all other variables unchanged, you can conduct a sensitivity analysis and view the impact of the adjusted variable.

Get an overview of how they would impact your forecasts and pivot accordingly

You've got your baseline forecast. With the capacity to monitor each and every variable, you get to play out specific scenarios, both pessimistic and optimistic. This gives you the control and capacity to prepare for these situations.

Is there a particular scenario you’d like to simulate? Contact us and let our experts know.