The LucaNet App for Predictive Analytics - powered by future

The LucaNet App for Predictive Analytics simplifies financial planning for companies. The core methodology of the app uses future, forming the basis for smart and objective planning activities. What can the app do, what’s behind it, and what makes it special? We explain it in this blog post.

Predictive Analytics is not just for large enterprises

We want every company to benefit from Predictive Analytics, not just large corporations, but also small and medium-sized businesses. For this reason, we decided to incorporate our expertise, developed over time, into software that provides easy access to Predictive Analytics: our future platform.

And since we believe that the synergy between sophisticated algorithms and a well-maintained and standardized data base is invaluable, we partnered with LucaNet. LucaNet is a software company for financial consolidation, planning, reporting, and analysis, facilitating financial reporting, planning, and reporting for over 2,000 clients worldwide. The Predictive Analytics app, developed jointly by LucaNet and us, is based on our forecasting core from future.

A unified data base is highly valuable

The Predictive Analytics app is an extension of the LucaNet module LucaNet.Planner, which enables customers to conduct professional financial controlling and integrated financial planning. This unified system allows to automate and flexibly manage planning processes. In the past, a forecasting assistant was part of this module, allowing to develop a detailed planning time series. This functionality is now complemented by the sophisticated forecasting methodology from prognostica, which is state-of-the-art in the field of forecasting and can be purchased as an extension to LucaNet.Planner.

The data base for the time series that the Predictive Analytics app generates forecasts for is based on accounts where all bookings are recorded in the LucaNet software. In this way, different items or cost centers can be planned, such as revenue, material, or personnel needs. In addition to point forecasts, the app also provides a forecast corridor, which quantifies the forecast quality. What may seem simple on the surface involves a large amount of calculations behind the scenes.

The app’s major advantage is that by using a standardized data base, all existing functionalities in LucaNet can be fully utilized: The effects on the income statement, balance sheet, or liquidity are immediately visible from the planning. Defined booking rules are automatically applied, and reports can be generated with little effort.

Financial forecasts with and without influencing factors

In addition to purely history-based forecasting (e.g., where nothing but historical material costs are used to predict material costs), forecasts can also incorporate additional influencing factors (covariates). Up to five such factors can be added to the software for each time series. The app evaluates and ranks their predictive power and then suggests which model to use for generating the forecasts. The planner is flexible in choosing the influencing factors, which can include economic or industry indicators (external information) as well as internal information, such as the revenue of another business unit or a subsidiary.

With the provided functionalities and results, the user can also perform scenario planning in LucaNet: The lower and upper bounds of the prediction intervals can be interpreted as worst- and best-case scenarios. It is possible to explore the impacts on income statement, balance sheet, or cash flow if actual values fall within the prediction interval limits. Additionally, future values of predictive influencing factors can be assumed, allowing different scenarios for the target time series to be simulated, such as expected economic growth or increasing rental costs.

In this section, as in many others, the app emphasizes the interplay between automated data analysis and planner input: Since the planner knows best what is important in their business area, they have the final say. An automatically selected predictive influencing factor chosen by quantitative methods is presented to the planner and accepted or not before it is included in the forecasting models. The same applies to outliers. Although the app automatically detects outliers and replaces them with meaningful alternative values, they are only used for further analysis if the planner explicitly allows it. This approach prevents artificial enhancement of the time series and ensures the validity of prediction intervals. Lastly, the planner can overwrite the statistically determined forecast values at their discretion.

Objective planning figures at the push of a button

In summary, the LucaNet App for Predictive Analytics delivers on its promise and brings us closer to our goal of making Predictive Analytics accessible to every company: It enables objective planning figures to validate manual planning. With precise planning figures generated in no time, shorter intervals for collecting them become a reality, and the planning process can proceed without delays. The parent company, for instance, can review and adjust planning figures from subsidiaries. And a data scientist is not required for any of this.

Our forecasting & AI technology can be easily integrated into existing software systems thanks to flexible interfaces. If you’re interested in learning more, contact us: