Forecasting Net

Look into the future

What is the Forecasting tool?


The Forecasting Tool is an Excel* based application that can generate valuable forecasts, in just 4 easy steps, for any growth process over time that has an S-shape (cumulative values) or Bell-shape (per period values).
The Forecasting Tool can be used for data sets of different nature, such as new product or technology market penetration, customer installed base evolution, cumulative product sales, new ideas adaption, spread of news, population growth, spread of epidemics, and virtually any growth process that has an upper limit and resembles an S-curve or a Bell-curve. 
In order to use the Forecasting Tool with per period data (Bell-curve) you should first transform the process to an S-curve by using cumulative data i.e. the sum of all data until a certain period. For instance, if your data represent new customers per year, you should use the sum of all new customers from the first year until each year (i.e. the customer base evolution).
All you have to do is provide the actual values of the data set per time and press the SOLVE button (you need to have macros enabled). After the calculation is completed, the Forecasting Tool will produce the following estimates:
Future values of the growth process for a selected period


The maximum value that the data set is expected to reach


The expected life cycle of the growth process (i.e. the time that it will take to be completed)


The midpoint around which the growth process evolves (i.e. the point in time where the growth process is halfway to completion)

Example cases

The following are some indicative example cases where the Forecasting tool was used (in some cases with other tools as well) to generate future insights.

A successful forecast of the evolution of the Greek GDP performed near the end of the Second Economic Adjustment Program for Greece in 2014. In order to evaluate the course and future potential of the Greek economy in terms of GDP value and growth levels, we used a double s-curve model with a seasonality effect and publicly available data from the Hellenic Statistical Authority. Although obviously simplified, the aforementioned model sheds some light on the dynamics of the Greek economy, foreseeing a mild recovery at lower growth rates compared to those before the crisis.

A successful forecast of the evolution of the number of reported cases of the 2014 Ebola virus outbreak. In order to estimate the evolution of the disease, we used the s-curve model and publicly available data. According to the generated forecast by the model, we anticipated the evolution of the epidemic and its subsequent conclusion.

The increased CO2 concentration levels due to human activity contribute to global warming with significant repercussions to our planet. In this case study, the analysis of the global CO2 concentration levels from 1900 up to 2008, unveils a two century growth process that is currently half way to completion leading to 17% higher CO2 levels in the atmosphere, by the year 2050.
Following a previous entry about global CO2 concentration level, an analysis of the global temperature increase is performed, for actual data from 1950 up to 2010, confirming global warming by more than 2º C between 2000 and 2100.

Indicative applications

Some applications of the Forecasting Tool that you may consider.

Product or company sales

Customer installed base

Enter your product sales, in values or quantities, per period and use the Forecasting Tool to make future estimates to identify your sales potential. Use cumulative data i.e. sum of sales until each period.
Enter the total number of active customers that you have every month or year and use the Forecasting Tool to generate future estimates about your installed base.

Social media traction

Technology adoption

Count the number of social media accounts followers, post likes, post reshares, comments, or any other social media engagement indicator and let and use the Forecasting Tool to estimate the evolution of your social media traction.
Enter the total number of adopters of  a new technology per year and use the Forecasting Tool to generate future estimates of the market.

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