The model which the demand for service is forecast, is made by analyzing several past data such as number of guests/visitors, sales or/and the number of transactions conducted during a specific time period.

The type of data to be analyzed will vary accordantly to client`s industry, particular requirements and availability of the data itself.

This past data makes the foundation of the forecast service demand model although

other measures are also considered since the past data can be influenced by external and timely situations such as:

• Weather
• Events
• Marketing and Ad campaigns
• Etc...

Moreover, considering extra elements that also greatly influences the demand for service for instance:

• Seasons
• Days of the week
• Point in time
• Etc...

Winworks develops and applies techniques on its forecast service demand model analysis that continuous considers those measures and elements.

Furthermore, as the demand for service changes on a daily basis, the mid/long term can be influenced by the variation in business or sector growth. The model initially created by inputting monthly data is continuously and automatically readjusted, and the mechanism that can reflect on the latest business circumstances at any point in time is mostly built already into WINWORKS One.

The Winworks calls this prediction method "Adaptive Reduced Model".