Rede Ímpar
Unidade Local de Saúde de Matosinhos
Sabará Hospital Infantil
Unilabs
Unimed Fortaleza
Santa Casa de Misericórdia da Bahia
Centro Hospitalar de São João
Pró-Saúde
Pulido Valente
Notredame Intermédica
Luz Saúde
Hospital de Santa Maria
Hospital Platô
Hospital Pequeno Príncipe
Hospital LeForte

SISQUAL®WFM innovates with new Forecasting model

SISQUAL®WFM innovates with new Forecasting model

On 30/06, the results of the Project ‘RH 4.0 FeD – Forecast and Automatic Sizing for Retail Teams‘, developed in co-promotion with the University of Aveiro (UA) were presented to the public.

Following the release of the upgrade made to the existing SISQUAL® Forecast module, the project was based on the creation of new forecasting models to generate the sizing of teams according to different external variables (such as events, weather conditions, among others) and its application in order to reduce possible errors.

“The goal is to use data science in an automatic way to forecast and dimension teams without human intervention”, says Jorge Costa, SISQUAL® WFM‘s Chief Product Officer.

New Technologies make processes easier

The ‘RH 4.0 FeD‘ project was based on the implementation of emerging technologies (Machine Learning) in order to perform tasks automatically using historical data. This means that “the algorithm used works from scattered data, transforming them so that they all focus on the same dimension” explained Martim Sousa, Information Systems’ Technician from University of Aveiro, who was one of the team members involved in the project.

In its first phase, Machine Learning models were used to predict time series, which could determine customer flows. After the exploratory phase, and after testing several prediction models, the UA team identified a model with superior performance for customer forecasting/team sizing, allowing the integration of machine learning models with SISQUAL®WFM.

“We now have a completely different Forecast / sizing module in terms of automation, and we’re able to sell the model as a service, project, or even as consultancy,” says Jorge Costa, CPO of SISQUAL® WFM.

 

Model is adjustable and universal

The new SISQUAL® Forecast ML (Machine Learning) has the advantage of being able to adjust to new markets, serving as a universal model for different geographies.

Another benefit of the solution is the upgrade to perform as a “short-term version” of SISQUAL® Forecast, allowing the use of short-term execution plans for each business area i.e., this automation allows managers to redistribute work to the team at least one day prior.

More than 75,000 managers worldwide use SISQUAL® WFM, making it a global solution, placing the software at the forefront of mechanisms that boost workforce management and increase companies’ productivity.

 

See the event’s gallery below: