Brazilian IA startup Fhinck creates a solution to identify burnout risk
Paulo Castello, founder and CEO of Fhinck. Photo: Courtesy

Brazilian AI startup Fhinck creates a solution to identify burnout risk

Fhinck's algorithm generates and analyzes data on employees' working hours, processes and platforms used by the company in search of opportunities to increase efficiency

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A study carried out by the District in partnership with KPMG, Pixeon, Bosch and Stradigi AI showed that 2020 was the best year for Brazilian startups focused on artificial intelligence solutions, largely due to the digital transformation boosted by the pandemic, which abruptly changed the routines and work processes, requiring companies and employees to adapt quickly. Artificial intelligence solutions have gone from “a differential” to “elementary”, according to the report.

This is the background for Fhinck, a Brazilian AI startup that developed a solution for analyzing data on the operational efficiency of people, processes and platforms. Founded in 2014, the startup operates in the United States, Canada, Mexico, Argentina, India and Singapore, besides Brazil. Among its clients are global companies such as Accenture, Unilever, Natura and Kroton.

The algorithm developed by Fhinck generates data related to employees’ working hours (People Analytics), work processes (Process Analytics) and the set of systems and tools used by the company (Platform Analytics).

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“Fhinck’s solution is based on data science and therefore provides a more assertive view of what is happening in the company. Sometimes it reveals something that even the leaders didn’t notice. This is the direction the world is heading in, we need to use data, intelligence, statistics and combine this whole set of information with analysis. It’s people science,” says Paulo Castello, founder and CEO of Fhinck.

Castello explains that, when installed on computers, the software starts to identify where there are opportunities to increase operational efficiency. For example, the collected data can give insight into work routines and warning signs – such as overload, excessive working hours or even risk of burnout –, whether in the office or at home. The processes are also analyzed by the software, which collects information about the activities performed and how many “clicks” (or steps) are needed, as well as which activities could be eliminated, optimized or robotized. Besides that, the software takes a look at the corporate systems and interfaces used by the company to verify that these tools are adequate for the expected results.

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In a pre-pandemic scenario, this kind of intelligence was interesting so that companies could better understand their processes and plan the necessary adjustments. The pandemic, however, by profoundly altering work routines, took data analytics tools to another level.

There’s a pain that exists in all companies: when you need to understand a process, you need to look at the process and the people. But the processes and interactions are more and more inside the computer, less visible. Fhinck’s solution maps this scalably and more accurately.

Paulo Castello, founder and CEO of Fhinck

Algorithm to identify burnout risk

One of the most sought-after features of Fhinck‘s solution is the one that identifies a series of variables associated with Burnout syndrome among employees. According to the World Health Organization, Burnout is a work-related phenomenon, an occupational syndrome that can lead to feelings of exhaustion, among other symptoms. Burnout already existed before the pandemic, but recent studies that try to understand the impacts of the health crisis on work and mental health suggest a significant increase in symptoms associated with the diagnosis.

According to a survey commissioned by Microsoft at the end of last year, 44% of Brazilians interviewed said that the pandemic has increased the feeling of exhaustion related to work. Globally, the survey showed that 54% of workers felt overwhelmed and 39% said they were exhausted.

Fhinck data panel. Image: Fhinck/Courtesy

Based on how the employee works daily on the computer, Fhinck’s algorithm measures workflow; number and frequency of daily meetings; how long the employees stay online, including after-hours; whether or not they meet break times and how often they have been working overtime, among other variables.

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Based on this data set, Fhinck identified, during the first year of the pandemic, a 12% increase in the workload and a 17% increase in the overlap of professional commitments and personal activities, resulting in a longer workday. Data also showed that the overload added to social isolation increased the risk of Burnout cases by 27%, especially among senior professionals and in leadership positions.

The reports generated by the startup, says Castello, can help leaders define changes in processes and teams, for example, calibrating goals, demands and results and outlining with more precision the ideal professional profile for each function.

The typical 8-hour workday was designed a long time ago. Companies need to ask themselves how this workday works for their business model and for their employees. Companies can adapt the journeys according to the profile of each employee; in the same way, they can adjust the teams according to the demands of each department. For that, they need data.


In search of a Series A

Founded in 2014, Fhinck has already developed projects for global clients in 15 countries. Castello does not reveal the startup‘s revenue but says the company has grown by 500% per year and is now in the process of analyzing a Series A round to expand the sales team and open offices in other countries. The startup received a Seed contribution of undisclosed value from Verve Capital, an American venture capital fund focused on early-stage startups.